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Three years after October 7, the conversation about antisemitism reaches far beyond the immediate aftermath of the attacks. It touches universities, political movements, foreign funding, and the everyday decisions Jews make about belonging.

This week, I spoke with Charles Asher Small about how those all connect, and what he believes institutions and Jewish communities should do next.

Small leads the Institute for the Study of Global Antisemitism and Policy (ISGAP). He described its ambition to connect academic research with public policy, and our conversation followed that path: from a broad diagnosis of democratic fragmentation to questions about evidence, university leadership, and Jewish identity.

His opening argument was that antisemitism thrives amid wider social and institutional weaknesses. He described the extreme left, extreme right, and radical political Islam as different forces attacking the democratic centre. In his analysis, hostility towards Jews provides a point of convergence between movements that otherwise have little in common.

Foreign influence and the institutions shaping opinion

That led us to ‘strategic entryism’, the term his team uses to describe ideological influence entering established institutions. Small focused on the Muslim Brotherhood and Qatar, arguing that funding and networks can advance the movement’s ideas within Western universities and cultural life, something I have covered separately at JNS. He sees universities as especially consequential because they educate future journalists, professors, and political leaders.

He argues that the financial pressure faced by universities makes them more receptive to outside money, while the ideas circulating within them eventually reach wider society - a serious allegation about institutional influence.

“If you think of what happened at universities on October the 8th, 2023, this to me is a watershed moment where people, I think, were shocked,” he said. “But this has been sort of in the works for decades.”

I wanted to understand how his team measures the impact of the funding it identifies, beyond pointing to protests or shifts in rhetoric. He cited ISGAP’s 2023 “Networks of Hate” report, saying universities receiving Qatari funds had “300% more instances of antisemitism” than those that did not, although he acknowledged the difficulty of scientifically proving the broader ideological relationship he described.

The exchange raised an essential question: how do we establish what money changes, as well as where it goes?

Criticism, antisemitism, and the question of belonging

We also discussed his concerns about propaganda and social media. While the central focus of ISGAP has been the Muslim Brotherhood and Qatar, Small described Iran, Russia, and China as contributing to an environment that fragments Western societies through infiltration and propaganda, including the use of bots.

It was here I wanted to challenge him. Universities have long been places of protest, and I believe Israel’s government is as open to criticism as any other. So where does legitimate political opposition end, and antisemitism begin?

“We have to define antisemitism in a scientific, comprehensive manner that allows for criticism,” he said, accepting that Israeli policies can be criticized. But institutions must also recognize rhetoric and movements that dehumanize Jews.

Later, he spoke about Jewish families questioning whether they could remain in countries where they had lived for generations (something I have written about before), and framed this vulnerability as a warning about the condition of democratic citizenship.

The new Hebrew University-European Forum Barometer offers a passing echo of those concerns: Israeli respondents overwhelmingly viewed Israel as safer for Jews than Europe, while Jewish Israelis reported strengthened Israeli identity. Those are perceptions, rather than a test of Small’s explanations, but they show how immediate questions of safety and belonging have become.

When I asked what he would do as a university president, Small’s answer began with education. Students should study democratic principles and understand their responsibilities as citizens, he argued.

“To live in a democratic society, every generation has a choice.”

We discussed greater transparency around foreign university funding and ISGAP’s efforts to turn research into policy through the DETERRENT Act, a congressional bill designed to increase oversight and lower reporting thresholds for foreign gifts and contracts at colleges and universities that receive federal student aid. The House of Representatives passed the bill in March 2025, and it has been referred to the Senate.

“Jewish Consciousness” and life after October 7

The conversation's final turn came when Small described ISGAP’s Jewish Consciousness framework, which draws parallels from South Africa’s anti-apartheid movement and the influence of Black Consciousness.

He argued that we Jews should define ourselves by drawing on our own traditions, knowledge, and history rather than accepting labels imposed onto us by hostile outsiders.

I raised what I called “the hijacking of history”: How Israel’s critics exploit language associated traditionally with Jewish persecution, and apply it against Jews themselves. “One of the things that we need to do is define ourselves based on our terms,” he replied.

That thought brought the episode’s different strands together. Small’s proposed response combines research, institutional accountability, democratic education, and a deeper understanding of Jewish identity. Our conversation moved between what others say about Jews and what Jews can say about themselves.

Three years ago, questions were urgent and immediate: security, safety, who was funding what. This episode suggests those questions remain, but have evolved beyond how institutions should respond to antisemitism, toward who gets to define what being Jewish even means while that fight continues.

[Preview: “Strategic Entryism”: How Qatar’s money entered America’s universities]

There was a moment in my latest conversation with startup psychologist Yael Daniely that surprised me. She described someone who walked into her clinic and asked to keep his laptop open so that Claude could run live for the entire session.

“He came with Claude to the room and asked to keep Claude open because he must be in contact with Claude and give him [updates]… because Claude is working and he must be reactive to him. Otherwise Claude will be stuck.”

She said no. “It wasn’t easy for him to close the laptops slowly, slowly.” He couldn’t understand why, in that moment between founder and therapist, the chatbot needed to be left at the door.

It’s a funny image, but it speaks to something much larger happening among founders in tech.

Yael Daniely has spent years researching the psychology of the individual founder, but also the relationship between co-founders and, interestingly, the relationship between a founder and their family spouse. Over her career, she has helped individuals and pairs work through trauma, anxiety, financial concerns, and (increasingly) the impact that AI has on their roles and identity.

She described that moment in her office as a symptom of something bigger than one dependent client. AI isn’t just changing how founders build companies; it’s becoming a relationship for some of them. “Everyone says that their best friend now is ChatGPT... they can share all their dreams, secrets, fears, and emotional burdens and issues with their partner with ChatGPT.”

Daniely is not dismissive of AI as a source of support. She said a conversation with a chatbot in the middle of a sleepless night may help someone calm down, and that some tools can complement therapy. Her concerns are placed in founders who put too much emphasis on a responsive machine that can supply everything a person needs from a relationship.

“They cannot completely take over the connection and the relationship that’s happening in the room with the therapist,” she said.

AI has entered the chat

The intense capital around these technologies is mirroring the emotions. Global startup funding hit $506 billion in the first half of 2026, the biggest half-year in venture capital history, with AI startups accounting for around 77% of all that investment.

Three companies (OpenAI, Anthropic, and xAI) that build addictive chatbots were behind $237 billion of that total.

Against this backdrop, the impact of AI is actually two-fold. Not only are founders forming attachments to their AI tools, but they’re also watching the technology overhaul the entire process of work, causing them to develop existential questions surrounding self-worth and identity.

For CTOs, she said, the shift has triggered something closer to professional grief. She shared how some feel they are losing their profession, which they connect to a sense of self. For CEOs, it triggers an anxiety if they see a competitor raise funds quickly, and interpret that news as evidence that they are too slow, too old, or building the wrong thing.

Daniely doesn’t think the answer is rejecting the tools; rather, monitoring “how you control AI versus AI controlling you.”

But that founder who couldn’t close his laptop is the extreme version of a very ordinary 2026 problem: tools designed to make founders faster are starting to make some of them feel like they’re already behind, all while making it easier to swap human connection for an algorithmic companion.

Including, it turns out, inside the therapy room.

You can connect with Yael Daniely on LinkedIn and check out more of her work here: https://yaeldaniely.com/

[Watch a preview: The Founder, the Therapist... and Claude?]

I recorded a conversation yesterday with Alexander Piskunov, a government AI advisor and founding partner at KAAN Ventures, at a strange little intersection of timing.

UN Secretary-General António Guterres had just used his address to call for a multilateral AI risk framework. Sam Altman and Dario Amodei were preparing to appear before the Security Council. And President Trump, predictably, was telling the room that the US had no interest in slowing down.

Eventually, the Security Council session happened - specifically because it felt AI’s security implications weren’t getting enough attention.

Yoshua Bengio, who co-chairs the UN’s scientific panel on AI and is considered a “Godfather of AI”, went first and told council members the dangers posed by advanced AI are “real and imminent.” Amodei warned that AI could become a risk to humanity itself, while Altman pushed for shared global benchmarks to measure AI capabilities and the safeguards companies claim to have in place.

I asked Piskunov the obvious question: does America actually have the leverage to just ignore all of this?

“It’s still quite important to separate rhetoric from the actual steps that would be made,” he replied. It made much of what is happening at the UN this week sound less like policy and more like theater. Effective theater for some, perhaps, but theater nonetheless.

Piskunov is the founding partner of KAAN Ventures, where he's spent the past decade backing deep-tech investments across the US, Europe, and Southeast Asia. More recently, he's shifted into advising governments (Pakistan, South Africa, Kazakhstan, South Korea, among them) on how to build an AI strategy from a position that isn't the US or China.

He doesn’t think Trump’s refusal to engage is dangerous or ignorant, as many believe. He thinks his position makes strategic sense, given the shape of the game governments are playing.

“The AI race is a game where if you lose your first place, it’s almost impossible to catch up given how rapidly everything is developing,” he explained. If that’s true, then every voluntary slowdown is a gift to whoever doesn’t slow down. And if calls for the US to slow AI development don’t apply to China, is that who we want to win and lead this revolution?

As for a potential third place: The EU used to be a contender, but he points out that “the EU is just too over-regulated right now” to remain a key player, and its national champions can’t compete on data or scale anymore.

Rather than simply staying out of the conversation around AI regulation this week, President Trump went the other direction completely - as is so often the case.

"The United States also totally rejects any attempt to construct a globalist scheme to control for the artificial intelligence being spoken of so much now," Trump said (adding that he thinks AI should be referred to instead as ‘superintelligence’ or ‘SI’).

Which brings us to the paradox that started this whole conversation. The same tech executives publicly warning about AI risk and pitching Trump for guardrails are, in Piskunov’s words, making “a very cynical case.” They understand their own limitations more intimately than they let on, and they know that if they can’t out-innovate their competitors, their next best move is to get those competitors regulated.

Safety concern and competitive strategy, in other words, aren’t necessarily different things.

Piskunov thinks the real value lies in the psychological fight, not the race to regulate. Discussions happening this week “open up the Overton window” for the public and show that governments are taking the risk seriously, even if nothing binding follows just yet. And that may be enough for Guterres or Bengio for now.

The week will end with Trump meeting with Xi in Washington - his first visit since 2015. In an act of goodwill, US Treasury Secretary Scott Bessent announced that the two countries will extend their trade truce to January, set to originally expire in November. Perhaps they’re saving this bigger fight for later.

America’s current position isn’t just a rejection of multilateral concern about AI. It sees voluntary restraint or an international framework as a move guaranteed to lose against those unwilling to restrain themselves. And so far, no one in New York can argue otherwise.

You can connect with Alexander on LinkedIn here: https://www.linkedin.com/in/alexander-piskunov/

The Spiro Circle is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

[Catch a preview: Is Trump Right to Ignore the UN on AI? This Advisor Says Yes]

Uzi Krieger has jumped from planes, descended into underwater caves, and skied slopes steep enough to unsettle most people’s stomachs.

When I asked what draws him to it, he put it down to a philosophy he lives by. “I think it’s a theme in life of being a little bit of an explorer,” he told me. “I don’t want to say ‘living on the edge’, but trying to see how far you can go, how hard you can push, and do it in a very structured way.”

For Krieger, now General Manager of Cloud Security and Exposure Management at CrowdStrike, risk is not about recklessness. “It’s not just about jumping off a cliff or diving hundreds of feet underwater,” he explained. “It’s more about taking on a challenge and trying to see how far you can get… That’s how I’ve approached extreme sports, or work, or almost everything I do in life.”

The idea of “structured risk” is interesting to me. I learned it personally at a young age when obtaining my SCUBA license: Plan your dive, dive your plan, I was told. It’s something that also grounds my decisions as I grow my independent media venture after departing from corporate newsrooms last year.

Krieger was the right person to speak to about this idea and how he applied it across his career. He started in corporate America’s telecom sector, running a business unit inside a large, publicly traded company, until he left to pursue something else. “Very early on I realized that moving fast and being able to get really good results is something that can only happen in Startup World,” he explained, which is also what attracted him to Israel’s startup ecosystem.

He went on to found and run several companies, most notably Reposify, an external attack surface management company which CrowdStrike acquired in 2022. CrowdStrike's leadership asked him to help bring more “founder DNA, startup DNA” into the organization.

Krieger credited the mentors of his early startup years with teaching him that line between risk and recklessness. “They had a very unique combination of very strong conviction and an extreme, structured, almost scientific way of how you get to being successful,” he told me. It comes down to preparation, not appetite: “You want to take risk, but it’s not just any risk. Where’s the passion? Are you really all in? What is the plan? Are you actually building a plan, or are you just trying to wing it?”

The new speed of risk

That same instinct now shapes how CrowdStrike approaches its own market, which has hit $243.3 billion, and a stock price circling within distance of an all-time high. Exposure management, which is the practice of identifying and prioritizing an organization’s most exploitable weaknesses, was largely a background chore before AI adoption pushed it into boardrooms. “It’s no longer a question of ‘why do we need this,’” Krieger said of the shift. “It’s ‘how do we move 10 times faster? How can we be ahead of the curve?’”

This mindset gets him safely out of a cave, or back on the ground with both feet, and it’s what separates a security strategy from a scramble. But it requires work.

“You really need to build that muscle. It’s not natural. People are risk-averse, but how do you transform risk aversion into something that allows you to take risks, enjoy the journey, and do it in a way that you become successful?” His question stayed with me until long after our meeting.

The AI era is asking everyone to take risks. Company pivots, career changes, market shakeups… all of them will require us to make decisions or take actions that will impact our personal and professional lives. “It boils down to basic human nature and being a good person. People want to do good; people want to be successful. It doesn’t matter if it’s in a small company or a big company,” he concluded. “I think [it’s about] not losing the edge that you have with a startup, and taking that into a larger organization, and bringing that impact.”

[Watch a preview: Why this CrowdStrike manager skydives, cave dives, and calls it “Structured Risk”]

Well, here it is: Episode 100 of The Spiro Circle.

When I recorded the first episode 18 months ago, I had a rough idea of what this show could be. I wanted it to be a place where long-form conversations about Israeli tech, geopolitics, or society could get broader attention.

Now, with a growing audience across 20 countries and partnerships with international media channels like Forbes, I am proud to see what it is becoming, and that these conversations are getting the attention they deserve. Startup Nation yearned for long-form English conversation, and I am pleased to be helping fill that missing gap.

For the 100th, I brought in Nitay Milner, co-founder and CEO of Orion Security, and Emily Fontaine, Global Head of Venture Capital at IBM Ventures, to talk about why every major company should rebuild its data security strategy in this AI era.

I find it fitting that our conversation on how a large corporate company saw potential in a scrappy Israeli startup was positioned as the 100th episode.

Thanks to all who have joined to share their stories so far, and thank you to all those who keep tuning in.

Onwards to 200. - JS

The data loss prevention industry has organized itself around a relatively stable threat model.

A disgruntled employee may copy files to a USB drive. Or a phishing attack could expose credentials to an outside attacker. Maybe someone accidentally CCs the wrong person on an email with sensitive information. Solutions focused on perimeter controls or policy rules were imperfect, but understandable when the threats were often caused by humans.

But that model is no longer sufficient. According to research by Cyberhaven Labs, whose 2026 AI Adoption and Risk Report analyzed data movements across 222 companies, nearly 40% of all AI interactions now involve sensitive data, with the average employee inputting proprietary information into an AI tool once every three days.

Threats don’t disagree insofar as they disaggregate, accelerate, and, in some new cases, remove the human from the equation entirely.

Nitay Milner, co-founder and CEO of Orion Security, offered a framework for understanding how the landscape has changed. In a recent episode with Emily Fontaine, Vice President and Global Head of Venture Capital at IBM, which backed ORION’s $32 million Series A in February 2026, he described the three categories of traditional data leakage that the DLP industry was built to address: human error, malicious insider activity, and external attackers.

“[Perhaps] I accidentally did ‘Emily@IBC’ and not ‘IBM’,” he said, by way of illustration, “and sent the entire board deck to the wrong person. That happens a lot. I call it keeping honest people honest.”

The second category, he noted, involves deliberate exfiltration, what he called the “Snowden” scenario. The third involved external actors penetrating an organization and quietly siphoning data over time.

Milner co-founded Orion Security in 2024 with CTO Jonathan Kreiner. It aims to replace traditional DLP (data loss prevention) tools with an automated, context-driven platform. Using LLMs and specialized AI agents, the platform continuously detects and analyzes data loss indicators in real time, capturing context for content sensitivity, data lineage, user identity, behavioral intent, and environmental purpose.

New anatomies, new leaks

Traditional categories of DLP remain relevant, of course. But Milner identified two new vectors that are reshaping the problem. The first is data extraction into third-party AI: employees uploading sensitive documents like earnings calls, customer records, or source code to unmanaged AI platforms before those materials are cleared for external use. “Taking the earnings call, which is super sensitive data, before the earnings call report was published, and uploading it to like an unmanaged ChatGPT or Claude,” he said. “It’s very, very sensitive, and data is now in the hands of a third party that you don’t have any agreement with.”

The second vector is data exfiltration not by humans at all, but by AI agents operating inside the enterprise. “AI agents doing human work inside the organization, having access to super sensitive data,” Milner explained. “Think about an AI agent email assistant that has access to your Google Drive, takes the entire customer list and sends it to the wrong person. That’s data exfiltration by AI.”

The scale of this emerging risk is becoming measurable. According to a 2026 Cloud Security Alliance report, 82% of organizations already have AI agents operating in production environments, while only 17% enforce runtime access controls consistently across those deployments.

A separate finding from Proofpoint’s 2025 Data Security Landscape report found that 32% of organizations identify unsupervised data access by AI agents as a critical threat.

Fontaine framed the underlying problem as one of movement, not just volume. “Data is a huge asset that must be protected, more so than ever before,” she added. “It’s moving across clouds, it’s moving across applications, agents, ecosystems. It’s moving across so much more than it was ever before. And we have to make sure it’s secure, that it is governed correctly.”

IBM Ventures, the strategic investment arm of IBM led by Fontaine, operates a $500 million fund focused on AI and quantum technologies — and its bet on Milner and the team reflects IBM’s belief that the arrival of large language models has fundamentally broken the assumptions on which traditional data security was built, creating entirely new leakage paths that legacy DLP tools cannot detect.

A new era for DLP

That governance challenge is exactly what today’s DLP industry is no longer built to handle. Policy-based systems depend on known patterns, like a credit card number matching a regex or a file name triggering a rule. They cannot, by design, interpret context or whether a particular data movement constitutes a legitimate business action or an exfiltration event.

Milner’s breakdown offers enterprises a useful starting point to identify which of the five categories (legacy or AI-era) represents the highest unaddressed exposure in a given environment, and build from there. “Understand your organization,” he concluded. “Based on this real data, get to decisions, train your employees, and help them understand how to use data safely.”

[5-minute preview: Is your AI leaking company secrets? IBM & Orion Security explain]

For two decades, the winning formula in consumer tech was simple: maximize time on screen. Last month that formula got a multibillion-dollar price tag attached to it when Meta agreed to pay roughly $17 billion to settle a multistate lawsuit alleging Facebook and Instagram were deliberately engineered to be addictive to teenagers.

Now, one Israeli investor thinks the backlash could create an opening for a very different kind of consumer product, and for a new generation of Israeli founders.

Oren Charnoff is the Co-founder and a General Partner at Sticker Ventures, a Tel Aviv early-stage fund that invests exclusively in Israeli B2C startups. He sees the settlement as validation of a thesis his fund was already investing behind, based on changing consumer habits among young people. “We want to find more companies whose goal is not to increase time spent on the app,” he said. “We hope to see more ‘IRL’ things being built by Israelis.”

He points to two U.S. examples he admires. The first, Tin Can, is a landline-style phone that plugs into the wall, paired with an app that lets parents approve who their kids can call; Charnoff says it’s doing roughly $80 million in annualized revenue. The second is Board, a digital game console built entirely around in-person play. “The only way that you can interact with it is with another person with you,” he said.

Closer to Sticker’s own market, Charnoff cites Edikted, the Israeli-founded Gen Z fashion label, which The Wall Street Journal recently reported as achieving roughly $460 million in revenue: “They crush it on retail. They crush it for offline discovery.”

Startup Nation’s advantage in the changing market

The shift makes it perfect timing for Israel’s tech DNA to tap into adapting markets. Startup Nation has accumulated decades of expertise in adtech, gaming, fintech and cybersecurity, producing a generation of founders trained to measure, test and optimize. Add to that a new type of internet-native, young immigrant to Israel who is a product of globalization, and those skills can be unleashed on the world’s biggest GDP category: consumers.

“The same quants who do anomaly detection in cyber can optimize the budget, channel and yield of consumer growth,” Charnoff said. He traces the lineage directly to Israel’s earlier tech waves. “Adtech is one of the founding mothers and fathers of B2C,” he said, pointing to the exodus of former ironSource employees now building consumer companies of their own.

The craving to steer away from online apps and toward “In Real Life” extends into dating apps, both in his portfolio’s orbit and out of it. Companies are moving away from “unlimited swipes whose goal is to maximize dwell time” toward an AI concierge model that delivers one or two curated introductions a week, rather than an endless feed of profiles.

According to Charnoff, 38% of Sticker Ventures’ deployed capital sits in the Health & Wellness category - framing the appeal generationally: millennials were “an experiment of unlimited internet access”, he told me, while Gen Z is driving “a huge trend to get back into IRL... experiences.”

Charnoff and Sticker Ventures aren’t betting that the attention-economy giants disappear. But the “hipster move” into B2C investments is placing new bets on the next generation of consumer winners built for the time people spend away from their news feeds, not the time they spend scrolling through it.

“B2C’s been a big part of Israel’s ecosystem for a long time,” he concluded, listing success stories like Waze, Oddity, Superplay, eToro, Wix, Simply, MyHeritage, and others. “We’ve always been doing this… I just think with AI, there’s a renewed interest to do it… It’s just way more attractive to be a B2C entrepreneur now.”

[Preview: Why building B2C in Israel is suddenly a "hipster move"]

Guy Katsovich and I sat across from each other in our shared studio a few weeks ago, discussing what happens when podcasting moves from the media ecosystem into the campaign trail.

Let’s set the scene: We are both former journalists, now running separate podcast operations (one in English, one in Hebrew), and talking about what happens when an interview format becomes part of an election strategy. Katsovich is the co-founder and partner at Fusion VC, a pre-seed platform and a longtime Israeli podcaster, and expects that trend to accelerate as election day approaches.

“If you look at the trend, I would assume... they’ll be interviewed by more and more podcasters... the closer we get to election day,” Katsovich told me.

The 2024 U.S. election showed just how powerful podcasts could become as a political campaign tool, with candidates increasingly opting for long-form conversations that offered more time and unfiltered depth - something traditional television can rarely provide.

Israel’s next election, scheduled for October 27, is already generating a growing political podcast ecosystem, from dedicated election shows to established interview programs. Prime Minister Netanyahu’s campaign has leaned into a circuit of small, friendly podcast studios in recent weeks, trading hard questions for a more intimate, folksy format that lets a candidate control the narrative in ways a more adversarial Channel 12 or Channel 13 panel never would.

Katsovich sees the same pattern and traces it to an obvious source: “Everybody now follows Trump’s steps and tries to interview [on] as many podcasts as they can.”

His show, The Guy Katsovich Podcast, now reaches, he told me, “more than 200,000 people... every month,” almost entirely inside Israel. He’s hosted Yair Golan, Gadi Eisenkot, Bezalel Smotrich, Simcha Rothman, and with an election bearing down, he expects the guest list to grow: “I might do a roadshow for all the politicians that wanna come on the podcast.”

Israel appears to be the latest country that is redistributing its political access during election cycles. Katsovich’s read is that as October nears, “those podcasts will carry more and more weight in how people make their decisions,” because a long-form sit-down is “a real opportunity to really meet and see a politician for one hour” in a way a ninety-second clip cannot replicate.

But the format only works if it stays open. “All the politicians that came to my podcast didn’t ask for preparation, and there were no preconditions,” he told me, before admitting some guests want questions in advance, or want to see the cuts before publication. “This is like... kills the whole point of a podcast,” he said - and I agreed. “If you wanna really do an open conversation, this is not the format” for anyone trying to manage their message.

Startup Nation’s election role

But access is only half of the equation. What politicians choose to talk about matters too. When I pushed him on whether topics like tech and AI sovereignty will actually move votes — a theme this campaign has already flirted with, and one I have discussed on another podcast with ILTV — he identified a key thesis for election messaging. “If in America you vote for economy, in Israel you vote for security, and that’s it.”

[Watch me on ILTV: Maayan Hoffman and I explore whether Startup Nation should weigh in on Israel's first election since October 7]

Whereas the American mantra once promised that “it’s the economy, stupid”, Israel sees things a little differently. As Israelis go to the ballot box for the first national election since October 7, high-tech, cyber, and defense are all what he called “intercollided” into a single binary: are you the guy who keeps the country safe, or not?

That’s the paradox sitting underneath this whole moment. Hebrew podcasting is gaining exactly the kind of reach and intimacy that could reshape how Israelis size up a candidate — and it’s happening at the same time as candidates are working out how to use that reach without actually being tested by it.

[Watch a preview: Israel’s podcast boom could change the next election]

The Spiro Circle is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

America’s fight over data centers is becoming a mainstream political staple. Seven in ten Americans say they don’t want a data center near their home, and more people now believe these facilities harm their community than help it, according to recent polling cited by industry trackers.

Opposition has more than doubled across 49 states over the past year, and in the first quarter of 2026 alone, an estimated $130 billion in data center projects were blocked or delayed by local resistance.

It’s not even a culture war. The backlash against them cuts across party lines: Republicans tend to object on tax incentives and grid strain, whereas Democrats oppose on environmental and resource use. The reasons may differ, but their mutual opposition is a rare instance of bipartisan alignment in American politics.

Into this landscape steps Phinergy. It’s an Israeli cleantech company whose aluminum-air backup generators have become an alternative to diesel in the AI infrastructure race, seeing early support from players in an impressive Google- and Microsoft-led innovation consortium. I spoke to its CEO Emmanuel Levy, who laid out a thesis that the “NIMBY” reflex against data centers collapses once three specific, solvable grievances are addressed.

“People are caring about [them] and are afraid... whether it is pollution, whether it is noise, or it is water consumption,” Levy told me. “If you’re able to explain why a new data center can come without this price on the shared resources, you’re able to bring the debate back to where it should be.”

It’s a clean, testable claim. In Colorado Springs earlier this year, a proposed data center drew objections almost identical to the ones Levy’s technology is designed to neutralize: noise and air pollution from backup diesel generators, and water consumption. The developer countered with a water-efficient, closed-loop cooling design and pledged 60 to 100 permanent jobs. But it didn’t defuse the fight.

Longtime residents cited broken promises tied to a chip plant and a cryptocurrency mine previously sited on the same land, and the developer told local reporters he had never encountered this level of public opposition, despite having built a similar facility elsewhere without incident. The complaints were the same three Levy names, yet the outcome was not.

Why do they need to be in our neighborhoods, anyway?

Those opposed to data centers don’t want them “in their backyard” - but that’s precisely where they need to be. Whereas training AI models can in fact be anywhere, the inference stage of AI - that’s getting the answers back to the customer who inputs prompts - needs strong latency to ensure smooth communication. And those are fast becoming critical infrastructure, which means backup generators need to be precisely alongside those initial centers. “More and more services are AI-based; they need their AI to be as close as possible to the market,” Levy explained. “So that’s the reason why inference in this case is localized next to communities.”

Think of it like being closer to your internet router at home: a reasonable comparison, until you realize that McKinsey forecast confirmed that by 2030 there will be an additional 140 gigawatts of power consumption by data centers. It means that the equivalent of 140 nuclear power plants will need to be set up in four years in order to manage the computing power. “You understand why there is a bottleneck,” he added.

Another question arises: whose job is it to close this trust deficit? Levy describes a cooperative, three-layer division of labor: new technology needs to be “socialized” to the market, regulators need to update rules that still legally define backup power as diesel-only, and developers need to carry the message to communities and win consent.

Phinergy was selected from a field of more than 70 proposals by the Net Zero Innovation Hub, a consortium formed by Google and Microsoft specifically to source alternatives to diesel backup power, with the pitch vetted privately by senior industry advisors (including a former chairman of Vertiv's technology board and a former Microsoft data center technology executive) before hyperscalers would take it seriously. "It's rarely cold calls," Levy said of how deep tech actually reaches Google and Microsoft. "Without that, it's very, very difficult for people to take you seriously."

Phinergy’s pitch for cleaner data centers is the start of the battle. Removing diesel noise and emissions from their footprint retires one legitimate grievance from a list that has grown to include broken trust, property values, and a broader unease about ceding land and resources to AI infrastructure. International polling on the same backlash lists the objections in similar order: water, energy, land use, noise, air pollution.

But it still needs to overcome the lingering challenge of a lack of community consent. Clean power may be necessary to end the data center fight. On the evidence so far, it isn’t sufficient.

You can learn more about data centers and how Phinergy can fix the bottleneck in the entire episode.

[For now, here is a preview: The NIMBY problem with AI data centers, explained]

I’ll admit it upfront: I’ve tried alternative meat on my own barbecue, and they’ve never been exactly a slam dunk for me. So when I sat down with the Chunk Foods founder and CEO Amos Golan for this latest episode, I wasn’t chasing a hype piece on the wonders of foodtech. I’ve written those stories before. What I wanted to know was whether the economics of fake meat had finally changed.

Turns out there is a number that can make that argument: $6.83, the price of a pound of ground beef in the US as of July 2026.

Beef steaks averaged $12.80 a pound back in May, up 16% year-on-year; the national cattle herd is sitting at its smallest size in 75 years. These Bureau of Labor Statistics numbers show a worrying trend for families and young people seeking affordable protein sources.

Chunk offers clean-label, plant-based whole cuts that look (and cook) just like beef. And today’s price rises may be a way for the fake meat industry to undergo somewhat of a comeback.

Golan has been watching this trend as closely as I have. “You don’t need to just talk about the need for the price of [fake] meat to go down,” I said to him. “You can also talk about the price of meat going up.” His answer: “Exactly.”

He’d already walked me through the math before I said it. “Ground beef in the US used to cost $4 [per pound]. Now it’s $5, $5.36. A steak is $10 to $20 a pound.” That was true when we recorded this episode in June, but beef has kept climbing since, which is, for those of us doing the weekly shop, the whole point of his pitch.

Chunk’s bet was never to compete with beef on ideology. People like me who genuinely like eating meat aren't suddenly going to stop because someone tells us it's better for the planet. “The experience needs to be good enough. The price needs to be good enough, ideally cheaper than meat,” he added. He was blunt that this is a demographic shift, not a moral one. “People are less altruistic, I’d say, at least externally, in how they talk about the food they consume.”

Ultimately, beef isn’t getting cheaper anytime soon. Forecasts put 2026 beef price increases as high as 18%, and analysts aren’t projecting relief into 2027. Chunk doesn’t need to win me over on taste alone. It needs the gap between $6.83 and its own shelf price to keep doing the argument for it.

It might be time that the alternative meat market comes back for seconds. And those at the dinner table may finally be ready for what’s on the menu.

[PREVIEW: Rising beef prices are doing Chunk Foods' marketing for them]

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Glilot Capital’s internal AI agent has a name and a full-time job - Elliot. It reads deal memos, surfaces founder meeting summaries, coordinates diligence advisors, and routes work across one of Israel’s most prominent VC funds.

Amit Spitzer, Glilot’s CTO and CISO, built it largely on his own, without a dedicated budget, while running the fund’s security operations in parallel.

“We need some super agents, some super tools, some ‘super employee’,” he told me. “That were able to connect to all the tools and all the processes and basically help streamline every manual work that used to be done up until that point.”

Arik Kleinstein, Glilot’s co-founder and managing partner, added that before the agent existed, an investment decision required five to ten diligence calls conducted manually. Now, the firm can screen advisors, make contact, present a company, and schedule calls at a pace that would have been unimaginable three years ago. And since Glilot is a seed and early-stage investor, operating in a market where the window between a promising founder and a closed round can be very short. An ‘employee’ like Elliot can help VC funds find their next gold mine.

Yet for all of its assistance, Kleinstein maintains that the agent cannot do the actual job. “If you invest very early, you invest basically in two things,” he said. “One, the team, and in their imagination. And AI is not a team, and AI doesn’t really have a good imagination.”

The difference between what AI accelerates and what it cannot replace carries broader implications for how the industry should think about the technology it is rushing to adopt. Even I, as a writer, admit to using the technology in my work; transcriptions take seconds instead of hours, and I have tweaked my agents to be harsh in their review of my work before I submit to a (human) editor. It means I have more time for research and deeper conversation with my guests.

In Glilot’s instance, the fund is as committed to AI as any in the market, and it evaluates every investment, in the words of managing partner Lior Litwak, “through a GenAI lens.” But Kleinstein and Spitzer make a sharp distinction between AI as infrastructure and AI as judgment. While AI in our workflows is indeed transformative, the ability to assess an unproven founder's leadership potential remains out of reach — at least for the investing Glilot does.

“All the analytical part, to look at the technology, to look at the markets, to look at the products, all the checklist that every VC is doing… that can be significantly augmented with AI,” Kleinstein said. “But to assess the quality, the leadership, the ability of a founder, many times a first-time founder, never done it before, to actually build a team, that’s something where AI just cannot help you.”

Spitzer adds another dimension to this argument. Describing his CISO position as “part of my soul, not just my experience,” he stated that the people who get the most out of Elliot will not necessarily be the most technical members of the team. They will be the ones who know what to ask, and how. “You still need the experience of the person,” he said. “Because now you need to know what to ask the AI, how to ask it, how to navigate in the path of AI. And that skill is important with AI and before AI, but now it’s making it even more critical.”

That idea of “tribal knowledge” inside an organization or team to carry the qualities needed to thrive in the AI era was discussed in a previous episode of The Spiro Circle. AI may have access to an organization's information, but it doesn't automatically understand which pieces of that information matter, or spot what an experienced human employee would notice that isn't written down.

This reframes the debate about AI and employment and the fear that it will “take our jobs”. Currently, it appears that there will be a big shift in which part of a job it takes, with a recent IIA/Zvriran study on Startup Nation suggesting that while AI isn’t the primary reason companies are reducing their headcounts, the technology is cited by 10% of companies as the cause of hiring pauses - a threefold increase from six months ago.

In Glilot’s case, Elliot absorbs the data-gathering, the scheduling, the pattern-matching across thousands of founder meetings. What it leaves behind is soft skills, such as the ability to sit across a table from someone who has never built a company before, and decide whether to bet on them.

“The emotional part, the charisma, that’s especially important if you’re a very early-stage investor,” Kleinstein concluded. “That’s much more important than any data I can crunch.”

[Watch a 5-minute preview: AI can do the diligence. But can it pick the founder?]

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The week Gal Ordo joined Amazon Web Services as the Product Leader for AWS Security Hub, he did something his colleagues thought was unnecessary. Instead of using the internal templates that AWS provided to get the product up and running, he insisted on installing it from scratch the way a customer would - no shortcuts or help from the team that built it.

But then he said it took him four to five days.

“It was so hard for me to install,” said the co-founder and CPO of Native Security. “And I am within AWS! I’m the product leader for that. What does it mean for a customer going in the first time trying to use that? At best, they give up; at worst, they misconfigure it, and then they don’t have active security coverage.”

That initial moment planted the first seed. But the second came a month later, when Ordo attended his first Executive Briefing Center session on behalf of Amazon. There, a room of executives from Fortune 100 and Fortune 50 companies had one message for the young product leader sitting across from them: “Why are you showing us the problem after it happens? Why can’t we just prevent it?”

“I remember them telling me, ‘Why do you even allow me to get to that place? Why don’t you just give me the knob to say this can never happen in the first place?’” Ordo recalled.

It was those two experiences, operating a product too complex for its own builders to operate, and a customer too exhausted to keep reacting, that became the founding logic of Native Security. The Tel Aviv-based cloud security startup emerged from stealth in March 2026 with an official $42 million in funding (he says they have already secured more, up to $55 million), and a collection of Fortune 100 customers already running its platform in production.

According to industry research, 80% of cloud breaches stem from misconfigurations — resources left exposed, permissions set too wide, settings that drifted after an engineer’s late-night change. Among companies that use multiple cloud providers, only 33% have a unified security strategy across them. Ordo’s argument to me is that the tools to close that gap have always existed inside AWS, Azure, Google Cloud, and Oracle - but enterprises cannot operationalize them at scale.

Native’s answer is what Ordo calls a control plane, a platform that lets security leaders specify an outcome in plain language, such as: “My sensitive data should never be exposed to the internet.” It then translates it into enforceable technical controls across all four major cloud providers simultaneously, using those providers’ own native capabilities rather than adding another external layer.

Before any policy goes live, the platform simulates its impact by surfacing which services might break, or which cross-cloud dependencies might be disrupted, so security teams can act without fear of taking down production.

“The building blocks are there, they’re strong, they’re powerful,” Ordo said. “But they’re hard for customers to use.”

Ordo co-founded the company with Amit Megiddo, CEO, who led Amazon GuardDuty, and Eyal Faingold, CTO, who served as VP of Cloud Security Products at Check Point. Between them, the three founders have shipped security products used by tens of thousands of enterprise customers globally.

The initial $31 million Series A was led by Ballistic Ventures, whose roster includes Phil Venables, former CISO of Google Cloud. He joined the round and, later, the board, even calling Native’s approach “the next big evolution in cloud security.” The company currently employs around 50 people across Tel Aviv and the United States, drawing talent from IDF cyber units, Palo Alto Networks, Wiz, and CyberArk, with a target of 90 by the end of 2026.

The founding question was whether the knowledge they accumulated inside those organizations could be turned into something different. Notably, knowledge of where the tools broke down, where customers gave up, and where the cycle of detect-and-react became self-perpetuating.

“There is a reason this hasn’t been done before,” he concluded. “It’s incredibly difficult to achieve. The technical problems we’re solving are very hard.”

[5-MINS PREVIEW: The founding story of Native Security]

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Most VCs will tell you they invest in people. Push them further, and you’ll hear the same formula of exceptional team, large market, and right timing. It is recited so often it has become meaningless.

But Yuval Ariav, Founder and Managing Partner of Symbol, doesn’t give me that answer. Ask him what he looks for in a founder, and he’ll acknowledge that integrity and grit matter, but then he sets that all aside.

“If I had to put one overarching theme for us, it’s depth,” he told me. “We like to see that founders went to the validation threshold the capital market requires — and then way beyond it. Because what that tells us is that they are really interested in the problem, that they really understand it.”

Much of the theme of today’s conversation is about depth, and how to avoid “non-deep” thinking (I try to avoid the term “shallow”). For Ariav, the ability to go deep is the willingness to go so far into a problem that you exit the comfortable zone of apparent mastery and enter the uncomfortable zone of knowing how much you don’t know. “We like to see people whose level of expertise forces them to say, on some things, ‘we don’t know.’ Because that’s how you really know they know their stuff.”

Symbol is a $50 million pre-seed and seed fund Ariav co-manages with Racheli Kogan, and bets on founders working outside the mainstream of Israeli venture, in sectors the local capital community has traditionally dismissed. We spoke soon after Business Insider named Symbol to its 2026 Seed 100, the first time an Israeli fund has appeared on a list that includes Sam Altman, Accel, and Greylock.

The ranking’s stated criteria, which highlighted those who identify technologies before they become mainstream categories, are basically Symbol’s entire thesis.

The problem is that depth is vanishing

There’s a paradox at the center of Ariav’s argument: That the quality he bets on is becoming scarcer precisely as building companies gets easier. Because of AI, he notes, “building products has never been easier, faster, cheaper.” When there are more founders, lower barriers to entry, and more buzz, the very environment that Symbol is making a contrarian bet on is becoming full of less intellectual effort.

“The capacity for depth… it’s not just that you understand something deeply,” he said. “It’s that you are fine with sitting on your ass at home and spending six hours diving into god-awful McKinsey super boring reports to understand some fundamental truth. That is a skill set that is rapidly fading from the world.”

Research found that average sustained attention on a digital screen dropped from 150 seconds in 2004 to 47 seconds by 2024. Ariav, who teaches a course at Columbia University on data, AI, and society, watches this in real time. “Our collective attention span is going way down,” he said. “At a time when the world is more complex than ever.”

Contrarianism isn’t the answer

Here is where Ariav diverges from the standard VC contrarian pitch. Being reflexively contrary, he argues, is just as lazy as following the consensus.

“Being reflexively contrarian is also easy. You look at Twitter [X], and you just add ‘no’ in the beginning of whatever somebody says.” What Symbol looks for is different: founders who have gone deep enough to discover something the market hasn’t seen. “When you meet the best founders, at some point they will say something to the effect of: we’ve observed something the market doesn’t understand. At that point, they shine a spotlight on a hidden truth.”

For Symbol, it is about finding the pre-consensus thinking across a world that is no longer operating in the very depths that depend on new discovery. And with a world that changes as AI becomes more embedded in our lives, the ability to think, explore, and innovate is becoming a commodity in and of itself.

[Watch a preview: The "Depth" Problem: Why great tech founders are getting rarer]

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In cybersecurity, hesitation can be the most expensive decision a company makes. Shahaf Galili knows this not as a management theory, but as a lived operational reality forged across 22 years running offensive cyber units inside the Israeli military.

“You always need to make decisions when you don’t have all the information,” says Galili, co-founder and CEO of Mars Security, a Tel Aviv-based threat detection startup that raised $9 million in 2025. “The most dangerous thing to do — if you’re investigating a breach, if you’re conducting an offensive operation, if you’re trying to decide which product line to invest in — is to wait. Targets are moving and evolving. There’s a lot of chaos and multiple unknowns.”

It is a philosophy shaped by his real-world experience in the Israel Defense Forces, confronting actual life-or-death consequences. Galili left the IDF at 39, relatively later than most who leave after their mandatory three-year commitment, which he considers an advantage. The extra years gave him something that fast-track civilian careers rarely produce: a visceral comfort with operating under conditions that would paralyze most executives.

“The more chaos that you live through,” he said, “the better you will thrive in chaos.”

That thesis now underlies how Galili runs his founding team and how he thinks organizations should respond to a security breach in progress. His core conviction is that an imperfect action consistently outperforms a perfect decision arrived at too late - or one not performed at all. “I believe that an action, even if it’s the wrong one, is always better than not acting,” he explained. “An action will help you understand reality. You need to act… and then have the flexibility to understand that you made a mistake and change.”

I pointed out that there is something almost Shakespearean in how he thinks about cybersecurity. Hamlet, history’s most famous illustration of the cost of indecision, understood perfectly what needed to be done but died precisely because he couldn’t bring himself to do it. The play is a 400-year-old case study in strategic paralysis, and one that Galili would recognize immediately as a security failure as much as a human one.

History, it turns out, doesn’t repeat itself - but we all know it can rhyme. Delay was Hamlet’s ‘fatal flaw’. In cybersecurity, it remains one of the most common that can still cost enterprises their data.

This is not merely philosophical for Galili. The detection gap that Mars Security is built to close between the moment an attacker enters an organization, and the moment the organization realizes it is partly a technology problem and partly a mindset one. Security teams have been conditioned to gather more data before acting. Attackers, meanwhile, are moving across identities, cloud environments, SaaS platforms, and corporate networks in hours, not days.

“You need to be good all the time,” Galili said. “The attacker has one advantage: he has the initiative. If you take this from him and start being proactive, looking all the time at how they’re evolving, they don’t have a chance.”

The best piece of advice he ever received from a commanding officer? He doesn’t hesitate: “Love the chaos.”

The ability to embrace chaos in 2026 is as applicable to building a startup as it was to running operations in the years before - even if contexts and technologies evolve. And the leaders who thrive are never the ones who waited for more certainty before moving. They’re the ones who always kept moving.

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While I was recording an episode with Toni Samson, co-founder and CEO of Arte Security, she told me it was important for companies and CISOs to “find your Mona Lisas.” It made me remember how a few thousand kilometers away, the actual home of the actual Mona Lisa had learned that exact lesson the hard way.

Last October, thieves walked out of the Louvre with crown jewels worth more than $100 million. French investigators later found that only one of the two cameras covering the break-in point was even working, and staff didn’t have enough screens to watch the footage that did exist. The whole operation lasted minutes.

Imagine that: The Louvre, home to the most famous painting on earth, couldn’t tell you in real time what was happening to the jewels twenty feet away. It didn’t know where its own “Mona Lisa” was, so to speak.

And a few days ago its gallery finally reopened - this time, without the stolen jewels.

That’s the trap Toni was warning me about, except she wasn’t talking about paintings. Her metaphor was directed at CISOs who need to know the most important assets in their enterprise, and make sure those are more protected than just applying blanket protection over everything. “Find your Mona Lisas,” she said. “This is the most important. You will not be able to close everything. It’s too much. It will never be fast enough.”

The value of each asset varies by company. A shoe manufacturer’s factory floor matters more than its HR files. A bank’s Mona Lisa is the data itself, sitting in very specific places. “The question now is: How can I protect my most critical things? [Because] not everything is the Mona Lisa,” she said. “Not everything needs to be protected the same.”

This is where Arte’s own work gets specific. The company helps enterprises identify what parts of their data require more attention (and protection) than others. It then specializes and tailor-makes a solution that helps them protect their Mona Lisas from theft or hacking. The company was founded with co-founder and CTO Asaf Ohayon at the end of 2025, and Toni herself comes from a background in the Israeli Ministry of Defense as Director of Critical Infrastructure & Data Center Cybersecurity.

Another example may be a hyperscale AI data center, where its Mona Lisa isn’t necessarily a database. It might be the chiller controller. Bad actors wouldn’t even need to breach a firewall to take an AI cluster offline. All they would need to do is make the room too hot to run.

This sounds obvious until you actually try to do it. Security researchers estimate that roughly a third of large businesses can see less than three-quarters of their own assets at any given time: Think of it as the digital equivalent of a museum that isn’t sure how many rooms it has, let alone what’s in them.

I asked her to help me quantify it: how do you actually know which door is the one with the painting behind it? To distinguish between the Mona Lisas and what I called “The James Spiro Original Scribble”. Her answer was to identify what you’d protect first if you could only protect one thing, and build outward from there. “Make sure your Mona Lisa is protected,” she said, “and put it as number one priority.”

Every laptop or every forgotten API endpoint is indeed an attack surface or entry point. And for a long time, the instinct in cybersecurity has always been to try to lock all of them at once. But Toni’s point is that this instinct is now outdated, because when attackers can use AI to move at machine speed, treating every asset as equally precious means treating none of them as precious enough.

The Louvre is now spending close to a billion euros to build the actual Mona Lisa her own dedicated room. Most businesses won’t get that budget. CISOs will have to actually know where their Mona Lisa hangs before someone else finds out.

[Watch a preview: “Not everything is the Mona Lisa” — Cybersecurity priorities, explained]

Israel’s cyber numbers from 2025 were staggering.

We all know the big ones: Google acquired Wiz for $32 billion. Palo Alto Networks spent $25 billion to absorb CyberArk. ServiceNow bought Armis for $7.8 billion. When the final tally was complete, strategic mergers and acquisitions in the cybersecurity sector had reached $81 billion - more than four times the volume of the prior year, according to data compiled by Notable Capital and Morgan Stanley.

For Oren Yunger, Managing Partner at Notable Capital and one of the architects of the firm’s annual Rising in Cyber report, the significance of those deals runs deeper than just their valuations. “The ceiling has kind of been shattered,” he told me.

“You can build businesses that are just massive. You can do things that we, in the past, thought were unimaginable in cybersecurity,” he added. “Companies should get acquired between $200-400 million dollars — that’s the best you can do. Now we’re seeing companies that really are paving the way to the next set of companies to go and build bigger and stronger.”

For much of the last decade, cybersecurity exits were measured in hundreds of millions, not the tens of billions we see today. The Wiz deal alone, which became the largest high-tech exit and business deal in Israel's history, poses a new question to a new generation of founders: If they could become a $32 billion business, what is possible for us?

The M&A wave of 2025 coincided with a shift in how enterprises think about the AI era and the risks that come with it. In 2024 and early 2025, the defining question for enterprises deploying AI was whether they could build agents capable of autonomous action. Yunger now argues that that question has largely been answered and a new one has emerged.

“The big question that we’re seeing is: can you put it in production, can you scale that agent, can you trust its operations?” he said. “Security is just a huge part of this question that needs to be answered at enterprise scale.”

The Rising in Cyber 2026 report, which surveyed nearly 150 chief information security officers from the world’s largest companies, puts precise numbers on the gap between deployment and protection. Seventy-one percent of respondents said their organisations already have AI agents running in production environments. But only 11% described their tooling to secure those agents as mature. That gap is where Yunger sees the next wave of investment flowing, and where the next generation of large cybersecurity companies will be built.

The broader cybersecurity sector is projected to reach $255 billion by 2029, up from $153 billion in 2025, according to IDC estimates. Early-stage investment is accelerating: Series B rounds grew 74% to $3.3 billion in 2025, with average deal sizes jumping 75% to $49 million. In a year when most software categories saw venture funding decline, cybersecurity’s earliest rounds were the only segment to grow year over year.

The momentum has continued into 2026. CrowdStrike acquired SGNL, Palo Alto Networks purchased Koi, and Sophos acquired Arco Cyber — all in the first half of the year. The platforms that spent 2025 making transformational acquisitions are now targeting the AI-native capabilities they need to stay competitive as the threat landscape continues to evolve.

Microsoft, which dominates five of the largest cybersecurity verticals, is adding capabilities faster than at any point in its history, with CrowdStrike and Palo Alto doing the same. But their acceleration has not crowded out newer startups. If anything, it has raised the stakes for founders who can identify the problems that the large platforms have not yet solved.

“Security companies today are answering those questions,” Yunger said, “and the ones to follow will eventually accompany every single technology shift that is happening in the market and will continue to do so for as much as I can think of.”

Yunger claims the thesis is confirmed by Satya Nadella, Microsoft’s chief executive, who he said has described engineering as converging into four enduring disciplines. One of them is security engineering: a category he considers permanent regardless of how AI reshapes the rest of the technology industry. “Doesn’t matter how AI is affecting our markets, what jobs AI potentially will threaten and maybe change… Security is here to stay.”

For founders building in the space today, that is both a reassurance and a challenge. The ceiling “has been shattered” and the market is expanding faster than we all predicted. Large companies are acquiring quickly, and the venture dollars are flowing earlier.

What founders may be asking themselves now is if they can also build something the platforms may have no choice but to pay to absorb. And Wiz has shown them that the answer may be worth $32 billion.

[Watch a preview: The Cybersecurity Ceiling Just Got Shattered]

Israel isn't fighting one information war. It's fighting three. At least, that’s the takeaway I had when I read Digital Warrior: Inside Israel’s Battle for the Narrative After October 7 by Rachel Lester this week.

Rachel served in the International Branch of the IDF Spokesperson's Unit, first on active duty, then in reserves from October 8th, 2023, editing and shaping video content for accounts with over 10 million followers across platforms. You probably saw her videos from the official IDF X account, or from her personal Instagram, @Rachel.In.Reserves

Thinking back to the early days following the October 7 massacre, what struck me most was the impossible communications challenge the IDF faced. Her job, and the job of the army, was to explain multiple things to the world at once.

“I think that Israel faces social media challenges that no other army and no other country in the world face,” she told me. “I think that we have the unique challenge of trying to reassure our civilians that we are safe and that the army is in control, while at the same time conveying to the world these are our enemies, this is what our enemies are doing right now… this is what our enemies just did: committed the largest attack on Israel in our history. And if we don’t fight them, then they’re gonna do it again and again, as they’ve said.”

One country, three completely different messages

One of the central arguments in Digital Warrior is that the IDF isn't running one narrative. It’s running three, simultaneously, to three audiences - and the messages don’t just differ in tone, they actively contradict each other.

* To the local, Hebrew-speaking audience - the message is reassurance: we are strong, we’re handling it, you don’t need to worry.

* To the Arabic- and Farsi-speaking world - the message is closer to a warning: we are strong, we’re watching you, and your own leaders are the ones corrupting you.

* And to the international, English-speaking audience, the posture flips entirely: we are at risk, we are under attack — because that’s the only framing that earns Israel the right to defend itself in the eyes of the world.

Project strength to one audience and vulnerability to another, at the same time, and you’d think it’d collapse under its own weight. Rachel told me it basically does, sometimes. The three departments work almost entirely independently of each other - there’s no room for someone to coordinate the tone across all three. “Sometimes it works, and sometimes it doesn’t,” she said.

The moment she paused

I considered the paradox Israel found itself in, and thought about why it didn’t apply to Hamas’ messaging strategy. So I put it to her directly: Didn’t Hamas actually pull off the version of this that Israel is still struggling with? A fear campaign aimed at the region, running alongside a sympathy campaign aimed at the West without the contradiction ever really catching up to them?

“That’s an interesting point I hadn’t considered before,” she said. Western outlets, she pointed out, never really broadcast the moments when Hamas spokespeople promised “to do October 7th again and again.” That footage exists, as Rachel saw firsthand, but it just doesn’t travel the way photos of dead children (or P.O.D.C., a term she coined for the book) do.

As the war dragged on, Hamas’ messaging was contained inside its Arabic-language threats, but its English-language grief campaign spread across the world. Somehow, the two rarely collided in the same feed, in front of the same audience, at the same time. This was not true for Israel, whose messaging sometimes came out slowly or inconsistently - and whose critics were quick to highlight these contradictions.

This is more than a media-strategy story

It would be easy to file this under another “PR problem” Israel has to overcome, and move on. But I don’t think that’s what it is. Our conversation kept circling back to how, in a war where legitimacy determines whether you’re even allowed to keep fighting, the coherence of your story and its narrative matters as much as the truth of it.

That challenge is only becoming harder now that AI makes it easier to manipulate and dismiss authentic content. During our conversation, we discussed the “liar's dividend”, a term coined by legal scholars Bobby Chesney and Danielle Citron for exactly this phenomenon: real evidence getting waved away simply because fake evidence is now possible.

She mentioned an instance in 2023 when journalists doubted the validity of footage released by the IDF. And earlier this year, genuine footage of Netanyahu was mistaken online for an AI fabrication. So the tech doesn't even need to be actively used against Israel. Its existence alone is often enough to doubt or undermine its digital efforts.

That’s the tension I’d encourage you to sit with if you pick up Digital Warrior: not “is Israel’s PR bad,” which is the question everyone already has an opinion on, but “can any democracy actually hold three contradictory messages together in an age when information is everywhere?”

Digital Warrior is out now. You can follow Rachel on Instagram here.

For transparency: I have no financial relationship with this book or its sale. This recommendation is unpaid.

[Preview: We discuss “How the IDF Talks to Israelis, Enemies, and the World — All at Once”]

On July 8, the head of the National Highway Traffic Safety Administration sent a letter to the autonomous vehicle industry saying that AV developers had shown a “clear pattern” of driverless cars blocking ambulances and fire trucks, ignoring flares and flashing lights, and in some cases driving directly into active emergency scenes.

While not technically naming Waymo, it was undeniably a focal player in the robotaxi reckoning - saying there was “a functional insufficiency” among automated vehicle developers regarding “a pattern of interference with first responders”.

At the same time, a different conversation has been unfolding inside the AI industry. Some of its leading figures have begun looking beyond engineering for answers. Anthropic recently launched its Faith & AI Covenant Roundtable to discuss how best to infuse morality and ethics into AI, while OpenAI's Head of Strategic Futures, Dean Ball, sparked debate after saying he had begun studying the Talmud to better understand AI policy.

Dr. Tal Cohen, co-founder of Drive TLV and managing partner of Next Gear Ventures, joined me to discuss these issues. In an interview recorded just after the NHTSA letter, Cohen used Waymo as the clearest example of what he calls “The Habitat”: the missing institutional layer of trust, permissioning, and accountability that must exist around an AI system before it’s allowed to act with consequential impact in the world.

“Two, three years ago, I was irrelevant, because there was no capability to talk like that,” Cohen said. But AI ability is expanding, and it is clearly starting to outpace the governance structure meant to contain it. “The capability is expanding,” he added, pointing to Waymo’s rapid deployment. “Suddenly, you have a gap between what the capability can provide and what we are lagging as a society.”

Cohen’s main argument is that the industry has spent its energy on the wrong bottleneck. Public debate about AI has focused overwhelmingly on physical infrastructure constraints related to chips, energy, and data centers, or on the capabilities of the models themselves. But he told me the actual constraint is a broader and less visible vacuum around the governance that authorizes an autonomous system to act, who reviews what it did, and who has the standing to revoke its authority when it gets something wrong.

“So then the question is: who’s gonna own the habitat that’s gonna authorize Waymo to go into crime scenes or not?” He argues society will hand over billions of consequential driving decisions before governments build the institutional framework capable of supervising them.

In his framing, regulators, municipal transportation departments, and NHTSA itself are unlikely to build that infrastructure fast enough on their own. He expects, and believes the moment demands, some hybrid of public and private coordination to define a constitution of sorts for autonomous systems. “We’re gonna live in the centuries or decades of habitat construction,” he said. “People really don’t get it yet.”

A manuscript he's been circulating, The Case for Habitat, argues this point exactly: That without a system or code in place, organizations face an uncomfortable choice. “You either put somebody in the basement, don’t let it do what it can do… or let it destroy your business,” he concluded.

In Cohen's words, the capability is “shiny,” but the Habitat is “boring.” Yet history suggests that the boring is often what determines which transformative technologies succeed.

[5-Mins Preview: Can Judaism solve AI alignment?]

Every day, billions of dollars move through the global payments system as people buy things online. And every day, a portion of those transactions gets reversed. Not through fraud in the traditional sense, but through disputes: a cardholder tells their bank they don’t recognize a charge, or that a service wasn’t as described, and the money often comes back to them almost immediately.

Multiplied across the entire e-commerce economy, that adds up to an estimated $125 billion a year. It’s a leak most consumers never think about, and most of fintech rarely discusses. In the AI era, however, as users continue to delegate AI agents to conduct financial transactions online, it is becoming the latest hurdle global payment companies need to overcome.

Ofir Tahor, co-founder and CEO of Justt, has spent the past six years building a company around that gap. His explanation of the problem starts with its age. “This is a mechanism created about 60, 70 years ago,” Tahor said, describing how card networks originally designed chargebacks to protect cardholders in a world of physical stores and mail-order catalogs. A customer could go straight to their bank rather than the merchant, flag a transaction as unrecognized, and get reimbursed while the burden of proof shifted entirely onto the business to explain why it should keep the money.

Tahor explained that perhaps the most noteworthy aspect of the industry is how almost nothing else in e-commerce still works this way. “If you take companies like Shopify, which did a revolution in the e-commerce world, and Stripe, which did a revolution in the payment processor world, chargebacks stayed behind,” he said. Checkout, fulfillment, customer support, and fraud screening have all moved to real-time, largely automated systems.

But dispute resolution remains a paperwork exercise: a merchant compiles documentation, sends it to their payment processor, which forwards it to the cardholder’s issuing bank, like Chase, Citibank, or Wells Fargo, where a human being reviews it and makes a call. “It’s still very manual-operated,” Tahor said. “It’s somehow stayed behind in comparison to many other processes within e-commerce.”

The consequence is a phenomenon known as ‘friendly fraud’: cases where a legitimate transaction gets disputed anyway, whether through genuine confusion or deliberate manipulation of a system stacked in the cardholder’s favor. It’s now the second most common type of fraud globally, and as the ability for agents to buy things themselves only speeds up, Tahor doesn’t expect it to slow down. “It’s easy to report a chargeback, and it’s becoming easier,” he said.

The data backs this up. Mastercard’s 2025 State of Chargebacks report, based on research from Datos Insights, forecasts global chargeback volume growing 24% from 2025 to 2028, reaching 324 million transactions annually. It’s a trajectory that was already straining a decades-old system before AI-driven commerce entered the picture at all.

The argument that clamping down on friendly fraud will be a net positive for the ecosystem and, in turn, the consumer, is the origin story behind Justt’s name. “It’s from the word ‘justice’, in order to create balance in the ecosystem,” Tahor said. Even though it may sound like the company is out to protect Big Business, it is an attempt to build a system that helps merchants keep money they’re owed while still returning money to cardholders when they’re right. In that world, everyone wins because consumers aren’t left paying those costs.

Justt was founded in 2020 and has since raised $100 million. It works with more than 250 global enterprise merchants and over 80,000 small businesses, and was named to Forbes’ 2026 Fintech 50 list this spring, the first chargeback-focused company to make the list. It shows that chargeback management, long treated as a back-office cost center, is being recognized as core financial infrastructure in its own right.

Learn about Ofir Tahor, chargebacks, fraud, and building Justt in the preview here:

The Spiro Circle is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Days before Tal Shoham announced that his AI monetization startup Velocity had closed a $27 million Seed round, an independent tracker put a number on something the industry had only been speculating about: ChatGPT ads were showing up in roughly 26.5% of all replies globally, and 49% of replies in the United States.

For Shoham, that timing is the proof of concept for his newest company and a sign of the latest change in the AI era. “ChatGPT, of course, has added ads now, which is amazing for us and for the industry, because it’s like a north star that everybody looks at,” Shoham told me.

He co-founded Velocity alongside Amir Shaked and Nimrod Zuta, all three of whom are former senior executives at ironSource and Unity. The company is building what it calls a growth infrastructure layer for AI-native applications: an ad network, a mediation and auction system, and a “conversation intelligence” layer that turns chatbot dialogue into structured, privacy-safe intent signals.

Basically, it’s helping bring adverts to your favourite AI agent.

The round was led by NFX and Red Dot Capital Partners, with participation from Stardom Ventures, Corner Ventures, and Transcend, alongside a roster of gaming and ad-tech angels, including former ironSource co-founder Omer Kaplan.

The pitch is a straight transplant of the problem his team spent a decade solving in mobile gaming, with one crucial difference. “Ninety-five percent of the users in gaming will never pay a dime,” he said. “You really want to try to find a way of monetizing those users.” In gaming, a free user costs almost nothing. But in AI, that math is inverted: “Every free user that you have on your AI platform is actually costing you a lot of money on inference, tokens, GPUs, and so on.”

That inversion is the reason that AI companies have defaulted to hard limits (two or three free prompts a day) rather than the generous free tiers that built mobile gaming and social media into mass-market platforms. He bets that an advertising layer can fund broader free access without those companies bleeding cash, and that doing so improves retention rather than damaging it. “We have more than 12 design partners live already,” he said. “This doesn’t harm retention, it doesn’t harm engagement, it doesn’t harm conversion to monetization.”

But the timing that makes Velocity’s raise look prescient also drops it into the middle of an unresolved trust problem - one that OpenAI itself has been actively renegotiating in real time. ChatGPT’s original ad policy excluded placement near politics, health, and mental health topics, with a standing ban on dating, alcohol, drugs, and gambling. But a June 2026 update already suggested that current advertising categories “may expand over time” to include medical, legal, and financial advice contexts eventually.

In other words, the rules of the road are being written after the road has already opened to traffic. It’s a pattern that anyone who lived through Europe’s post-hoc arrival at GDPR will recognize as headache-inducing.

I pushed Shoham directly on where that leaves the user. Chat conversations are not basic search queries: they’re often confessional, emotional, and far more revealing than anything a keyword ever captured. “There’s a lot more emotion behind what people are giving these algorithms,” I said. “It’s not just tapping into data points... It’s tapping into a real human feeling.”

Shoham’s answer leaned on the compliance muscle memory his team built at ironSource, navigating GDPR and a patchwork of state and platform-level privacy rules for years. “We don’t take any of the private information from the user,” he said. “If you type in something on health, something sensitive, your social security number, or whatever it is, we’re not saving that, we’re not taking that, and we’re not integrating that into the model when we’re trying to find the right ad to show you. We have an abstraction layer that actually abstracts all the sensitive information.”

So, whereas search reads your keywords, social media reads your behavior, AI just reads you. Velocity’s bet is that the same compliance discipline that got ironSource through GDPR can keep that power in check… but with ChatGPT's ad rollout already outrunning its own written rules, that's a promise the whole industry is now testing in public.

Preview: The Next Google Ads? Inside Velocity’s $27M Bet on AI “Intent”

Manny Marotta has a theory about why America’s 250th birthday felt subdued. It isn’t purely politics, though politics is tangled up in it. It’s the structure. There are simply too many feeds now, and not enough shared ones. And the ones that do break through to the masses get read as political, whether they mean to be or not.

I sat down this weekend with Manny for the second time. He’s the creator and curator of the Live History Project, which takes a couple of accounts on X and posts in real time what’s happening in that moment in history.

There’s:25 years ago - @25YearsAgoLive50 years ago - @50YearsAgoLive100 years ago - @100YearsAgoLiveand 250 years ago - @250YearsAgoLive

Right now, that means we’re living through 2001, 1976, 1926, and 1776 simultaneously. He pointed me back to America’s bicentennial in 1976, which he says was one of the only major stories of that year, competing for attention with little more than an Olympic Games.

This year, Independence Day landed alongside a World Cup on American soil, an ongoing Iran conflict, a White House renovation project, and an MMA match. It also took place with a media landscape noticeably divided along party lines and contrasting levels of patriotism between political ideologies.

“Now we have so many different news cycles, so many different news sources that people are following,” he told me. “It’s just oversaturation.” His 250-years-ago account picked up roughly 300,000 followers and 20 million views in the days around the holiday, almost entirely because a political audience decided it mattered.

That’s where the story gets complicated. Manny insists the account isn’t doing anything ideological - he just posts digitized letters and meeting minutes from the Library of Congress that are available to everyone, without commentary. And yet that neutrality is precisely what got it adopted as, he describes, a patriotic rallying point by people ‘on the right’.

“A neutral or positive view of not just the American Revolution but American history in general has become, in recent years, sort of right-wing coded,” he explained. “So if you are even reporting in an academic sense what happened, a lot of people do tend to see that as right-wing.”

Meanwhile, news outlets covering the holiday split along familiar lines: CNN described the mood as shaping up to be “a big blah.” The New York Times ran an op-ed blaming the Trump administration for deflating the day, then was forced to revise its own headline. The Washington Post called it “an unfortunate metaphor on national divisions.”

Disney, by contrast, ran wall-to-wall patriotic programming, and outlets like The Free Press leaned into celebratory content.

But Manny didn’t spare the current administration either, telling me the patriotic messaging he’d seen recently during a trip to Washington, DC, centered more on a single political figure than the anniversary itself: “The only America 250 content that I saw were giant banners with Donald Trump’s face on them... nothing about the anniversary itself, more about the person who happens to be president.”

His hope, he said, is “to create maybe a simulation of the monoculture that we had in the past,” which is academically sourced, uncaptioned, and a return to the apolitical. So he is trying to hold a neutral center by republishing old letters, in a country where an audience conditioned by fragmentation has decided that the center no longer exists.

But a Jefferson draft, posted without a caption, still lands as a statement to somebody.

This is my second conversation with Manny Marotta. Watch the first, from February, about the Live History Project’s 2001 account, here.

Jira tickets used to sit open for years. A medium-severity vulnerability, flagged by a routine scan, could be assigned to an engineer who had bigger fires to fight. It had largely been that way for years: patch the criticals, manage the highs, let the mediums age. When it came to CVEs (Common Vulnerabilities and Exposures), a publicly available list of known cybersecurity flaws in software and hardware, nobody was going to weaponize one rated 5.4.

But in today’s world, that’s no longer true.

“In 2020, [if] there was a CVE reported and a security hole, it would take more than a year until there was a public exploit,” said Shimon Tolts, CEO and co-founder of Tel Aviv-based cloud security startup Copperhelm. “Nowadays, with Claude and OpenAI and other players, the time has shrunk from one year to one day. So now you treat every CVE, every security issue that you have, as immediately exploitable.”

The data confirms what Tolts describes. The mean time between a vulnerability being discovered and its exploitation has dropped from nearly a year in 2021 to just over a day in 2026, with industry projections suggesting the window will shrink to one hour by 2027. Rapid7’s 2026 Global Threat Landscape Report found that what once unfolded over weeks now materializes in days (and in some cases, minutes), with the median time between vulnerability publication and inclusion on CISA’s Known Exploited Vulnerabilities catalog falling from 8.5 days to five.

The implications invalidate an entire category of enterprise risk management.

For decades, security teams built their workflows around severity scores. The National Vulnerability Database, operated by the National Institute of Standards and Technology (NIST), classified every disclosed flaw as ‘critical’, ‘high’, ‘medium', or ‘low’ - and organizations built their response hierarchies accordingly. Fix the criticals immediately, schedule the highs, and then defer the rest.

That model is now under institutional strain: CVE submissions surged 263% between 2020 and 2025, and starting April 15, 2026, NIST announced it would only prioritize enrichment for a narrow subset of vulnerabilities, such as those already on CISA’s exploited list, those affecting federal systems, or those covered by Executive Order 14028.

This would leave the majority of newly disclosed flaws without severity scores. “You’ll no longer be able to use the old risk management methodology of saying ‘I’m only going to fix criticals’,” Tolts explained. “Because you’re not going to have a severity anymore.”

The shift has a compounding effect. AI models are not only accelerating exploitation timelines, but they are also discovering vulnerabilities at a rate that human analysts cannot process. NIST enriched nearly 42,000 CVEs in 2025, 45% more than any prior year, and forecasts from the Forum of Incident Response and Security Teams projected a record 50,000 additional CVEs to be reported in 2026 (these figures do not yet account for the accelerating contribution of AI-powered vulnerability discovery tools like Claude Mythos and GPT-5.4-Cyber).

Every day, the cyber world is facing more vulnerabilities, faster exploitation, and fewer severity scores to guide triage. But security teams are still largely operating through manual workflows designed for a different era.

Copperhelm’s answer is autonomous investigation and remediation, already backed by a $7 million seed round led by TLV Partners and deployed in Fortune 500 environments. The platform uses a proprietary “Context Lake” to structure cloud data across environments, enabling AI agents to continuously monitor infrastructure, investigate threats, and execute real-time remediation without manual handoffs.

Tolts describes the practical effect in terms his customers already understand: one client arrived with 10 million open vulnerabilities and two home-made severity categories above “critical” — labels they had invented themselves because the official scale had run out of runway.

“Your window of response has shrunk, and you need to autonomously take care of it,” Tolts said. “It’s no longer the case where you can just open a Jira ticket and wait for some engineer to fix it in one year or one month, because now you’re gonna get exploited very, very fast.”

In the early days of Teramount, investors kept asking CEO Hesham Taha the same question.

He had a platform that could connect chip to chip using light instead of electrons, considered a technical feat he and co-founder Avi Israel had spent years developing. But the problem, he recalled, was everything else.

“We thought it was a great idea, see how easy we can connect the light to the chip. Everyone will use that,” Taha said. “But it turns out to be exactly the opposite in the first few years after our inception.”

The problem for Taha and Israel was that for nearly a decade, Teramount was trying to solve a problem the semiconductor industry didn't know it would have. The market didn’t yet exist, nor did the supply chain. “The most critical point and the big barrier at the beginning of this journey was, ‘What is the product? What is the use case?’ This is what every investor kept asking us, and we failed to give a good answer.”

Years passed, and that question, once unanswerable, just got answered. In April, Molex announced the acquisition of Teramount for approximately $430 million, roughly 7-8 times the $58 million that the Jerusalem-based startup had raised across its lifetime.

The exit is a case study in what might be called ‘The Patience Trade’: bet on a technology before the world knows it needs it, endure years of uncertainty, and trust that the market eventually catches up. In Teramount’s case, it took two pivots, one global AI infrastructure boom, and a seed investor willing to see something others couldn’t: Lior Handelsman.

Today, Handelsman is a Managing Partner at Grove Ventures, and before that, was a co-founder of SolarEdge - so he himself is no stranger to building technologies into markets that don’t yet exist. When he first encountered Teramount, his instinct was to pass. “There was no market even when I met them at the beginning of 2021,” he said. “And I was pretty much willing to tell them, ‘Look, guys, very nice, but I can’t see the market’.”

Handelsman ended up reaching out to senior contacts at NVIDIA, Broadcom, Cisco, and Intel — companies that would eventually need exactly what Teramount was building. “When I told them, they said, ‘That’s a big problem. Connecting fiber to chip? That’s a big problem. We are all going to need that in four to five years’.”

Grove led the seed round in 2021, and the next few years compressed faster than anyone predicted. The 2022 generative AI explosion turbocharged demand for the kind of optical connectivity Teramount had spent years perfecting. Co-packaged optics — the integration of optical engines directly with compute chips to reduce power consumption and latency — moved from a niche conference topic to an urgent industry priority.

And so Teramount, having spent years building the ecosystem relationships and supply chain partnerships that most competitors hadn’t started, was suddenly indispensable.

Taha points to two moments that changed Teramount’s trajectory. The first was 2017, when co-packaged optics began to emerge as a defined technology category. The second was 2024, when AI infrastructure demand made optical connectivity not just desirable but necessary. “This was the major and significant pivot in our journey,” he said.

Strategic investors followed the technical validation. AMD, Samsung, and Hitachi all joined Teramount as the company’s direction became increasingly legible to the industry. Handelsman describes the combination of financial investors alongside strategic ones as the signal that a company has crossed a critical threshold: “That’s like a sweet spot. A financial investor is leading the round, saying that there is still upside, and strategic investors, who can all be customers.”

For Taha, the Molex acquisition was less a finish line than a pragmatic decision about speed. “We had a great technology, we have a great product, but we need to move fast to match the market speed,” he concluded. Molex, a proven interconnect manufacturer with global production capabilities, offered the industrial scale that the Jerusalem-based startup could not self-assemble quickly enough.

The patience trade paid off. The lesson it offers is about endurance, and about finding investors willing to hold the same long view as the founders they back.

The Spiro Circle is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Everyone is talking about a water crisis brought on by AI use. But think of this: the data centers powering the AI economy are not built from code. They require concrete, steel, cranes, and the coordination of hundreds of subcontractors across millions of square feet of new floor space.

And right now, the construction industry is struggling to keep up.

Capital expenditure from the 14 largest publicly owned data center operators globally is projected to approach $750 billion in 2026, up from under $450 billion the year prior. The Stargate Project alone, a multi-year, $500 billion plan to deliver up to 10 gigawatts of AI-ready power, was formed as a joint venture between OpenAI, SoftBank, Oracle, and MGXis and spans multiple U.S. states.

Meanwhile, the median cost of building a data center hit $445 per square foot this year, up 7.4% from 2025, with average costs skewed far higher by hyperscale projects. The pipeline is enormous, and yet the pressure on builders to deliver is greater still.

Erez Dror has seen this shift from both sides. A structural engineer and former construction superintendent who spent over a decade on job sites in Israel, he co-founded workforce intelligence platform, Genda, which last year was acquired by Buildots after a $5.5 million Seed round. He recently stepped into the new role of VP of General Contractors & Genda at Buildots, which to date has raised $166 million.

After the acquisition, the joint entity is now positioning itself as the operational backbone for exactly the kind of complex, fast-moving builds that the AI infrastructure boom demands.

“A product executive who worked on the biggest project Genda was on, a $600 million project, took them four years to build,” Dror told me. “He moved to build one of the biggest data centers in the U.S., which was $6 billion — 10x the scale — and they built it in three years. A year less, and 10x times the scale.”

The compression reflects a new standard being set by hyperscalers who come from a software-first culture and expect physical construction to behave accordingly. “A person who works for Google and is used to building software that doesn’t break expects to get a building that doesn’t break at the same quality,” he said. “They’re setting a new standard, which I believe will eventually trickle down to everything.”

The challenge is that construction remains one of the most fragmented, data-poor industries in the global economy. Unlike a tech organization, where a single executive decision can transform operations overnight, construction is built around individual projects with its own lead, subcontractors, or even its own tolerance for disruption. Change management, Dror argues, is “just a different beast.”

That fragmentation is precisely what Buildots is trying to solve. The platform ingests two data streams: weekly 360-degree camera footage from job sites and the project’s 3D building model, to use computer vision to identify what has been built versus what was planned.

Genda, meanwhile, tracks where workers are on-site in real time, anonymously, using an app-based system that Dror designed around behavioral incentives rather than hardware. Together, Buildots says the platforms offer visibility into both the work being completed and the labour required to complete it.

“We know the output, we know the input… we know what was built, and we know what efforts or how many resources were needed to get there,” Dror explained. “We’re the only solution in the world that can provide you with the full picture. Not even at scale — just to provide that.”

In April, Buildots formally launched a new product category, which it is calling “construction intelligence”. It frames itself as the operational platform for an industry that can no longer afford to rely on gut instinct and fragmented spreadsheets. And as data center construction starts reached $9.8 billion per month through April 2026 (300% more than levels seen a year ago), the timing for a platform that can turn chaotic job sites into predictable delivery machines has never been better.

“When you need to build a facility like a data center that is very detail-oriented, and you need to build it very fast, and every day of delay is millions, if not tens of millions, if not billions, in liquidated damages, you really need to make sure you finish on time and you know what the hell is going on in your project,” he added.

Watch a 5-minute preview of this conversation here:

Everyone is talking about the $90 billion M&A wave that hit the sector in 2025: Google’s $32 billion purchase of Wiz, Palo Alto Networks’ $25 billion buy of CyberArk. People love to talk about those, but almost nobody talks about how few companies can actually write those checks.

Except Ofer Wolf.

As Akamai’s SVP and General Manager of Enterprise Security, Wolf sits on the buy side today. But he got there as COO of Guardicore, the Israeli startup Akamai bought in 2021 for roughly $600 million. It makes his reading on the market less theoretical and more one from actual memory. “I can see the picture from the three sides: the entrepreneur side, the investment side, and the potential acquirer side,” he told me.

What he sees from all three is a market punishing founders who raise at prices the buyer pool can’t support. “There are [fewer] than five companies that can do constant acquisition of over a billion,” he said, calling the Wiz-type deals an exception, not the rule. “Most of the acquisitions in cybersecurity, which is a fragmented market, are limited to hundreds of millions of dollars, usually.”

That’s what he called “the poison pill”: raise too high, and you haven’t built a war chest, you’ve actually shrunk your buyer list to almost nobody. “Your valuation decision has set the future of the company to be a different future,” Wolf told me. “[It’s] probably the most strategic decision that is overlooked.” His advice isn’t to dream smaller, or only aim for the IPO - rather, it’s to prepare a few plans and act accordingly. “You need to have in the back of your mind another plan B, plan C… because eventually, most of the cybersecurity companies, the successful ones, were acquired by somebody.”

Akamai’s own Tel Aviv record reads like that discipline in practice. It completed four Israeli cybersecurity acquisitions in five years, most recently the roughly $205 million purchase of browser-security startup LayerX (expected to close later this year), comfortably inside Wolf’s “hundreds of millions” band and nowhere near the CyberArk or Wiz price tags.

Wolf describes the Israeli geography of the company’s acquisitions as serendipitous: “Two miles around our office, you’ll find a major part of the cybersecurity industry, from Palo Alto, Check Point, CrowdStrike, to small startups.” When Akamai went shopping for a workforce-security target, it checked six or seven companies across Israel, the US, and Europe, only to find the winner “sitting in the building right down the street, five minutes from our office.”

Akamai's ability to stay active on the acquisition front is helped by its strength elsewhere in the business. The company's stock recently surged after disclosing a $1.8 billion cloud deal with what it called a leading frontier-model provider, widely reported to be Anthropic. That gives Akamai the luxury of approaching acquisitions from a position of strength rather than necessity.

The same recalibration Wolf sees in acquisition markets is also showing up in Israel’s labor market. Wolf calls it “two headwinds”: AI-driven layoffs squeezing junior hires, and a shekel that’s strengthened over 20% in a year, making Israeli engineers pricier than they were twelve months ago.

The Israel Innovation Authority’s 2026 report backs him up, and something I previously wrote about in JNS: for the first time in a decade, Israeli high-tech R&D headcount actually fell by roughly 3,500 jobs. “The reduction in force is hitting the news,” Wolf said, “but the slow drift won’t make the news.”

He’s surprisingly upbeat about where this lands. In his mind, laid-off engineers will become founders of future great companies. And new hires get “a little bit more sensible” about pay. His own team is leaning into “AI-native junior guys” at the same dollar budget that bought fewer senior people a year ago.

So currently, valuations and salaries are both drifting back toward what the buyers are willing to pay. And for Akamai, that is an easy pill to swallow.

Watch us discuss this idea in a 5-minute preview: The "Poison Pill" That Kills Cybersecurity Startups

The robotaxi race has a winner’s podium that everyone can name. Waymo is expanding fast, with TechCrunch reporting that its fleet has now crossed 3,000 vehicles, completing over 500,000 trips per week across multiple U.S. cities. Tesla launched its robotaxi service in Austin. Chinese players like Baidu and WeRide are scaling aggressively at home, as well.

But Igal Raichelgauz, CEO and founder of Israeli autonomous driving company Autobrains, thinks the industry is looking at the wrong scoreboard entirely.

“The major market, the biggest opportunity today, is in the Western world for every car,” Raichelgauz told me. “We have today over 1.5 billion cars on the road. These are not addressed - not by Tesla, not by Waymo, and not by the Chinese players. And that’s where we see the biggest opportunity.”

Waymo’s overall fleet is impressive and certainly dwarfs Tesla's. Take the state of Texas, which, as of recent state DMV filings, showed that the Musk-owned company had just 42 autonomous vehicles authorized for driverless ride-hailing, compared to Waymo’s 577.

Meanwhile, Chinese players cannot realistically scale into Western markets for geopolitical reasons, leaving the competitive map with a conspicuous gap at its centre.

Autobrains is positioning itself directly in that gap, using agentic AI to split the driving task into thousands of specialized agents rather than training a single monolithic model. The Israeli company has raised over $140 million from investors that include BMW, Toyota Ventures, Magna, Continental, Temasek, and others, and claims to hold more than 300 patents related to AI and autonomous driving. It’s where Raichelgauz sees the company getting the best chance to join that winner’s podium.

The logic is as follows: Waymo’s approach is built on expensive sensors, LiDAR arrays, and HD maps that require enormous upfront investment before entering any new city. “When you need to move to a new city, you need to invest tens, if not hundreds, of millions into this infrastructure work,” he said. Tesla, on the other hand, has made the consumer vehicle its canvas, but still hasn’t delivered on unsupervised autonomy. “You don’t have a personal car that you can buy from Tesla with FSD (Full Self-Driving) that can run in a way that the person can start working, watch videos, and read emails. You must work in a mode that is ‘eyes on’.”

The result, as Raichelgauz puts it, is “a disconnect”: one side has autonomy that doesn’t scale, the other has scale that isn’t yet truly autonomous. Industry analysts broadly agree: while Level 2 ADAS is expected to become the standard baseline across new vehicles through the 2030s, Level 5 autonomy remains a distant goal on a potentially multi-decade timeline.

The practical payoff is that it can run on standard automotive sensors and existing compute platforms, without requiring the expensive hardware stacks that make Waymo-style deployments hard to replicate. “We want to make sure this technology becomes mainstream, where people can get the time back from driving and start working,” Raichelgauz said, describing eyes-off Level 3 capability as the near-term commercial target rather than full robotaxi autonomy.

To get there, the company has secured partnerships with Uber, NVIDIA, and VinFast to run two contrasting real-world proving grounds. Germany’s Munich for European regulatory rigour, and South Asia, particularly Vietnam, for the sheer chaos. “If we can solve autonomous driving in Hanoi on a regular car, we can solve it everywhere,” Raichelgauz said.

Chinese OEMs are already taking the lead on sophisticated ADAS integration in their home markets, which means the window for Western-aligned players to establish an OEM-agnostic standard is finite. Autobrains is betting that the company that cracks affordability and scalability will ultimately define what autonomous driving looks like for most of the world’s drivers.

“The first starting point is ‘eyes off’,” Raichelgauz said. “When you can take your car driving from home to work without really supervising it… without paying tens of thousands of dollars to upgrade to a robotaxi.”

You can watch the entire exchange in the video above.

Thanks for reading The Spiro Circle! This post is public so feel free to share it.

Watch us discuss this topic in a 5-minute preview of this episode: Tesla, Waymo, and the Self-Driving Race Nobody's Won Yet

Every boardroom in the world is having the same conversation right now. A vendor pitches an AI product. Someone on the executive team then asks the question that has become the most disruptive five words in enterprise software: “Can’t we just build it?”

Increasingly, the answer appears to be yes. The barrier to generating a working prototype has collapsed. With the right prompt and an afternoon with plenty of coffee, a modest technical team can produce something that looks convincingly like the product they were just quoted six figures to buy.

And so, the logic follows: why pay for what you can build yourself?

Daniel Zahavi thinks this instinct represents the peak of the current AI hype cycle and that the correction will be painful for the companies that followed it. Born in Kermanshah, Iran, in 1985, he immigrated to Israel at the age of 15, studied electrical engineering at the Technion, and earned a doctorate in Information Theory, the mathematical field underpinning modern large language models.

During IDF service, he held one of the highest security clearances in the military, working on projects touching the Prime Minister’s Office and the Intelligence Corps, before going on to develop drone interception systems and offensive cyber capabilities. He has now co-founded Arito, an AI analytics platform for finance and revenue teams, which raised $6 million in seed funding last month.

When Zahavi talks about commercial survival, there is biographical weight behind it. His defense technology business was blocked from export by Israel’s own Defense Ministry: a working product that couldn’t reach its market. He knows what it costs to build something that turns out not to be deployable.

That experience sharpens his read on the ‘Build vs. Buy’ trap now playing out in enterprise AI.

“Right now we are at the very top of that hype cycle that everyone believes that they can build whatever they need themselves easily,” he told me. “The amount of people that know exactly what they need and what they want is not very high. The portion that knows exactly how to describe that in very high resolution so that you can actually get what you need is even lower.”

Building anything genuinely useful with AI requires a clear understanding of the actual problem, and the ability to specify it with enough precision so that a model can act on it reliably. Most organizations have neither. They have a vague sense of the pain and a vocabulary borrowed from demos. But that produces impressive prototypes and disappointing production systems.

But the main point is what happens after launch. “Writing the code is only the first part,” he added. “Maintenance is a way, way bigger part of creating it the first time. I’m not even talking about security and privacy. A lot of the actual challenge continues afterwards.”

This is the consideration in the ‘Build vs. Buy’ debate that goes ignored. The prototype is cheap, but maintenance is not. And unlike a purchased product, where maintenance, iteration, and accountability belong to the vendor, the self-built version belongs to whoever built it, permanently.

Finally, Zahavi frames this as the difference between tools that produce what he calls “one-off artifacts” and tools that compound value over time. Asking an LLM a question and getting an answer is a one-off artifact, easy to replicate, easy to replace. But to build a system that learns how a specific finance team defines its metrics, tracks how those definitions evolve across fiscal years, and surfaces anomalies against that institutional context in real time is something much harder to build in a weekend or ‘vibe-code’.

“The only question that they need to ask themselves is: ‘Are they creating continuous long-term value for their customers and not just a one-off thing that can be solved easily?’ Because if it’s a one-off thing, then the chances of them being replaced by an AI prompt [are] very, very high.”

The hype cycle will correct. For Zahavi, who has spent a career building things in environments that were actively trying to stop him, like war zones, military bureaucracy, or the Defense Ministry that blocked his exports, the question of what survives hostile conditions is not theoretical.

You can watch the entire conversation above, or you can watch a snippet of this particular topic below:

Last week, I heard a number that should terrify every founder raising a Series A.

Between 50% and 60% of Israeli tech startups that reach round A never make it to round B. Think of it: You’ve pitched, hustled, and convinced initial investors that your idea is worth betting on… yet statistically, you’re more likely to flame out before the next round than not.

The reasons are messier than most founders want to admit. It’s not always the product or market. A lot of the time, it comes down to one hire. The first real sales leader you bring in to crack the US market. Get it right, and you’re soaring your company to new levels. But get it wrong, and you’ll be burning through runway while pretending everything is still fine.

This week on The Spiro Circle, I spoke with Giora Gil-Ad about the most dangerous (and weirdly emotional) hire in Startup Nation - the first serious US sales executive.

That’s exactly the world he operates in. As the founder of CQ Global, Giora specialises in one very specific, very high-stakes moment in a company’s life: finding the sales exec who will either unlock the US market or become a very expensive lesson.

In our conversation, Giora puts the cost of a wrong VP hire at somewhere between $1.5 and $2 million, once you account for the salary, the team members who follow them out the door, the deals that slipped through the cracks, and the months of momentum lost.

But the money is almost the easy part to quantify. What’s harder to measure is the founder who starts second-guessing themselves. The team morale evaporates, or investors start asking harder questions. A bad hire can cost confidence, and in the early startup space, confidence is everything.

So what does getting it right actually look like? According to Giora, it starts with founders being honest about what they actually need, and accounting for cultural, business, and personal needs along the way.

You can learn more about this whole area in the episode above.

I’ll be honest: I entered into this most recent conversation for The Spiro Circle knowing almost nothing about quantum computing. I said as much to my guest, Itamar Sivan, co-founder and CEO of Quantum Machines, before we even started recording. That’s alright - most people don’t really understand it, he told me. Even scientists used to laugh at the idea that quantum computing would ever be commercially viable.

But then, about halfway through our conversation, he said something that piqued my curiosity and made me put down my notes.

The threat isn’t that quantum computers will simply ‘make things faster’. It’s that they’ll make things possible that are currently impossible. And one of those things is breaking the encryption that protects everything - and keeping cryptographers up at night. He cited potential examples as banks, messages, the NSA, and Bitcoin.

“Quantum computers are not interesting because they’re going to take problems we solve today and solve them faster,” Sivan told me. “But rather they will take problems today we deem as impossible and make them possible.”

The mechanism is an algorithm called Shor’s algorithm, which can factorize enormous numbers at speeds no classical computer could approach. Modern encryption is built on the assumption that factorizing very large numbers is effectively unsolvable. But by taking away that assumption, the entire architecture collapses. “Something that would take a hundred thousand years might be solvable at the scale of minutes,” he told me.

Quantum Machines (QM) is a Tel Aviv-based company that has raised $280 million to build the orchestration layer running quantum processors. Founded in 2018, customers include academia, national labs, and the private sector.

What struck me was that he raised this before it exploded as a mainstream story. At the time of our recording, he flagged that a newly published paper suggested quantum computers would need far fewer qubits to break encryption than previously thought. “We’re still digesting it. If they’re right, we’re going to see some big changes in the world in a few years.” And almost as an aside: “One of the claims is that it will be able to break the underlying encryption used for Bitcoin. Just that itself could be a big impact.”

Research published between May 2025 and March 2026 shows that breaking widely used cryptographic systems may require far fewer quantum bits than previously thought. Estimates dropped from around 20 million physical qubits in 2019 to under one million by 2025. Papers from Caltech and Google in early 2026 prompted one Bitcoin security researcher to estimate a 10% chance that a quantum computer recovers a Bitcoin private key from an exposed public key by 2032.

In April 2026, a researcher successfully broke a 15-bit elliptic curve cryptography key using publicly accessible quantum hardware — a 512-fold improvement over the previous public demonstration just months earlier.

Google has already set a 2029 deadline to migrate its own authentication services to post-quantum cryptography. The so-called “harvest now, decrypt later” threat (adversaries collecting encrypted data today, waiting for quantum capability to mature before cracking it) means the clock is ticking, even though many still believe their things will be protected for many more years.

Sivan’s broader point, the one I kept coming back to, is that quantum won’t replace the computing infrastructure we’ve built - but instead plug into it. It means the vulnerabilities we’ve built into that infrastructure travel with us.

“Not a question of if,” he told me as we finished. “A question of when.”

I didn’t know much about quantum computing before this conversation. But I think I know enough now to think that answer should concern all of us!

Watch a 5-minute preview of our conversation on this topic, here:

Imagine the scene: A developer at a large financial institution merged a routine code update. Nothing alarming yet, just a minor change that, on its own, meant little.

But Terra Security’s AI agents were watching.

AI agents flagged the change, verified a potential vulnerability, and then did something a human penetration tester probably wouldn’t have done. They kept looking. Eventually, they found two more vulnerabilities nearby, each individually insignificant. But they spotted a pattern and connected all three together.

“1+1+1 = 1,000,” said Shahar Peled, co-founder and CEO of Terra Security. The result was a Remote Code Execution (RCE), a cybersecurity vulnerability that allows an attacker to run malicious code on a target system or server from a remote location. It is considered one of the most critical vulnerability classifications of its type.

The customer found out from their vendor, not from an adversary.

Founded in 2024, the Tel Aviv and New York-based startup has raised $38 million across a rapid Seed and Series A, and counts Fortune 100 enterprises among its customers. Its core product is an agentic offensive security platform where swarms of AI agents are trained to think and act like “ethical hackers”, running continuously across a company’s attack surface.

The traditional model of penetration testing (hiring an external team once or twice a year to probe for weaknesses) was never designed to catch what Terra caught in that unnamed financial institution. “Until 2025, it happened on an annual basis mostly,” Peled explained. “Once a year, you hire someone externally to work for a week or two weeks... The reason you couldn’t do it continuously is that you couldn’t really train software to hard-code how adversaries think and act.”

But AI has changed all that. Terra Security’s agents scan for known vulnerabilities and simulate the reasoning of an attacker, chaining together findings and verifying whether a vulnerability is actually exploitable rather than merely theoretical.

But Peled is careful not to overclaim, and beat me to my own next question. “Are AI agents today better than any ethical hacker in the world? They’re not,” he said. “They don’t yet possess the creativity of the best ethical hackers. But they can be more scalable than anyone in the world. They can run continuously. They never sleep. They’re already better than the vast majority of ethical hackers in the world.”

With AI, there are no longer cyberattackers who wait for annual review windows. Adversaries now use tech to find entry points faster, adapt in real time, and strike before defenders can patch. A point-in-time test is, by definition, already outdated the moment it concludes.

Terra’s idea is that continuous, AI-driven offensive security is the only architecture that matches the pace of modern attacks. The chained vulnerability Peled mentioned in our conversation was only catchable because an agent was watching the moment the code changed - and not six months later, when a consultant finally showed up.

“I still see too many organizations that say, ‘Okay, now we have AI in offensive security’,” he concluded, and as a slight warning to CISOs still budgeting for annual pen tests. “[They say] ‘I want to do the same thing I’ve done before, just faster, better, cheaper’. And that scares me.”

There’s a new security risk out there, and it’s come to be known as The Shadow AI Problem.

It suggests that the next major corporate data breach may not come from a sophisticated nation-state actor or a phishing campaign, but rather from an employee asking an AI chatbot to read or summarize sensitive company data.

That’s the reality Itamar Golan has spent the last two years building a company around. As co-founder and CEO of Prompt Security (acquired by SentinelOne earlier this year for $250 million), he has become one of the voices warning of the gap between how fast enterprises are adopting AI and how little they understand about where their data is going. According to him, most CISOs focus on traditional attack vectors, but the real risk is employees pasting IP addresses into unauthorized tools.

Prompt Security’s platform now detects nearly 20,000 distinct AI applications operating across enterprise environments. Golan clarified that the figure isn’t plugins or product variants, but 20,000 separate entities. “Today, essentially almost any SaaS application, website, native application running on your endpoint… we are converging towards a landscape where any one of those will be an AI application by itself,” he told me.

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The visibility problem is one thing, but the training problem is another. Prompt Security’s research found that roughly 40% of AI applications, when surveyed at the configuration level, are set by default to train on the data they receive. “Not only has confidential data leaked out of your organization,” Golan explained, “it’s now potentially becoming part of the model’s brain.” Details like corporate strategy, personnel data, or legal documents will be available for everyone to see - and there is no obvious retrieval mechanism once embedded in a model’s training run.

The sectors most exposed are also the typically traditional ones that are now moving fastest to catch up: Financial services, insurance, and legal firms are adopting AI precisely because it performs exceptionally well on their core workflows. “They find themselves in this very tricky situation,” he told me. “On the one hand, they are adopting AI the fastest, and the potential gain is immense, but the risk of making a mistake is so big as well.”

It is a distinctly Israeli problem to be working on. Golan mentioned that when he surveyed the security stacks of Fortune 500 CISOs while building Prompt, he found that around 60% of the tools on their lists were built by Israeli companies. Startup Nation has given the world Check Point, CyberArk (acquired by Palo Alto Networks), and Wiz (acquired by Google). Now, Prompt Security, as part of SentinelOne, is trying to secure the AI layer that sits above all of them.

“We cannot stay blind,” Golan concluded. “We must admit that our employees are using hundreds or thousands of AI applications. A big portion of those are able to train on the data we are sharing with them.” Acknowledging that reality, he argues, is the first step to acting on it.

This isn’t the first time I’ve covered Israel’s foodtech sector. Back in 2022, reporting for CTech, I mapped the ecosystem at a moment of tension, when investment was holding up better than in any other tech vertical, but the skeptics remained.

I was, and still am, bullish on Foodtech - at least at the start. I tasted 3D-printed burgers in Tel Aviv and called them “technically perfect, albeit creatively void.” I interviewed investors who compared the industry to early mobile phones — primitive first iterations, but with everything still to come.

I wanted to delay a full embrace of alternative foods until the markets all caught up. Turns out many felt the same way. So years later, I wanted to revisit all of that with someone who’s lived it from the inside.

Ilanit Kabessa Cohen has spent 25 years asking one question: what does it actually take to bring innovation to market? As the first Head of Innovation at Osem-Nestlé, a corporate venturing lead at Dole in Singapore, and now co-founder of the advisory firm URIKA, she’s seen the food ecosystem from virtually every angle — and she joins me to share what she’s learned.

Our conversation opens with an assessment of Israel’s position in global foodtech. Despite being a relatively small player in terms of total funding (roughly $16 billion globally), Israel punches well above its weight: driven by its kosher culinary traditions, research institutions, a culture of cross-domain improvisation, and the Israel Innovation Authority’s risk-sharing model that few other governments have replicated.

But Ilanit is candid about where the industry fell short. The first generation of alternative proteins disappointed consumers, investors, and believers alike. Not because the vision was wrong, but because first-generation products rarely win. She argues we’re now entering a correction phase, with more mature companies, better-tasting products, and a smarter understanding that the real action right now is B2B ingredients, not consumer-facing brands.

The most forward-looking part of the episode covers what she calls “animal-free technologies” — a next-generation wave that goes far beyond food. Think collagen produced via precision fermentation for use in cosmetics, pharma, and nutrition. Or how biomaterials could replace shark liver extract or horseshoe crab blood in medical testing.

She said how the next decade of opportunity lies in the convergence of food, health, and biotech - and finally, she discussed two opportunities: the Coller Startup Competition (now open, with a $100K prize) and URIKA’s Generate partnership program with CSM Ingredients for startups in sugar reduction and proteins.

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Datarails CRO Aviv Canaani has an unusual vantage point. He runs the full revenue engine of the financial planning and analysis platform for Microsoft Excel users — sales, marketing, partnerships — from New Jersey, while his marketing team operates out of Israel.

He relocated to be closer to the North American customer base as the marketers stayed put. And after years of sitting inside both ecosystems at the same time, attending CMO sessions in Tel Aviv and building pipelines in the US, he’s reached a verdict most people in his position wouldn’t say out loud: the Israelis are better.

It’s a claim that cuts against the instinct of almost every Israeli founder he’s encountered - and every company I’ve spoken to over the years. “Normally, when I speak to startups that are born in Israel, they want to send their sales and marketing overseas immediately. [It’s] the first thing they want to do,” I told him during our conversation. But Canaani’s experience runs the other direction.

The Israeli edge, he claims, comes down to a cultural obsession with output. “When you talk with people in Israel, marketing leaders, it’s about how they built machines, how much the cost per meeting, how they’re running campaigns on Facebook and Google and all that.” American counterparts, he finds, often arrive at the conversation from somewhere else entirely. “A lot of CMOs and people in marketing I talk with in the US or Canada… can talk more about the brand, how things take time, like it’s a long-term investment.”

“Tachlas mentality” explained

He traces this back to something structural in Israel’s tech DNA: The concentration of adtech companies and the performance-marketing culture they seeded, and also what he calls “tachlas mentality”. He explained that this requires teams to be focused on results above everything else. The blend of that mindset with an unusually international talent pool (many ‘Olim’ from Britain, the US, or Europe) produces something Canaani finds hard to replicate in America.

But there’s a catch - and one worth remembering. The same intensity that makes Israeli marketing so effective in the early stages carries a structural weakness as companies grow. “In North America, things are much more organized. It’s clearer how they create the messaging and the product marketing and how to make sure there is alignment between marketing and sales,” he told me. Israel, by contrast, tends to run so fast that alignment becomes a casualty. “It seems like sometimes it doesn’t even matter if marketing speaks one language and sales speaks another. Let’s just run fast. It’s speed above everything else.”

The American advantage, then, is less about raw marketing talent and more about institutional discipline. “In North America, maybe it’s hard in the startup phase, but once they’re a bigger company, they have better processes — how to run things, how to stay on point.”

So what Canaani is describing is a stage-mapping problem. Israeli performance marketing is almost perfectly calibrated for the zero-to-one phase: find the signal, iterate fast, fill the pipeline before the runway ends. But American marketing discipline becomes the dominant advantage once you’re scaling and when the team is distributed. Move fast and break things, but then slowly mold them into greatness.

The companies that figure out how to sequence both are the ones most likely to build something that lasts. Datarails, with teams operating on both sides and a CRO who has lived inside both cultures simultaneously, is running that experiment right now.

[5-minute preview: Why Israeli Startups Are Better at Marketing Than They Think]

Every few years, a new American administration arrives in the Middle East convinced it can start fresh. Trump’s team was no different. They came to the problem with a clean slate and nothing but the confidence of a New York real estate mogul. They produced two documents across both his terms: the January 2020 plan and the October 2025 twenty-point Gaza framework.

The result, according to my guest Gidi Grinstein, was that they landed exactly where everyone always lands.

“Even Trump ends up landing very close to where Nixon landed, to where Carter landed, to where Clinton landed,” he told me. “Because there is a gravitational force that is shaping these negotiations.”

Gidi Grinstein has seen the Middle East from angles most people never will. At 29, he was the secretary of Israel's negotiating delegation at Camp David and the youngest person at the 2000 Summit. He spent years inside the machinery of the peace process drafting texts, aligning teams, and managing the distance between what leaders said in public and what they were willing to accept in private.

Today, he runs Tikkun Olam Makers (TOM), a global initiative using open-source 3D printing to bring affordable prosthetics to people who can't access or afford conventional ones. While we intended to speak mostly about TOM, our conversation stayed on peacebuilding, negotiation, and his view of politics today.

The force, he said, traces back to “the most brilliant and American diplomat of the last hundred years”, Henry Kissinger, and the architecture he designed in the 1970s. It was a framework built not around Israeli or Palestinian interests, but around American hegemony in the Middle East. Half a century later, and it is proving so durable for Washington that no administration, however disruptive, can break from it.

The 2020 Trump plan's "two nation states for two people" echoes UN Resolution 181 from 1947. The 2025 Gaza framework in places reads like a revamped version of the Oslo Declaration of Principles from 1993. “You would be stunned by the amount of similarities,” he told me.

What’s interesting this time around is that both countries - Israel and the US - face impending elections mere days apart, promising to shake up not just the political makeup for both sides, but potentially the leadership of one.

This creates what Grinstein calls the clock problem: Israeli and American leaders, under electoral pressure, always want a deal now. Their counterparts (Arafat then, the Iranians today) operate on an entirely different political timeline, with every incentive to wait out a weakened or transitional government.

“The synchronization of the political clocks is very important in getting the deal,” he said. Trump, he suggests, may be walking into the same trap by pushing hard before November while Tehran calculates what comes after.

The gravity doesn’t guarantee peace, but I realized it means the frameworks are always roughly the same so long as the Americans are involved. And so far, history is showing us that they always find their way back to them.

You can catch the entire conversation above. And expect more analysis from our conversation in future newsletters.

[5-minute preview: Watch Gidi explain this in a YouTube clip, “Trump Thinks He's Rewriting Middle Eastern History. He's Repeating It.”]

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As conflict dynamics shift across the Middle East, from disrupted shipping lanes to drone warfare, a new question is emerging: who controls the software behind autonomous systems?

Military power used to depend on access to advanced weapons systems, often built through international supply chains and dominated by a handful of large contractors. Today, conflicts in Ukraine and Iran, and tensions with China, are highlighting bottlenecks on critical technologies and the instability of disrupted supply chains.

One Israeli company may have an answer to this new challenge. Udi Oster is the co-founder of eyesAtop, a startup building AI-native universal controllers for drone fleets. The company has spent the last three years making a case that the strategic asset in modern warfare isn’t any particular drone, but it should be the operating system above them.

“Locking in to one vendor with one platform is something that in today’s world is very difficult,” Oster told me. “You want to have the flexibility to get the best technology at the point of time of interest and use it immediately.”

Militaries around the world are accumulating drones from dozens of manufacturers, but without a common interface, any shared AI layer, or no easy way to retrain operators when hardware changes. EyesAtop’s platform intends to integrate into any drone, from any vendor, under one controller trained on over 500,000 hours of live IDF operational data.

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The geopolitical context of conflicts and wars has expanded this market. Global defensetech VC hit a record $49.1 billion in 2025, nearly double the prior year, driven largely by autonomy and AI. American firms like Anduril have already moved into Taiwan, South Korea, Japan, and Singapore, selling hardware to nations trying to face off against the Chinese military. eyesAtop is pursuing a different layer of the stack: not competing on the drone itself, but selling the so-called brain that integrates whatever drones those nations already operate or plan to buy.

Oster draws a sharp distinction between the American market and everyone else. America is its own category: It accounts for more than half of global defense spending, it has its own procurement logic, and its own concept of operations. EyesAtop already has a U.S. co-founder, a U.S. base, and existing deals with American military commands.

For the rest of the world, the company offers a full-kit solution, where it selects the best available platforms globally, integrates them under its universal controller, and delivers a turnkey reconnaissance or strike capability to militaries that lack the R&D infrastructure to build it themselves.

“Most of the countries outside of the U.S. lack the infrastructure and the R&D budgets even to get to the same type of level as Israel and the U.S.,” Oster said. “I would look at these countries differently.”

The fundraising backstory underscores how fast the landscape has shifted. Three years ago, Oster says, virtually no Israeli VC would touch defense. The stigma was visible and impacted reputational and commercial opportunities. But the world changed after October 7, 2023, and today, funds are competing for allocations in a sector that now ranks among the top three investment themes globally.

The longer-term vision Oster sketches is more ambitious than any single product cycle. As robotic systems multiply on the battlefield, army headcount becomes less relevant than software sophistication. Today, wars can be fought by one operator controlling multiple autonomous platforms that were trained in actual combat. “Instead of having a whole company,” he says, “you have two people, but they would operate a company of robotic systems.”

He calls it "the ghost squad." For the allies now looking to build drone sovereignty in the middle of an active regional war, it may also be the next software contract they don't know they need. And that balance of power is moving up the stack.

[3-minute preview: Optimism in Defensetech and the future of deterrence]

I know better than anyone that there’s a version of Startup Nation that the world is perfectly happy to celebrate. The record exits, the Wiz acquisition - $15.6 billion raised in 2025, with exits totalling $74 billion. Those stories write themselves. I know that because I spent five years doing it, too.

But the other story, the one about what it actually takes to keep a company’s messaging intact in wartime, is harder to tell, and rarer to find someone willing to tell it honestly.

So I spoke to Alona Stein, co-CEO of ReBlonde, one of Tel Aviv’s more influential tech PR agencies. She has spent 13 years managing the gap between what Israeli founders want the world to know and what the world is prepared to hear. Since October 7, 2023, that gap has never been wider.

“There’s an axis,” she told me, “between showing resilience and chasing ambulances.” It sure sounds like a line from a crisis comms handbook, but the way she says it, it’s more like a warning.

The question of how to position an Israeli company is becoming existential. Do you lean into the Israeli identity, or quietly let the Delaware incorporation do the talking? In my journalism days, I lost count of the number of founders who told me: "Don’t write that we’re Israeli - we’re a ‘Delaware’ company.

During recent recordings of this podcast, we had a standing protocol for missile alerts. I would ask my guests if they wanted their run to the shelter included in the final episode in the event we were interrupted. The split was about 50/50: Half wanted to show Israeli pride, and the other half didn’t want to spook overseas investors or customers.

Alona knows that conversation well.

“Do we move forward with the fact that we’re Israeli-based and Israeli-formed? Do we just talk about that headquarters somewhere else? It really depends on the kind of personality they have as a founder, but also the kind of business that they run and the kind of clients they sell to,” she told me.

One example that came up, as it often does, is Wiz. The company went out to the world openly Israeli, and it never hurt them. But Wiz is Wiz. For companies with global client bases in sensitive markets, the calculation is different. She describes one client (a German company returning after several previous engagements) who pulled out at the last minute when their CFO discovered the agency was Israeli.

“Everything was already set. Even the kickoff date was scheduled. And then the guy said, ‘Listen, I’m so sorry, but our CFO was not aware that you’re Israelis and we have a policy that we can’t work with Israelis.’”

That's what ground-up narrative collapse looks like in practice: when public sentiment, left unmanaged for long enough, works its way into boardrooms. Alona traces the mechanics of it back to what happened after October 7, when she joined a pro bono initiative called Words of Iron, working to flag false information spreading on X about Israel.

“I understood that this is where the narrative starts. It’s driven [by] the people, it’s driven from the masses. And then it affects so high up, to the point where VCs pull back, clients pull back, because the public sentiment is so bad.”

The Iran conflict has added new layers to this. Nearly half of Israeli tech firms reported struggling with worker shortages during the conflict, and the ongoing conflict made it more difficult for entrepreneurs to secure funding in the short term, with global investors adopting a more conservative approach until the situation stabilised.

For PR agencies navigating this, the question isn’t only what to say, but it’s whether to say anything at all. “If the coverage is mostly around what is happening in the war and your story can’t contribute to what is happening right now, there’s no room for that.”

What makes her perspective useful is that she’s been here before. COVID, the post-October 7 period, now this. Each crisis has required a recalibration of the same fundamental question: what is your company actually contributing, and to whom?

“You can provide good value. You can talk about the product without throwing names for the sake of throwing names, especially for such explosive matters.”

During the lead-up to and throughout the campaign against Iran last year, 31 funding rounds took place — evidence that entrepreneurs kept building and investors kept writing cheques. But whether the narratives around those companies held are a different question.

When we speak, there isn’t a clean resolution. What Alona has is 13 years of knowing where the line is between resilience and so-called ambulance-chasing, and the professional discipline to hold it even when founders don’t want to.

There is a record being broken in America right now, and almost nobody is talking about it.

According to U.S. Census Bureau data, 5.48 million new businesses were formed in 2023 — the highest annual total ever recorded. That number has barely dipped since, running at over 5.1 million annually through 2025, a figure that represents a near-50% increase on the pre-pandemic baseline. February 2026 alone saw a 12% year-over-year jump in new entity formations, according to Registered Agents Inc., which tracks state-level filings in real time.

To some, this looks like a boom. But if we look closer and learn the stories behind those new businesses, it looks a bit different.

Across the same period, the tech sector, once seen as the safe bet for educated young professionals, has been shedding workers at a pace that few predicted and fewer have absorbed. In 2025 alone, nearly 246,000 tech employees lost their jobs. In the first months of 2026, another 95,000 have followed.

Amazon, which reported record revenues of $716.9 billion last year, has already cut around 16,000 roles this year. Meta, spending up to $135 billion on AI infrastructure in 2026, is eyeing reductions that could eliminate up to 20% of its workforce. Oracle conducted its single largest layoff event in recent memory, cutting 30,000 employees in one stroke.

The people standing in the rubble are doing something interesting: they’re not waiting to be rehired. They’re building something of their own. And those who were told to “learn to code” to keep up with yesterday’s job trends are coming out victorious.

The Galloway Thesis, Applied

I discussed this topic on The Spiro Circle this week with Tom Lahat, co-founder and CXO of Tailor Brands. Tailor Brands is an AI-powered platform that helps individuals form LLCs, build brand identities, and launch small businesses in the United States. It started as a logo generator; it has since evolved into what Lahat calls a “business-in-a-box” - handling everything from paperwork and EIN registration to insurance, permits, and legal structure. In its current form, it is effectively the infrastructure layer for a new kind of worker: someone who used to have a job title and now has a company instead.

It reminded me of one of my favorite writers and speakers on the subject. Scott Galloway has been making a version of this argument for years, most explicitly in his book The Algebra of Wealth, which I read last year. His claim, "Don't follow your passion. Instead, follow your talent," was contrarian when he first made it. It is beginning to look prophetic.

Lahat shares data, which he agrees tells a story about professional aspiration that the last decade got badly wrong. “The job that was desired five years ago today is nothing,” he said. “Being a developer was the best thing you could be. You could go into Meta, Amazon, or Google, and basically, you had a safe path. That thing changed.”

His observation relates to the speed of the current disruption felt nowadays, especially in the AI era. The roles that were most reliably insulated from economic downturns, like senior engineering, backend development, or data analysis, are the ones being targeted in the current wave of AI-driven restructuring.

According to research published in 2026, an estimated 44% of recent tech layoffs are directly or indirectly attributable to AI automation.

The Return of the Tradesman

Here’s where Tailor Brands can help this adjusted workforce. One of the less-discussed consequences of this shift is what it is doing to blue-collar labor markets. Skilled trades like plumbing, electrical work, construction, and metalwork spent much of the last 20 years being socially devalued in favor of knowledge-economy careers. Parents who once pushed their children toward law or medicine pivoted to an emphasis on software and high-tech.

The Obama-era cultural message was consistent: work with your mind, not your hands, and “learn to code”.

Well, not anymore. The market has begun to correct this. Lahat describes a user from North Carolina — a man who spent his twenties and thirties resenting the metalwork trade his father had pushed him toward — who has seen his income rise 15% annually for three consecutive years. Demand for skilled trades has increased precisely because AI cannot replicate them.

We reference the South Park episode that directly addresses this: An electrician cannot be outsourced to a large language model. These are the jobs Galloway pointed to when he invoked smelting as a career path. They are no longer a punchline. In fact, the jobs we were told to avoid are becoming the most resilient.

“We see a rise in blue-collar jobs,” Lahat said. “These are the things that AI won’t change. There’s a need for blue-collar jobs, whether it’s plumbing, construction, or electricity, and all of these titles suddenly see an increase in demand, which leads to an increase in the paycheck.”

What Tailor Brands is doing, in part, is giving these workers the business infrastructure to capitalize on that demand. A tradesperson who previously operated cash jobs informally through word of mouth and no formal entity can now formalize their practice and grow a legitimate business. The platform is designed to take the bureaucracy out of the equation entirely, so the gardener or the plumber or the wedding photographer can focus on the work rather than the paperwork.

The Generation Entering Now

The cohort now entering the workforce has had, to put it mildly, a strange preparation. First, they were in high school during the pandemic, learning remotely or socializing through screens. This meant developing an entire set of professional instincts in conditions that bore no resemblance to any labor market that preceded them.

Today, they are entering the workforce in an AI disruption cycle that is accelerating faster than any analyst predicted.

Lahat is direct about the challenge this presents. “Every day you open the news, and you see that Meta lays off 30,000 people and Amazon fires 15,000 people,” he said. “The people they are firing are from all departments: the developers, the back end, the analysts. And every morning you read the new Google or Anthropic update, and you’re like: who’s going to get it now?”

For a 20-year-old choosing a direction, this is not an abstract concern. The career ladders that earlier generations climbed are visibly disintegrating. Job-hopping, which became normalized among us millennials as a form of career acceleration, now looks almost quaint compared to the structural volatility that sits underneath it.

Today, young people are wondering if joining a company, in the traditional sense, is even the right move.

Tailor Brands’ own data reflects this shift. The share of users on their platform who hold four or five separate LLCs has grown from roughly 5-8% four years ago to nearly 30-40% today. These are not serial entrepreneurs in the Silicon Valley but people building portfolio careers out of necessity and pragmatism — they are so-called “weekend warriors” who operate a Monday-to-Friday job alongside a second weekend gig, each with its own entity to hedge against the collapse of any single income source.

The Skills That Survive

This trend is fascinating to me - both as a journalist and as a father. Both Lahat and I have young children, so I asked him, setting aside his role as a founder and industry observer, what he plans to actually teach his kids.

“The best tools I can give my kids, the advice, is how to self-learn,” he said. “That’s 100%. There isn’t a university, there isn’t a course, there isn’t a YouTube yet because version one was yesterday and today version two is already up, and it’s different.”

But Lahat’s definition of curiosity has a second layer that is less obviously teachable, and perhaps more important. He spoke about the ability to talk to another person to generate ideas in conversation, collaborate, and convey trust in a room. It is something I learned when I spoke with founders and presented at a conference. But these are skills that the pandemic disrupted badly in those now entering professional life, and that AI is doing nothing to restore.

The American Dream Is Not Dead. It’s Just Honest Now.

The American record for new business formation has been broken in back-to-back years. February 2026 saw formations running 12% ahead of the same month a year prior, even as hiring slows and layoffs accelerate. The pattern Registered Agents Inc. identifies in its monthly tracking report is a behavioral shift that has been underway for five years and shows no sign of reversing.

“The concept of starting a business and being responsible for my own destiny… It’s extremely rooted in the American culture,” Lahat concluded. The American Dream is not disappearing, but it is being renegotiated. The version that required a degree, a corporate ladder, and 30 years of institutional loyalty is giving way to something arguably more honest about what the economy has always rewarded: people who know what they are good at, who can convey that to another person, and who have the discipline to build something around it.

Galloway told young people to follow their talent. The data from Tailor Brands shows people are doing it. Follow your talent, formalize it, and don’t wait for someone else to permit you to start.

[5-minute preview: Why Blue-Collar Jobs Are Beating Tech Careers in 2026]

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The last two years in AI have been disorienting.

Every week brought a new model, a new product launch announced on X, and a new reason to reconsider assumptions that felt settled only months before. For startups trying to keep up, the experience has been less like riding a wave and more like trying to read a map while the terrain keeps shifting beneath you.

It was something I discussed on another episode of The Spiro Circle only a few weeks ago. But this time, according to Tom Findling, Co-founder and CEO of Conifers, the disorientation was merely a prologue for what’s to come.

“The last two years were a promo to what’s going on,” he said. “I think starting in 2026, you really see the maturity, both on the model side and the agent side, to come and really disrupt the enterprise.”

If the explosion of GPT-4, autonomous agents, Claude’s product launches, and multimodal models were just the opening act, what exactly is coming next?

The Convergence Moment

Findling claims the answer is in a convergence that is only now becoming visible. For most of the AI boom so far, the two core components of enterprise deployment (the models themselves and the agent frameworks built around them) were developing on separate tracks. Models were getting smarter, and agents were getting more capable - but the combination wasn’t yet reliable enough to deploy seriously inside a large organization. “I think we got to the point that agents got to a certain level of maturity when you can deploy them in the enterprise, you can monitor them, you can scale them, and the models themselves have become extremely smart.”

SOC teams face alert volumes that no human workforce can realistically process. Analyst shortages are chronic, and Findling estimates that fewer than one percent of applicants for analyst roles can actually do the job. Previous attempts to close the gap were built on rule-based logic that couldn’t adapt to the context-dependent, environment-specific nature of real incident investigation. “We tried for the last decade to solve that problem,” Findling said. “Unfortunately, it didn’t go that well. That’s why we still have business.”

CognitiveSOC, Conifers’ flagship platform, ingests thousands of daily security alerts, uses AI reasoning to investigate incidents autonomously, and delivers measurable outcomes. The company reports up to an 87% reduction in investigation time compared to human analysts working manually.

To date, the company has raised $25 million from SYN Ventures, Picus Capital, and Washington Harbour Partners, whose investment is aimed at expanding into government and critical infrastructure markets. The momentum reflects a growing conviction that agentic AI (systems that can act, not just respond) is the architecture that finally makes the math work.

“If you don’t fix it, it will break.”

Which brings the sharpest business lesson of the moment into focus: The philosophy of adoption. The adage that “if it ain’t broke, don’t fix it” is no longer relevant in a sector that is moving and evolving in weeks, not years. “If you don’t stay current, you become obsolete. Even for two quarters, if you haven’t looked at the latest and greatest, the new models, your product is already far behind.”

In our conversation, I highlight this inversion: It isn’t that change is “good” and stability is “bad”, but rather that the calculus of risk has entirely flipped. Waiting used to protect you from premature commitment, but now it exposes you to competitive irrelevance. The companies treating AI adoption as something to revisit once the dust settles are already making a strategic error that they may not be able to unwind.

A lot of our conversation focused on how these two years have seen such incredible transformations. He admitted he could not have predicted back then what he would be building today. Finally, Findling expects to look back on 2026 in two years’ time with the same sense of uncertainty.

The prologue is complete - but no one knows exactly what they’re about to watch.

[5-minute preview: Why “If It Ain’t Broke” No Longer Applies in AI]

Lior Yogev says he’s barely been home in three months.

The FundGuard CEO and co-founder has spent the better part of the year in client meetings, and the conversation at every stop has been a variation of the same thing. “Everybody is now thinking, how do we remodel how we’ve worked over the last 30 years?”

The forcing function is agentic AI and the shift toward autonomous systems capable of taking action across complex workflows without human instruction at each step. In asset management, the implications are massive. Compliance flags that require manual review could be triaged, contextualized, and escalated automatically. Portfolio data that currently arrives in overnight batch files could flow in real time to the decision-makers who need it.

FundGuard’s platform replaces legacy fund accounting systems with cloud-native infrastructure that handles everything from NAV calculations to portfolio accounting to operational automation, in real time rather than overnight batches. The company has raised more than $150 million, counts Citi and State Street among its investors, and now operates across six cities, including Tel Aviv, New York, and London.

The company’s thesis is that large banks and asset managers were using archaic core systems that were expensive, slow, and error-prone. The way this industry has operated “since the 1970s and 1980s” starts to look unprepared for the variety, complexity, and volume that he describes as spiraling out of control. “They can clearly envision the future that’s going to be totally different than the way that they’ve been working the last two or three decades,” Yogev explained.

The first obstacle is the infrastructure itself. The core systems still running much of the asset management industry were built in the 1970s and 1980s and updated minimally since. It is still a conservative and traditional space: large, singular, slow to change. They also process data in overnight runs rather than continuous streams. In Yogev’s framing, this is not an inconvenience to be worked around. “Legacy systems, because they’re [so] monolithic and batch-based, just don’t carry the weight and can’t really interact with the infrastructure that’s being built in the world.”

This creates a sequencing problem that the industry is only beginning to confront honestly. Agentic AI requires live data, modular architecture, and cloud-native infrastructure. Almost everything being built to power the AI revolution assumes these things exist. At most large financial institutions, they do not. The result is an enormous appetite for what AI promises, but paired with the structural inability to capture it.

The second obstacle is governance. Yogev described financial institutions as simultaneously the most excited and the most restrictive audience he encounters. “Most large financial institutions are going to ask you to turn off or disable the use of models, at least at this stage, and not even use their data in an anonymous way.” The concerns relate to data leakage, penetration points for bad actors, and regulatory exposure.

He draws a parallel to the cloud and to institutions' concerns about putting client data anywhere outside their own servers. It felt reckless, legally exposed, and competitively dangerous— until it didn’t. “Just like with the cloud, it took a few more years to be fully embraced by financial institutions. It’s going to be the same with AI,” he predicted. “Everybody is looking at what we’re delivering and gets very excited. And they go with us because they know that we’re futureproof.”

Yogev does not believe the AI transition will move as slowly as cloud, but warns: “If you don’t do it, you’re essentially going to die.”

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Institutions that have already modernized their core infrastructure by moving to cloud-native platforms, and in other ways, will be positioned to deploy agentic capabilities more quickly. But those still running batch-based legacy systems will eventually face a two-front problem: they will need to rebuild the infrastructure and close the AI gap, while competing against those who solved the first problem years ago.

The $200 trillion asset management industry has spent 30 years optimizing around the constraints of its technology. It is now up to institutions whether they can reverse that relationship before someone else does it for them.

[Preview: How better tech could add $100K to YOUR retirement]

When the US and Israel launched Operation Epic Fury, the opening moves were not B-2 bombers or Tomahawk missiles. Before the first strike aircraft crossed into Iranian airspace, Iran’s radars had already been blinded, its command-and-control links severed, its communications networks dismantled.

Within this context, one Israeli startup has spent four years building the communications infrastructure that conflicts like this one keep exposing as absent. Commcrete, which raised $29 million in seed and Series A funding — backed by investors including Mobileye founder Amnon Shashua — makes narrow-band satellite connectivity solutions that connect to geostationary satellites 36,000 kilometers away without requiring line of sight or clear skies.

Some of these devices are small enough to fit in a jacket pocket, and all are resilient enough to operate in all weather conditions.

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Most defense companies outsource the ethics of who they sell to — to export regulators, to governments, to the comfortable abstraction of compliance departments. Itzik Daniel Michaeli, the company’s co-founder and CEO and a former senior commander with over 25 years in Israeli special operations and intelligence, does not.

“There are the good guys and the bad guys,” Michaeli said. “It exists. And Hollywood can keep on pushing out those great movies about good guys and bad guys because eventually you saw that when the bad guys mean that they want to destroy you or to harm you, they’re putting their efforts, their money, everything on that.”

Commcrete’s products — Stardust, a 150-gram unit enabling voice, text, location and distress signalling; Flipper, which converts any radio into a satellite-enabled system; and Bittel, which extends those capabilities to vehicles — address a $200 billion global SATCOM market. Its tech is already deployed in active conflict zones, integrated into drone platforms, and operating in the hands of defense, public safety, and emergency response customers across multiple continents.

Since the start of the US-Israel war with Iran, GPS and navigation interference has surged across the Persian Gulf, disrupting shipping, aircraft, and emergency services across the region — exposing the degree to which modern infrastructure depends on satellite connectivity that can be jammed, spoofed, or seized.

Reports from analysts at CSIS and navigation intelligence firms have flagged evidence that Iran may be accessing China’s BeiDou satellite navigation system, boosting the accuracy of its missile targeting in the process.

Commcrete’s architecture is built for this environment. The system uses a proprietary waveform and protocol that make it near-invisible to adversaries. So if a user isn't transmitting, they don't exist on the spectrum.

During live demonstrations, the company invites customers to try to find Commcrete’s signal on the spectrum. Michaeli claims they can’t, which explains the company’s reported 82% demo-to-acquisition conversion rate.

While Michaeli doesn’t disclose his customers, he does disclose who he would - and would not - sell to. “You don’t want to put the weapon in the hands of your enemies, in the hands of your future enemies,” he said.

The question of who can get access to such technology comes with another layer of complexity, one that is specific to Israeli defense companies operating in the current geopolitical climate. Commcrete sells to customers in countries that cannot or do not publicly admit they buy from Israel.

Germany has spent recent years pressing Israel on West Bank policy while simultaneously proceeding with multibillion-dollar defense deals and resuming weapons export approvals. Finland’s president condemned Israel for violating international law, then purchased the David’s Sling air-defense system from Rafael. France blocked Israeli firms from the 2025 Paris Air Show and prohibited Israeli munitions from crossing French airspace. Israel ultimately ended all defense trade with the country in response.

Half his meetings occur in countries that have publicly criticized Israel and the company has been banned from three major international exhibitions. But the phone kept ringing regardless. “Some countries and some authorities are saying… with the same sentence, ‘we can’t buy your stuff but we really do like your stuff so maybe we can buy your stuff only if you… don’t mention that we’re customers’.”

The ongoing conflict has already answered the question of whether the market for what Commcrete builds is real. But the question that remains, and one that Michaeli has appointed himself to answer, is whose hands it ends up in.

“With great power, which is our technology and our capability to do that and to manufacture that, comes a great deal of responsibility,” he concluded. “I really believe in that. And I think that’s part of the game. You have to be in it. You have to understand it. You can’t avoid it. If you don’t understand the landscape of all those layers, you can’t be in the game.”

[5-minute preview: Selling Israeli defensetech in the face of political pressure]

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We were told never to get into a stranger’s car. Yet millions of us do it every day.

The rules most people grew up with (“don’t talk to strangers online”, “never open the door to someone you don’t know”) have been dismantled by the platforms we now use without thinking. Sharing economy platforms like Uber, Airbnb, Amazon Marketplace, and DoorDash run entirely on the assumption that strangers can be trusted at scale.

“We live in a generation that buys everything online,” said Yair Tal, CEO of AU10TIX. The Israeli identity verification helps organizations confirm that a person is who they claim to be when opening accounts, making transactions, or accessing services online. “We trust people that we don’t know. We go on a car share ride in the middle of the night in a place that you would never go into someone else’s car. This is where we live today.”

The question AU10TIX answers is simple: how do you know the person on the other side of the screen is who they say they are?

Before digital onboarding was a mainstream category, Tal was Senior Vice President and Head of Enterprise at Payoneer, trying to serve users in places where conventional verification breaks down. “‘The address is the house near the tree behind the garden’,” Tal recalled. “This is the home address. How do you validate that this is the right person?”

That problem of having to verify identity across emerging markets, for unbanked freelancers in Bangladesh, Vietnam, and Pakistan who needed access to global platforms, forced AU10TIX to build systems that Western banks never had to imagine. That early stress-testing became the architectural foundation for what the company does today.

Deepfakes Broke Identity - At Scale

The threat landscape, however, has changed faster than most anticipated. For most of identity verification’s history, fraud was fundamentally an individual problem. The scale was manageable, and the detection logic was straightforward: check the document, match the face. Deepfakes and AI-generated identities broke that model entirely. What was once a manual, one-at-a-time problem is now industrial.

“If we see for a specific company that there’s payments going into APAC of about 20,000 fake IDs in a day, we need to block them,” Tal said. “We’re not talking anymore about the individual. We’re talking about the massive scale of applications that companies are seeing — and it’s so easy to create them with deepfake.”

Detection can no longer happen at the document level alone, and AU10TIX’s automation-first architecture is designed precisely for this volume.

Privacy vs. Security: “The Two Number Ones”

Complicating matters further is the regulatory environment, which is pulling companies in two directions simultaneously. Governments are demanding stricter identity verification while also tightening privacy protections, creating what Tal calls a structural conflict with no easy resolution. “It is not that you can say that my highest priority is privacy and the second priority is security,” he said. “Both of them are your first priority.”

The practical answer AU10TIX has arrived at is to collect only what the decision requires. A platform that needs to restrict under-18 purchases doesn’t need a user’s address, employment history, or document number. It needs one binary answer.

The pub bouncer, Tal argued, doesn’t care where you live or what you do for work. He needs to know if you’re allowed to order that beer.

The stakes of getting this wrong are no longer abstract. Companies that have failed at the identity layer haven’t just faced regulatory fines. They’ve put people in physical danger. “We recently saw companies that lost their data, their reputation, their customers,” Tal said. “They took the wrong people into their cars. People stayed in the wrong apartments.” The sharing economy’s entire value proposition - that a stranger’s home or car can be trusted - collapses the moment that verification layer fails.

The next ‘frontier’ is digital government IDs and QR-code-based national verification, to the delight or horror of everyone. The promise is that they will introduce stronger source-level authentication, but new fragmentation challenges for companies operating across borders. Critics will be skeptical of government or private company attempts to collect, store, or exploit personal information.

The infrastructure will keep evolving, but the principle remains fixed. “The digital identity is the only way for us to keep the trust going,” Tal concluded. Whether companies, governments, and society can achieve the careful balance of safety, privacy, and security remains the next challenge.

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[Preview: The Painful “Necessity” of Digital Identity]

I’ve written extensively about Europe and its tech sector for many years.

For some, it seems slow, stagnant, and tied up in regulatory bureaucracy. For others, it is a champion in responsible data protection and privacy laws that spread across the world.

Either way, the continent should not be disregarded when we discuss tech ecosystems and innovation coming from startups and large corporations.

The bloc has undergone a bit of scrutiny since Mario Draghi delivered his report on European competitiveness to the European Commission in September 2024. Its diagnosis showed slowing productivity, demographic challenges, rising energy costs, and increased global competition as the forces putting pressure on Europe's long-term prosperity.

Europe's productivity gap with the United States was being driven, in significant part, by a failure to adopt technology at scale. What followed was a significant reorientation of sovereign wealth toward tech investment: governments funneling capital into venture funds, seed programs, and national innovation vehicles, all aimed at catching up.

“Europe realized that the US is taking care of the US, especially today,” said Eran Westman, Managing Partner of Planven, a Zurich-based fund with roughly $300 million in assets under management. “And if Europe wants to have its own independence on the technology, it can also be, of course, in defense and other aspects, Europe should take care of Europe.”

Westman joined Planven in 2024 to lead its Israeli expansion. His vantage point sits at the intersection of European capital and Israeli innovation, which he sees can offer a structural opening that Israeli companies are uniquely positioned to fill. Companies born out of Startup Nation can bring something to Europe's sovereign capital push: decades of accumulated instinct for scaling across borders and for navigating unfamiliar regulatory regimes.

Israel’s Numbers in Europe

Many companies in Israel immediately consider expansion and look toward the US. And the perception of European-Israeli relations in tech tends to be shaped by political noise. The reality, documented in hard data, tells a different story.

For example, a report published in late 2025 by Planven, EIT Hub Israel, and KPMG mapped the footprint of Israeli technology companies across Europe and found not retreat but deepening integration. As I wrote for JNS at the time, more than 1,600 Israeli tech companies now employ over 30,000 people across Europe, with a 4.8% annual growth rate over the past three years.

The report highlights strong alignment between Israeli strengths in AI, cybersecurity, healthtech, defense, and climate tech and EU strategic priorities for 2024–2029, particularly in security, sustainability, and digital infrastructure. That alignment matches the sectors that Europe has identified as the most urgent need for strategic autonomy and where Israeli companies have the deepest bench.

In September 2025, Planven exited Nozomi Networks — an Italian-Swiss company protecting operational technology infrastructure across power grids and railways — in a billion-dollar all-cash sale to Mitsubishi Electric. The company had been profitable for approximately 18 months before the deal closed.

Its exit demonstrates that a company built at the intersection of European engineering and Israeli-style security expertise can produce a world-class outcome, and it can also show the EU's emerging defensetech conversation: Protecting critical infrastructure is not a peripheral tech problem. It sits directly inside the strategic autonomy agenda that the Draghi Report put at the center of European competitiveness policy.

The data shows that European-Israeli business collaboration has continued to grow through the current conflict period — a signal of the difference between political weather and structural economic logic. “The continent may protest Israel politically, but economically, it is building a future that relies on Israeli innovation,” I wrote last year.

The Antisemitism Tension

The same period that produced these numbers also saw documented rises in antisemitism across European cities, EU-level noises about sanctions on Israel during the latter stages of the Gaza conflict, and a political climate that has, at various points, made the Israeli flag a contentious symbol in European public spaces.

Westman is careful on this point, and it is worth taking his care seriously. He speaks from a specific vantage point: the deal table, the LP meeting, the board room — and he is explicit about what he can and cannot claim. “I have not met with any antisemitic comment, a question, or approach during the time that I’ve been... I speak with the ecosystem, other VCs, investors, LPs, companies, partners, all the ecosystem.”

He notes that he does encounter concern about operational continuity for Israeli companies during wartime. Questions about whether engineers can still reach the office. About what happens to a company when its CEO is called up for reserve duty. These are legitimate business anxieties, not antisemitic ones.

“There were some noises in the EU in the later part of the Gaza war in August, September of last year,” he acknowledged. “Maybe there will be some sanctions from the EU on Israel. So these were some issues that were maybe coming — but again, nothing that I can directly connect to any antisemitic comment.”

Looking Ahead

Westman is optimistic about the decade ahead. The deal flow he reviews weekly has improved materially in quality over his two years at Planven. European founders are arriving at first meetings with more global ambition than he had seen before. The capital environment, for all its structural gaps, is maturing.

But the honest version of the story holds the tension rather than resolving it. European sovereign capital is being deployed by the same governments whose foreign policy toward Israel remains complicated and variable. The business relationships have proven durable so far. Whether that durability persists as the geopolitical environment continues to shift is the question nobody in Westman’s world can fully answer.

What the numbers show, and what his experience confirms, is that the economic logic of the Israel-Europe tech relationship is stronger than the political conversations around it. Europe needs what Israel has built. And Israeli companies, for all the complexity of the European market, cannot afford to ignore a customer base of 450 million people sitting a few hours’ flight away.

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The joint US-Israeli operation against Iran — the most significant military collaboration between the two countries in modern history — validated a thesis that Protego Ventures had been building since October 7, 2023.

The fund, one of the first in Israel to explicitly target defensetech, had already placed bets on the idea that the US-Israel alliance was evolving from a diplomatic relationship into something more structural. Founders Lital Leshem and Lee Moser imagined a technology pipeline backed by private capital, battlefield data, and a generation of founders who had seen war up close.

“When an Israeli company wants to sell today to the DoD, we have the mutual understanding that we stand for the same values, and we fight together,” Moser said. A former Israeli diplomat and chief of staff to Ambassador Michael Oren, she spent years in the corridors of Congress lobbying for Israeli defense systems.

The Data Point Advantage

“Most of the entrepreneurs in Israel are graduates of elite information units… Add to that the revolution of AI and add to that what the world sees right now,” she added. “You got yourself a superpower. Superpower with data from the battlefield.”

Israel’s defensetech sector has long been seen as a natural evolution of cybersecurity, which in turn was born out of Israel’s need to create robust security measures upon its establishment in 1948. The US-Israel alliance has been strong since its inception.

But what makes this defense relationship different in 2026 isn’t just the joint operations. It’s what Moser calls Israel’s data advantage: 80 years of continuous conflict compressed into a body of operational intelligence that no other country can replicate. “Unfortunately, we’ve [needed] to fight for 80 years,” she said. “And this data can be translated to save people's lives in all aspects.”

Founders in today’s Startup Nation era who build on that data are a different breed from the fintech and cybersecurity entrepreneurs who came before them. They’re coming out of active reserve duty, returning from the battlefield with firsthand knowledge of what the technology gaps actually are. “They know exactly what the pain is,” added Leshem, who was herself at the IDF Southern Command’s Central War Room by 9 am on October 7. “They’re coming with their own ideas and a lot of motivation to grow it and implement it. And it’s actually happening.”

America First, India Next

The loop that battlefield experience feeds into startup formation, which then feeds into defense procurement, is something I have witnessed over the last few years. And it is accelerating beyond the US–Israel axis. From India to Europe, governments and institutions are increasingly looking to plug into Israeli defense innovation, whether through partnerships, procurement, or investment.

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One of Protego’s portfolio companies, Xtend, recently closed an $11 million contract in India for its drone-integrated robotics system. The US remains the primary go-to-market, but the alliance architecture Protego is betting on extends globally.

The Information War

One final aspect of our conversation focused on the changing battlefield and how the country’s fights have migrated from land and sea to online. Moser was unambiguous about what she sees as an equally urgent front: the information war, waged through AI-generated content, foreign influence operations, and weaponized social media ecosystems.

“What was real? What was fake? I think what we see today is like the first AI war,” she said. The conflict with Iran has only sharpened that point: deepfake propaganda, coordinated disinformation, and AI-generated imagery have become standard tools of modern conflict, running parallel to every kinetic operation.

Protego is actively backing founders working in what Leshem calls the “cognitive war” space, treating information integrity as a defense problem with the same urgency as drone protection or force projection. “Everything that has to do with the cognitive war or the information war, that is something that we’re seeing a lot,” Leshem said. “A lot of entrepreneurs are going in this direction.”

[5-minute preview: Israel's defense sector is creating global alliances]

Every time Anthropic drops a product update on X, a startup somewhere dies.

That’s the sentiment across the startup world right now. Claude can do new things each week that were once considered core products of companies, not just simple feature additions. Each week, founders watch their whole business become a footnote, and the post-mortems begin.

I recently spoke to Eyal Fisher, co-founder and CPO of Sweet Security, and former head of the cyber operations center in IDF Unit 8200, about this. Even though the concerns are real, the lesson is being misread.

When a major AI platform ships a capability that overlaps with an existing startup’s product, the instinct is to panic. Fisher pushes back on the reaction. “I think that in most cases, it’s a little bit too early,” he says. “If that capability will miss important things, really bad things can happen. So I’m not sure that everybody’s running to replace all the security tools with AI — yet this is a trend. This is where it’s going.”

After more than two decades in Israeli military cyber operations, he co-founded Sweet Security in 2022 alongside former IDF CISO Dror Kashti and Unit 81 veteran Orel Ben Ishay. The company has since raised $120 million, including a $75 million Series B led by Evolution Equity Partners, and grown its enterprise customer base tenfold. So when Fisher talks about what it takes to survive, he’s speaking from experience.

The Core Capability Trap

According to Fisher, founders who treat these announcements as an obituary are making a strategic error.

The deeper problem, he argues, is that founders are building companies around capabilities, rather than ecosystems. “Let’s say that you’re trying to invent some kind of system that can summarize calls,” he tells me. “That capability is a waste of time to develop today because AI is doing it like that.”

Companies that once developed transcription and call summarization as their core product a decade ago do face a reckoning: not because they ‘failed’, but because the ground shifted underneath them.

For example, I use a media platform to record my podcasts, and an instant transcription is available as an extra feature. I no longer need an entirely new service because it’s part of the suite I operate in. It’s great as a user, but Fisher said that founders need to consider this everywhere and build the moat around the capability, not inside it. “You need to make sure that it’s going to be easy to use, interact with everything else that you have in your company, have a full ecosystem.”

This pattern is already playing out across software: from media tools to sales platforms to developer products. In other words, the feature will be commoditized. But the platform and its integrations are harder to replicate.

What Every New Founder Should Know

Fisher is a founder with 25 years of experience behind him, as opposed to many founders who are only 25 years in age. His advice to young entrepreneurs starting today urges them to pursue things that AI cannot disrupt today.

“Go after things that cannot be disrupted today by AI,” he said. “You don’t want to build something that someone else can do exactly the same in like half a year… If you think that you can do something in half a year, someone else can do it in half a year as well.” But then came the truth underneath that advice: “At the end, AI will replace everything.”

For many users, including myself, features like transcription are now embedded into existing tools I use for video recording and editing - I’m not looking for a solo tool anymore. So, his advice is particularly relevant for founders thinking about what to build next.

If replacement is as inevitable as he says, then the question becomes how much time you have before it happens - and what you build around your core in the meantime. That way, you can avoid the dreaded update from a large AI giant that risks putting you out of business.

Sweet Security’s Own Answer

Fisher applies this logic to his own company. Sweet Security’s runtime sensor — the technical foundation of its cloud security platform — is written in Rust, a low-level programming language that makes it unusually difficult to replicate. “There is almost no other company out there that wrote such a sensor in that programming language,” Fisher says. “It’s very hard. It’s very complicated.”

But even he doesn’t treat that as a permanent shield. “Eventually, maybe it’s going to happen. Until that happens, what we are doing is building the ecosystem around it.”

The Bottom Line

For founders worried every time a major AI company posts on X, Fisher’s parting advice cuts through the noise: “Patience. One day you are here, one day you are here. You need patience and resilience. It’s a hard journey.”

The founders who survive the AI update cycle will be the ones who built the deepest and had the discipline to keep building when everyone else was busy panicking.

[5-minute preview: AI's Impact on Startups: Avoiding "The Core Capability Trap"]

When fans walk into Wembley Stadium or Wimbledon, they see the show - but what they don’t see is everything underneath it: An ‘invisible’ workforce working hard in unison, powering the global experience economy to make sure the event is running seamlessly.

“In order to make an experience… it can be thousands of workers,” Omri Dekalo explained.

The hidden infrastructure behind modern events is a fragmented labor force made up of temporary workers, contractors, and staffing agencies. It spans industries (from sports and concerts to catering, security, and hospitality) and often operates in clear view but with near-total invisibility.

“No one feels it, no one sees it,” Dekalo said. “It just works and it creates amazing moments.” But beneath that seamless experience is a system that, until recently, was anything but that.

Dekalo is the co-founder and CEO of Ubeya, an Israeli B2B SaaS platform positioning itself as an “operating system” for this invisible workforce. With more than 250,000 workers on the platform and clients including Wembley, Wimbledon, and the UEFA Champions League Final, Ubeya sits at the intersection of the gig economy, HR tech, and the multibillion-dollar live events industry.

It’s a space that, until recently, many will recognize as still being managed largely through WhatsApp groups or spreadsheets. Workers would check in via pen and paper, or be reassigned mid-shift with a handwritten note.

The scale of what happens behind the scenes at a major event is something most attendees never consider. A Taylor Swift concert is not a Champions League final - even if they sometimes use the same venue. Each event requires a completely different configuration of workers like caterers, cleaners, security personnel, stagehands, or bar staff.

Many of these workers don’t even work directly for the venue itself.

At Wembley, as at most major stadiums globally, a significant portion of the workforce is sourced through third-party agencies. Before platforms like Ubeya, coordinating all of them would take up space, time, and energy for all involved.

“It’s moments that people like remember for their whole life,” he said, discussing the excitement of attending a live event. “And in order to make it happen, there are a lot of stakeholders… that are doing a lot of work there. It can be thousands of workers that are coming early in the morning.”

Ubeya's platform streamlines that complexity into a single system. Managers can check worker availability, book and approve staff, track time and attendance, and run payroll all from one place.

The platform also tracks which individual is deployed in which area, how much revenue they generated, how well they performed, and where they should be redeployed mid-event. "Suddenly this whole connection between the tech and the real life — that's the magic," Dekalo explained.

An Event Operating System for Post-Pandemic Performances

We are six years since the start of Covid-19, and while there was a dip in live performances for most of that time, the industry is experiencing a surge.

There are currently 500 stadiums under construction in the United States alone, part of a broader shift toward multipurpose venues that can host a football game one weekend and a global concert tour the next. Wembley, for example, now sits at the center of an entire neighborhood: hotels, malls, and restaurants are all built around the stadium as the anchor experience. The workforce required to run that ecosystem is only growing.

Ubeya has scaled roughly ten times in revenue over the past two and a half years, employs more than 50 people, and is operationally breakeven on $13.5 million raised to date, with enough cash for a run rate of 40 years.

“That’s a lot of Taylor Swift,” I said. “That’s a lot of heartbreak.”

[5-minute preview: The “invisible workers” behind your Taylor Swift concerts]

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When Gal Elbaz decided to hack Instagram, he didn’t need much convincing.

“We wanted to hack Instagram because they’re Instagram, right? We don’t need a lot of motivation,” the co-founder and CTO of Oligo Security told me in a recent interview. What followed was a lesson in how modern cybersecurity actually works - not through confrontations with shadowy figures, but through the quiet exploitation of a single overlooked library buried deep inside one of the world’s most downloaded applications.

I’ve spoken to many cybersecurity companies over the years, each of which addresses safety and protection in different ways. Usually, I hear about how they try to prevent attacks. This was the first time I had heard from a white-hat hacker.

For those unfamiliar, a white hat hacker (or ethical hacker) is a cybersecurity professional authorized to identify security vulnerabilities in systems, software, or networks. By using ethical methods like penetration testing and scanning, they strengthen security before malicious hackers can exploit weaknesses.

Today, the company’s mission is to redefine how application security works in modern software environments. This is achieved by focusing on what’s actually happening at runtime, rather than just scanning code or assessing theoretical risks. Its Application Detection and Response platform now protects Fortune 500 companies and recently secured a partnership with AWS. The company was founded in 2023 and has raised approximately $80 million to date, backed by Lightspeed Venture Partners, Ballistic Ventures, and TLV Partners, as well as security veterans like Shlomo Kramer, Adi Sharabani, and Eyal Manor.

Elbaz and his team didn’t brute-force their way into Instagram. They found a vulnerability in an open-source image compression library built by Mozilla Firefox — the kind of invisible, unglamorous code that powers millions of apps without anyone realizing. The result was total access.

“The moment that we can literally execute code, you can take over the flow of the application, we control the application,” he said. “We are Instagram - and we have everything that we want over your phone. We have every permission that exists. We have access to the camera, to the gallery, to the memory, to your contacts, to everything.”

One thing that adds intrigue to my conversation with Elbaz is the way he thinks about what hacking actually is. For him, breaking into a machine and reading a person operate on the same fundamental logic. “Hacking is the art of controlling someone else’s mind, so to speak,” he explains. “Hacking is the manipulation of human beings who are behind the software. Phishing is the thing that brings them together because you trick people with technology.”

He carries that philosophy into how he runs his company. “As a founder, you sell to employees, to customers, to investors, to everything around you — you sell, sell, sell, sell. And people don’t get it, that it’s very similar to talking to a machine. A very random machine. But it is a machine.”

That mindset was forged early. Elbaz grew up in elite IDF intelligence units alongside his co-founders, CEO Nadav Czerninski and CPO Avshalom Hilu — childhood friends whose parents were themselves childhood friends — before going on to Check Point Software, where he spent years hacking the world’s biggest applications and presenting findings at black hat conferences and DEF CON.

The Instagram hack wasn’t just a headline. It was the founding insight behind Oligo. What struck Elbaz was that the entire security industry was oriented around catching attackers after they’d already won. He wanted to catch them at the moment of entry. “We thought, what about detecting the act of the breach? What if you can detect the root cause? What if you can catch the hacker when they’re trying to get in? Because after they got in, you lost.”

The urgency behind that mission has only intensified. The same open-source vulnerability problem that Elbaz exploited manually against Instagram can now be discovered and weaponized by AI agents in a fraction of the time. “It used to take 30 days to weaponize a zero-day by the most sophisticated attackers. Today it’s minus one. Agents can actually find zero days and exploit them so they can do the zero to one by themselves.” The defender’s margin for error, already razor-thin, is disappearing entirely.

When I asked Elbaz which side of that equation feels more natural to him, the hacker or defender, he doesn’t hesitate. “Definitely the hacking one, a lot more fun. When it’s hacking, it’s pretty easy, right? It’s about yes or no, could I hack you or not? The proof is in the pudding.”

The man who spent his career finding holes in systems — digital and human alike — is now in the business of closing them.

[5-minute preview: Hacking Instagram, a white hat perspective]

When Bria AI CEO Yair Adato talks about AI, he sounds more like an economist watching a familiar crisis unfold in slow motion, as opposed to the typical startup founder I have spoken to over the years.

“People think about this revolution as a technology revolution,” he said. “It has nothing to do with technology. It’s all about the economy and society. The technology is just an enabler.”

Bria AI is an Israeli company building licensed generative image infrastructure for enterprise clients. It ensures that AI-generated images and videos are controlled, accountable, and compliant by working with stock image providers like Getty and others. These, in turn, train its foundation models while also ensuring royalties and fair compensation for creators.

It has raised more than $66 million from VCs such as Red Dot Capital, Entrée Capital, IN Venture, and others.

When speaking with Adato, it was clear that he believes the product exists because a major obstacle to AI adoption isn’t just about model quality. It is about ownership, provenance, and legal usability.

One consideration in all of this is the concentration of some of the leading players in the AI space. As a handful of American hyperscalers like Google, Microsoft, and OpenAI race to control the AI stack, Adato sees the distribution of benefits becoming dangerously narrow. “It’s a question of how the resources will split between current players, future players, and society,” he said. “There is a voice that wants to have all of the resources, all of the benefits of AI, for a few big companies. I think there will be a second voice that tries to split it more equally — because you don’t want to have three companies that basically control the world.”

The idea of companies having a central control in the direction of AI-generated content can be considered a geopolitical problem, not just a market one. We reference similar ideological fault lines that produced competing visions of the internet: Silicon Valley’s open innovation, Europe’s regulatory model, and China’s state control are now reasserting themselves around AI infrastructure.

The outcome of that contest, he argues, will matter more than any individual model breakthrough.

AI’s Spotify Moment

The closest parallel may be the music industry's own reckoning a decade ago. The internet created a data distribution crisis that the music industry fought legally before Spotify resolved it economically — through per-use licensing, attribution architecture, and revenue sharing.

Generative AI is producing a data generation crisis that demands the same kind of structural solution. “Spotify said something really smart,” he explained. “Instead of buying the album, we will let you use it per use, per listening. And every time you hear a song, there is a mechanism behind the scenes to pay the artist.”

Bria AI is building that mechanism for visual artificial intelligence: an attribution engine that tracks which training data influenced a generated image and routes revenue back to the original creators. But Adato is candid about the gap between the vision and the current reality. He acknowledged Spotify’s failure in that the studios got rich, but the artists mostly didn’t. “We try to do it differently… but in many cases, the artist is simply not there.”

The stakes go beyond fairness to individual creators. If synthetic media can replicate everything for free, the incentive to create erodes entirely. “The fact that we can monetize intellectual property is mandatory to continue to develop the economy and society,” he says. “If you cancel the concept of copyright, there’s no reason to create games and movies. There’s no reason to create a brand because it has no value anymore.”

Regulation, he believes, is coming to answer the question the market has so far avoided: Who gets to benefit, and on what terms? “Something will happen,” he says. “I don’t know when, I don’t know how. But something will happen.”

The revolution, it turns out, will not be televised - it will be generated. But whether the economy forming around it is a fair one remains entirely unresolved.

Watch a 5-min preview:

“AI regulation: A geopolitical game between USA, EU, and China”

Everyone is talking about AI. And Generative AI adoption, especially, has practically become a corporate mandate - everywhere you look, it is being deployed.

Across industries, executives are urging teams to integrate AI into their workflows. Engineers want access to AI coding assistants, and consumers are constantly being introduced to new AI products whether they want them or not.

But amid the rush to deploy new tools, many organizations are overlooking a simple question. Is it doing its job and making anything any better?

“We are helping engineering leadership to govern AI and adopt it,” said Liad Elidan, co-founder and CEO of Milestone. The platform provides engineering leadership with something deceptively simple: an honest account of what AI is actually doing inside their organization. Not what the AI vendors tell them it’s doing — what’s really happening, measured against business outcomes that matter.

Elidan described it as a situation where the whole system is pushing forward at once: “The world’s adopting AI. Every person is using AI, either in their personal life or in their professional life.” But the result is that many organizations deploy AI tools before they fully understand what those tools are actually doing. And the metrics provided by those tools do not necessarily answer the questions executives actually care about.

This is giving rise to an emerging category of technology: systems designed specifically to measure the interaction between humans and AI tools inside enterprise environments. Milestone sits at the center of that category — sitting above the vendors, correlating usage data with actual engineering outcomes like code quality, review times, and delivery speed.

Elidan described this challenge as a shift in management thinking. “Now you add another animal into the play, which is AI itself.” Looking further ahead, he is optimistic about where this leads — for engineers willing to adapt. The profession isn’t contracting, he argues. It’s mutating into something far more powerful.

“It’s very controversial,” he said, “but you can be much more independent now. And that is amazing.” The engineer who learns to work with AI tools effectively, who treats adaptability as a core professional skill rather than an occasional inconvenience, is not being replaced. They are being amplified.

Five years from now, Elidan predicts the best engineers won’t be defined by what they can write, but by what they can direct. “I expect that engineer to be almost a Superman engineer compared to the engineer of today,” he said. “He’ll have a hundred or more agents under his belt — agents that he can run, configure, and push forward.”

The future of software development, in other words, may be defined by the ability to manage how humans and AI work together and the wisdom to actually measure whether it’s going well.

As tensions rise between Iran and Israel, one narrow stretch of water is once again holding the global economy hostage: the Strait of Hormuz.

Nearly a third of the world’s seaborne oil passes through the corridor each day. This week alone, Iran deployed sea mines in the channel - and GPS spoofing, which is the manipulation of satellite navigation signals, continues to disrupt ships moving through the region.

For Yarden Gross, co-founder and CEO of maritime technology company Orca AI, this is exactly the kind of moment his industry has feared. “90% of the goods today in the world, $5 trillion a year, is moving through the seas,” he said. “When you see the disruptions happening, it’s usually when you see major events.”

Those events are now arriving in quick succession. The corridor is narrow, congested, and the world is watching it get weaponised. These tensions are creating a distinct kind of disruption, sending oil prices climbing and forcing shipping companies to navigate increasingly dangerous waters.

This is where a company like Orca AI can help. It has built a platform that collects data from onboard cameras and sensors, analyzes it in real time, and shares it across a network of ships. The company now has over 100 million nautical miles of data, compounding as more vessels come online.

In a GPS-denied environment, the system operates independently of all standard navigation instruments, using thermal cameras and computer vision to detect objects — including small boats, and now, sea mines — that would otherwise be invisible at night.

When spoofing is detected on one ship, alerts are shared with others approaching the same area. “They can actually take preventive actions,” says Gross. “They can be aware that reaching an area or a specific location, they’re going to have GPS spoofing there.”

For decades, maritime technology lagged far behind other industries. The reason, he argued, was structural: without reliable internet connectivity at sea, updating software across a fleet required physically boarding each vessel with a hard drive. The arrival of low-orbit satellite internet in 2023 changed everything. “I saw like a massive change,” says Gross. “It’s so massive changing the perspective of the shipping companies, how they look at technology.”

The longer-term vision goes further than smarter ships with human crews. Gross anticipates a shift in how the industry thinks about high-risk corridors — from large, expensive vessels requiring protection, to smaller autonomous craft designed for agility and expendability. “Imagine if you had a small swarm of smaller vessels that can actually take fuel and gas out of there,” he said. “If one is going to get hit, fine. It’s going to be a very small quantity and it’s not going to be like a hit on a major tanker.”

The Strait of Hormuz is narrow, but its implications are vast. What is playing out there right now is not just a regional conflict story, or an energy markets story. It is a story about whether the technology underpinning global trade can keep pace with the forces trying to disrupt it.

Those who follow my show know that I speak to many cybersecurity founders.

While the explosion of AI has certainly made the sector a fascinating place for technical discussions, there are also many areas where we can explore the human side of cybersecurity.

Take security operations centers (SOCs), for example. These SOCs operate within large organizations that rely on dozens of monitoring tools to detect suspicious activity across networks, devices, and identity systems. Each system generates alerts when something unusual occurs.

In theory, those alerts help security teams identify attacks early. But in practice, they can overwhelm the people responsible for responding.

“Over time, this became overwhelming,” said Guy Teverovsky, co-founder and CTO of Semperis. “We have been hearing from multiple customers that they are drowning under the amount of different alerts from different solutions.”

Organizations are now collecting so much security data that analysts often struggle to determine which alerts represent genuine threats and which are harmless anomalies. The change in new age cybersecurity means that challenges are not only technical, but they can have a lasting impact on the stress levels of industry workers.

Teverovsky said that when security teams face thousands of alerts every day, their most valuable resource becomes the ability to prioritize. Missing the one critical signal buried in a sea of warnings can allow attackers to escalate privileges, move through networks, or disrupt key infrastructure.

“Prioritization becomes critical,” he explained. “You have to surface the most critical findings… otherwise you’re in a big problem.”

That pressure has pushed many cybersecurity companies to rethink how alerts are generated and delivered. Instead of flooding analysts with raw signals, modern systems increasingly attempt to contextualize threats, highlight the most dangerous activity, and recommend specific remediation steps.

Semperis provides threat prevention, detection, response, and recovery for Active Directory, the Microsoft directory service for connecting users with network resources. Customers who use its services get layered defense across the entire lifecycle of an AD-based attack, both on-prem and in the cloud.

The company serves over 1,000 organizations, including government agencies and a significant portion of the largest U.S. companies. It has raised a total of $369.5 million.

AI plays a role in helping teams process all this new information by helping security platforms analyze patterns across massive volumes of data. But even as automation improves, the human factor remains central to cyber defense.

Decision-making during a live security incident still depends on experienced engineers, analysts, and responders who must interpret signals, assess risk, and act quickly under pressure.

So in that sense, cybersecurity today is about enabling people to make the right decisions in an environment defined by constant digital noise.

The airports may be closed, but that isn’t stopping the Tel Aviv Stock Exchange (TASE) from soaring.

As Israel navigates renewed conflict with Iran, the country’s stock exchange did something surprising. Instead of tanking, it did the opposite. The TA-125 Index climbed to record highs of around 4,200 points, which represents a 66% increase compared to this time last year. At the same time, the Israeli shekel strengthened against the U.S. dollar.

That isn’t to say the conflict hasn’t caused disruption and anxiety across the country, but it does demonstrate that there is confidence in Israel’s ability to bounce back from adversity.

"The stock market is a predictor of what the belief or expectation is about what's going to happen in the future, not what's happened in the past," said Ezra Gardner, Partner at Varana Capital. “The stock market in Israel is actually doing the right thing, because the signaling is that Israel is going to boom when this is over. Israel is going to be the winner, and Israel is going to deliver even more on the things that they’ve delivered on in the past, in innovation and helping the world.”

Gardner was supposed to arrive in Israel alongside South Valley CEO Travis Vap, and this episode was supposed to take place in a studio. But when their flight was cancelled hours before take off, we decided to continue our conversation as planned, this time virtually.

It was already in the calendar, so it made sense to everyone. According to both men, not a single meeting with Israeli companies or officials was cancelled.

“To me, these people are in a geopolitical conflict that I can’t imagine because I’m not there and I’m not dealing with it,” said Vap. “But the fact that we’re on calls, on Zoom, on Teams, and it is...4pm, 6pm, 8pm, 10pm Israeli time. It’s just a little overwhelming… it just reinforces what good people there are, people that are focusing on much bigger things than what's happening right now on the ground.”

The case for the TASE’s trajectory may lie in this response to adversity that has become all too familiar since the early days of the pandemic. Gardner and Vap had been to Israel before (Vap only once) and were struck by the entrepreneurial culture embodied among its people. Despite the country’s challenges and an army mobilization rate that at one time reached 15% of the tech workforce, business rarely slowed.

In fact, for Gardner’s deeptech and hardware portfolio companies — the kind involved in drones, semiconductors, and defense-adjacent infrastructure — closer to 50% of staff were called up. “The productivity actually went up. People worked 10 times harder when half of the staff was gone.”

Gardner spent the first half of his career in the public markets. His experience spans from J.P. Morgan to Michael Dell’s family office, MSD Capital, and running the US equities desk at UBS at an unusually young age. So, when he says the TASE is doing “the right thing,” it carries weight. He argues that the market isn’t ignoring the war - it’s pricing in what comes after it.

You can catch our entire conversation about the market’s response to the war in the video above.