How do you scale high-performing video ads when creators are expensive, slow to hire, and hard to test at volume?

Today, we look at ArcAds, a startup using AI actors to generate realistic, UGC-style video ads in minutes instead of weeks. By lowering the cost and friction of testing creative, ArcAds is reshaping how marketers approach performance advertising. It has attracted $16 million in recent seed funding.

Corporate legal teams face rising costs and slow turnaround times, driven by hourly billing models that reward inefficiency. Today, we take a look at Eudia, which is trying to address these issues by combining AI systems with an in-house legal practice. Enabled by regulatory changes in Arizona, Eudia offers a case study in how AI and new business structures may reshape high-volume legal work. 

What if the real bottleneck in AI isn’t the model, but the data itself? In this episode, we’re talking about Snorkel AI, a Stanford spinout helping enterprises turn expert knowledge into high-quality training and evaluation data, far faster than manual methods. The company recently raised $100 million in Series D funding at a $1.3 billion valuation. We’ll explore how Snorkel’s approach works, its shift toward AI evaluation, and what that means for the next wave of enterprise AI.

Today, we’re turning to the networking side of AI - the part that keeps all those GPUs talking to each other. Nexthop AI recently came out of stealth with $110 million in funding at a $500 million valuation. The company rethinking how massive AI clusters are connected - not just building faster switches, but co-developing custom network hardware and software with hyperscalers. We’ll look at how Nexthop’s approach could reshape the AI infrastructure stack and why investors are betting big on it.

Today, we’re talking about Reflection AI — the new startup everyone’s watching. Fresh with a $2 billion raise at an $8 billion valuation, it’s founded by ex-DeepMind researchers behind AlphaGo and Gemini. Their goal? To build open, frontier-scale intelligence that rivals the closed labs like OpenAI and Anthropic. We’ll dig into their technology and discuss the future of open-weight models.

Today, we’re looking at Hippocratic AI, a startup building generative AI agents for patient-facing, non-diagnostic healthcare tasks. From post-discharge check-ins to chronic care management, Hippocratic’s goal is to ease staff shortages and create what it calls “healthcare abundance.” The company recently raised a $141 million Series B at a $1.6 billion valuation, and we’ll explore how its safety-focused approach and deep clinician involvement could reshape the way patients and providers experience care.

Today, we’re looking at Fyxer AI, a startup building AI executive assistants for email and meetings. Fyxer plugs directly into Gmail and Outlook to sort messages, draft replies, and even handle scheduling and notes — all to save users an hour a day. The company has grown ARR from $1 million to $17 million in just eight months, and we’ll explore how its rapid rise is reshaping the future of workplace productivity.

Today’s episode is a little different — we’re talking about defense AI. Shield AI builds autonomous systems designed to protect soldiers and civilians by enabling aircraft and drones to operate without GPS or communication links. We’ll explore the company’s origin story, its core software platform HiveMind, and how its AI-powered drones are changing modern warfare. We’ll also look at its $5.3 billion valuation, key defense partnerships, and the ethical questions around AI on the battlefield.

Today, we’re looking at Groq, a startup aiming to redefine AI inference speed. Groq recently raised $750 million, bringing its valuation to $6.9 billion. We’ll explore Groq’s founding story, its specialized LPU chip, and how its focus on real-time AI performance positions it against Nvidia and other giants in the GPU cloud market.

Today, we’re discussing Decagon and how they’re rethinking customer support with human-like AI agents. We’ll look at how their generative AI engine differs from traditional chatbots, the impact of integrations like Stripe, and what it means for enterprises facing rising support costs. Plus, we’ll explore where this technology might go next, from personalization to new applications beyond customer service.

In this episode we explore the differences between U.S. and Chinese venture capital, from software-driven models to hardware and supply chain innovation. It highlights how biases shape investment, the role of trust networks, and why overcapacity can fuel new opportunities.

In this episode, we talk about CalAI, a fast-growing nutrition app that tracks daily calories through photos. Its founders are teenagers. While some online reports speculate its ARR could be over $30 million, we’ll focus on how the app works and its challenges.

Happy New Year! Welcome to our first episode of the year.

As we kick off a new year, is the future of AI about who trains the biggest models, or who can run them most efficiently?

Let's take a look at Together AI, a company focused on making open-source models fast, affordable, and usable at scale. By pairing open models with deep systems optimization and flexible deployment, Together AI is arguing that the next phase of AI competition is really about infrastructure.

Today, we’re discussing Sana Labs and their approach to workflow automation. We’ll explore how their AI-driven solutions set them apart in the market, particularly when compared to companies like Asana. Plus, we'll take a look at some of the everyday tasks that AI can automate to boost productivity.

Doctors today spend nearly two hours on administrative work for every hour with patients, a major driver of burnout and inefficiency in healthcare. Nabla is tackling this problem with its AI assistant, already used by over 85,000 clinicians
 across 130 organizations. The company recently raised $70 million in Series C funding, bringing its total to $120 million, to expand from reducing documentation time into building agentic AI that can also support coding, launch orders, and integrate more deeply into clinical workflows.

Today we’re looking at Crescendo AI, a company that hit nearly $100 million in ARR in just 15 months. Crescendo’s approach blends automation with human expertise to create a more responsive, scalable, and cost-effective support platform. We’ll talk about their rapid growth, the shortcomings of current business models in the space, and how they aim to fix them.

In this episode we’re talking about Gamma, the online tool for creating beautiful, interactive presentations and documents in minutes. We’ll explore how it started, how it works, how people are using it, and the challenges it’s overcome to get where it is today.

Midjourney just launched its first video model—and at nearly the same moment, found itself facing a major lawsuit from Disney and NBCUniversal. In this episode, we'll unpack how Midjourney reached this pivotal point and where it might be headed next. From its rapid rise as a leading AI image generator to the creative and legal challenges it now confronts, Midjourney’s story offers a glimpse into the broader future of generative AI.

Today, we’re looking at OpenArt.ai - a fast-growing platform making AI-generated art more accessible. We'll discuss the range of tools available and their use cases, explore how artists can train models to reflect their own unique styles, and see how OpenArt compares with other AI image and video generators.

fal.ai is a fast-growing AI infrastructure platform for media creation. Its focus is on generating images and videos using open-weight models running on its optimized inference engine. In this episode, we'll explore fal’s history, how the platform works, and how it compares with other AI infrastructure companies.

CHAI is a platform that lets anyone build and chat with custom AI characters. Founded by former quant traders, CHAI has reached $30 million in ARR with only 12 employees. We'll explore how it works, what makes it stand out among social AI apps, and where it might be heading next.

In this episode, we're talking about DevRev - a company building tools to help developers and customer support teams work better together. DevRev raised $100 million in a Series A round last year and reportedly has already reached $100 million in revenue. We'll discuss what exactly DevRev offers, how it streamlines product feedback and support, and its role in the expanding landscape of developer-focused platforms.

We've discussed CoreWeave before. Today, we're looking at another key player in the GPU cloud market: Lambda Labs. Lambda recently raised $480 million in a Series D round, with Nvidia among its investors. We'll explore Lambda's founding story, its evolution, and how it compares to others in the GPU cloud space.

As 2025 comes to a close, we’re ending the year with a slight shift. We’ve spent most of the year focused on AI applications and infrastructure - today, we’re looking at how AI is starting to change security.

This episode looks at how AI-driven automation is reshaping security operations, helping teams move faster with less manual work, and what that could mean as we head into 2026.

Figure AI is reportedly seeking to raise $1.5 billion at a $39.5 billion valuation - just three years after its founding. What's driving this surge of investor interest? What exactly has Figure built so far and what's unique about their approach? Who else is developing humanoid robots, and what's Figure’s vision for the future? Let’s find out.

Today we're talking about a very popular AI framework, LangChain - where it came from, what it actually does, and how it fits into the broader AI landscape. We'll unpack its main components, what the team behind it is trying to achieve, and also dive into its business model and some of the challenges they're facing.

In this episode, we’re taking a look at Clay, a startup building a Go-to-Market platform that just raised $40 million at a $1.25 billion valuation. We’ll cover what Clay is, how it works, where it provides value for sales and marketing teams, and some open questions around its revenue model.

Today we’re discussing Hebbia - an enterprise software startup that recently raised $130 million in Series B funding to help knowledge workers extract insights from unstructured data and get work done more efficiently. We’ll look at Hebbia’s origins, explore what’s broken in current enterprise search tools, and discuss how Hebbia approaches these problems differently. We’ll also compare it with other rising stars like Glean and Harvey.

Mercor, a startup that just raised $100 million in Series B funding at a valuation of $2 billion, is transforming the way companies find and hire talent through AI-driven screening. Already, Mercor has conducted over 100,000 AI interviews and vetted more than 300,000 candidates globally. In this episode, we'll take a look at how Mercor’s platform works, the technology behind it, its challenges, and what it signals about the future of work and global hiring.

In this episode, we’re talking about Windfall - an AI-driven data company helping organizations identify and engage high-value consumers. Windfall recently raised $65 million in Series B funding. We’ll discuss how it helps go-to-market teams, its core technology, key customers, and what sets Windfall apart in an increasingly crowded data landscape.

In this episode, we're looking at Sierra AI, a company building a conversational AI platform that helps businesses create AI agents for customer support and many other applications. Sierra recently raised $175 million, valuing the company at $4.5 billion. We'll talk about the founding team, their product and the technology behind it. We'll also discuss how companies are already using Sierra today, and its unique outcome-based pricing model.

In this episode we’re talking about Writer, a startup that provides a full-stack generative AI platform built specifically for enterprises. The company recently raised $200 million in a Series C funding round, at a pre-money valuation of $1.7 billion.

We’ll cover how Writer got started, explore its core products, take a peek under the hood at how the platform actually works, and discuss how enterprises are using writer.

Let’s jump in.

In this episode, we look at Harvey - the legal AI startup backed by over $500 million in funding and most recently valued at $3 billion. We cover its origins, underlying technology, go-to-market strategy, and compliance approach. We also discuss how AI is changing everyday legal workflows, and what lessons it can offer to other knowledge based industries.

In this episode, we’ll talk about Abridge—a healthcare startup building a generative AI platform for clinical conversations. Studies show that doctors spend, on average, more than two hours each day on administrative tasks. We’ll explore how Abridge got started, how it aims to solve this problem, and what its secret sauce might be. With a recent Series D funding round of $250 million, Abridge is now valued at $2.75 billion . If you've ever wondered how AI could actually reduce paperwork for doctors, this one's for you.

What would it take to challenge NVIDIA’s dominance in AI compute? Today, we’re looking at TensorWave, a startup betting big on an all-AMD cloud, a one-gigawatt infrastructure deal, and a fast, debt-fueled expansion. We’ll break down how this model could reshape competition in AI computing, and the risks that come with it.

MCP (Model Context Protocol) and A2A (Agent2Agent Protocol) are getting plenty of attention lately. But what exactly are these protocols, and what problems are they trying to solve? In this episode, we'll decode what MCP and A2A have in common, explore the use cases that could benefit from them, and highlight what sets them apart.

Video production has traditionally involved many tedious tasks - things like motion capture, rotoscoping, and precise camera tracking. These jobs typically require significant time, specialized teams, and complex setups. But now, AI-powered tools like Wonder Studio, Runway Act-One, and Runway V3 Alpha are making these tasks simpler, faster, and more accessible. In this episode, we’ll look at how these tools are already reshaping video production, and discuss what the future might hold as AI becomes an everyday part of the filmmaker's toolkit.

In this episode, we'll explore the journey of character.ai. Founded in 2021 by ex-Googlers Noam Shazeer and Daniel de Freitas, character.ai quickly grew into a popular AI chatbot platform, attracting tens of millions of active users and raising hundreds of millions in funding. Then, in August 2024, it struck a strategic deal with Google - almost an acquisition. What exactly happened? Let’s find out.

AI agents are a hot topic right now. We've talked about different aspects of agents before - like the operator, browser use, and deep research. In this episode, we're looking at a new agent that's getting a lot of attention: the "Super Agent" from Genspark. Genspark claims they've reached $10 million ARR in just 9 days. By my calculation, that's about $250K in revenue for those 9 days - not exactly "annual" recurring revenue (yet), but still impressive. So, what's special about Super Agent? What can it actually do, and how does it compare with other AI agents out there? Let's get into it.

CoreWeave is a cloud computing company focused on GPU infrastructure tailored for AI workloads, and it just went public recently. In this episode, we'll cover CoreWeave's history, discuss its competitive strengths and potential weaknesses, and compare it to traditional cloud providers. Can it stay ahead of the competition? Let's find out.

A hot new open-source project, browser-use (https://github.com/browser-use/browser-use), has just raised $17 million in seed funding. We've previously explored how LLMs interact with browsers, such as with OpenAI's Operator and Anthropic's Computer use. In today's episode, we'll take a closer look at browser-use, diving deep into how this tool can enable these capabilities, highlighting its strengths, exploring its limitations, and uncovering the exciting opportunities ahead.

High-quality labeled data is crucial for training successful AI models, but collecting it at scale has always been a major challenge. In this episode, we’ll decode the story of Scale AI, one of the standout companies helping businesses annotate their data. We’ll explore its origins, how it scaled to work with hundreds of thousands of human labelers, and the challenges it continues to face.

In this episode, we dive into Deep Research, an agentic AI system that harnesses LLMs to automatically search the web, gather relevant information, and synthesize comprehensive research reports. We'll explore how these systems work behind the scenes, key vendors in this space, and discuss practical applications and use cases.

Last year, cybersecurity firm Wiz turned down a $23 billion acquisition offer from Google. Now, it's on track to double its annual recurring revenue to $1 billion by 2025. In this episode, we'll explore the story behind Wiz's rapid growth, dive into the technology powering its products, and uncover the unique strategies that help Wiz stand out in the fiercely competitive cloud security market.

If you'd like to know more about Wiz, here are the references used for the research:
https://www.wiz.io/blog/how-wiz-code-was-built-with-developers-in-mind

https://www.youtube.com/watch?v=ueM8XxkUSFI&t=278s

https://www.wiz.io/blog/100m-arr-in-18-months-wiz-becomes-the-fastest-growing-software-company-ever

https://youtu.be/79WtXeacujU?list=TLGGD_x6QlEC7I8yODAyMjAyNQ

https://youtu.be/3YmRia4djP0?list=TLGGbrlrIFdhxWIyODAyMjAyNQ

https://www.youtube.com/watch?v=-HYA_lNCpiY&t=5s

https://www.youtube.com/watch?v=SHuKQTFmrdE

https://en.globes.co.il/en/article-wiz-reports-350m-revenue-in-2023-hiring-400-in-2024-1001469549

https://www.wsj.com/articles/cyber-startup-wiz-raises-1-billion-on-path-to-ipo-500f9145

https://techcrunch.com/2024/10/23/wiz-hopes-to-hit-1b-in-arr-in-2025-before-an-ipo-after-turning-down-googles-23b/

https://techcrunch.com/2023/02/27/cloud-security-startup-wiz-now-valued-at-10b-raises-300m/

https://techcrunch.com/2024/10/28/wiz-ceo-explains-why-he-turned-down-a-23-billion-deal/

ElevenLabs is a pioneering AI company specializing in natural-sounding speech synthesis software. Founded in 2022, it has grown rapidly, reaching $100 million ARR in just 2 years. More recently, Spotify just opened up the support for AI generated audiobooks (https://newsroom.spotify.com/2025-02-20/spotify-opens-up-support-for-elevenlabs-audiobook-content/).

In this episode, we discuss the technology behind realistic speech synthesis, their unique approach and business model.

If you want to know more about ElevenLabs or the technology, you can refer to the following materials used in the research:
- https://github.com/neonbjb/tortoise-tts
- https://elevenlabs.io/blog/tortoise-tts-v2
- https://assets.ctfassets.net/f1df9zr7wr1a/5iH4gCSx2AdDihfxd2Sj3/5a44f34d8ac9c002ad946adfce9cef68/elevenlabs.pdf
- https://research.contrary.com/company/elevenlabs

Nscale is a fast-growing infrastructure company focused on large-scale AI data centers. Fresh off a $433 million Series B that valued the company at $1.1 billion, nscale has announced a massive $14 billion data center deal with Microsoft. We’ll break down what nscale is building, why this partnership matters, and what it says about where AI infrastructure is headed.

Anthropic just published an interesting report on how people are using AI in the real world by analyzing millions of real conversions on their Claude.ai platform. In this episode, we'll discuss some of the key findings in the report, for example, who's using AI the most (hint: software developers) and how they are using it. 

If you'd like to read the full report, it is here:
  https://assets.anthropic.com/m/2e23255f1e84ca97/original/Economic_Tasks_AI_Paper.pdf

OpenAI recently introduced Operator (https://openai.com/index/introducing-operator/), an AI agent that can use its own browser to perform tasks for you. Anthropic has a similar product called computer use (https://www.anthropic.com/news/3-5-models-and-computer-use), and there are open source projects like browser-use (https://github.com/browser-use/browser-use). In this episode, we take a look at the technology behind the so-called Computer Using Agents (CUA), their use cases, limitations and the challenges ahead.

In this episode, we dive into DeepSeek, the hottest AI company making waves in the industry right now. We'll explore the company's origin story, discuss what's unique about its v3 and R1 models, and why DeepSeek is able to train these models at a fraction of the cost compared to traditional methods.

If you are interested in learning more about DeepSeek and its models, we've included some references to satisfy your curious mind:
- DeepSeek v3 Technical Report: https://arxiv.org/pdf/2412.19437
- DeepSeek R1: https://github.com/deepseek-ai/DeepSeek-R1
- SemiAnalysis' analysis: https://semianalysis.com/2025/01/31/deepseek-debates/
- Founder's interview: https://www.lesswrong.com/posts/two-interviews-with-the-founder-of-deepseek

In this episode, let's talk about Replicate, a company on a mission to make running AI models as simple as making an API call. We'll discuss its origins, the business model, its strong ties to the open source movement, and some potential challenges.