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Building AI Got Cheap. Building It Well Got Expensive | S3E1801 sept. 202600:45:32

Hedgineer's annualized AI bill has grown past $1M, which brought back up a long-running internal discussion at the company: how do you measure ROI on a token? Michael and Jhanvi work through both layers of the problem. The first is instilling good AI hygiene practices across the company — encouraging thoughtful model selection, session discipline, keeping irrelevant context out of the window to optimize on cost. The second is harder. Tag every session to the feature, product, or service it produced, and the company starts to look like a portfolio of assets, each with a cash flow you can discount, price, and reallocate capital against. Running a business through the lens of AI turns every operator into an asset manager.

The complication is that building a product has never been cheaper and building a good product has never been harder. Everyone can prototype now, so the constraint moved from execution to taste, and killing good ideas in favor of great ones grows more challenging. They also get into why an observability layer and a skill library are worth more together than either is alone, and why some AI products are immediately understood and then never used. 

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.

Audio available wherever you get your podcasts.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

Hedgineer.io


Can the Marketplace Be Worth More Than the AI Models? S3E1725 août 202600:38:00

Stripe just bought OpenRouter for over $7B. At first glance, a payments company acquiring a model proxy for that much money sounds strange, until you consider what Stripe sees. It watches spend across a very large customer base, and AI spend is rising at an exponential pace. When inference becomes something you shop for rather than something you're locked into, owning the venue where tokens get priced starts to look not just strategic, but immensely lucrative.

Underneath the deal is a question every company is now running live: does it make more sense to purchase AI inference through a router, or is sticking to a frontier model subscription still the right choice? The answer depends on how much of your work actually needs the best model available, and on whether you have the engineering capacity to build the tooling that makes a router usable in the first place. Michael and Jhanvi take opposite sides on how long premium reasoning stays worth the premium, which turns into the bigger question sitting under every frontier lab valuation. Those numbers assume companies reorganize around AI, that the work left for people is the hard judgment-heavy kind, and that the labs capture the spend for everything else. The destination is easy to describe. The route there is the argument. 


About Hedgineer


Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 


Subscribe for weekly analysis on AI infrastructure and institutional finance.


Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.


Audio available wherever you get your podcasts.


Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.



Hedgineer.io


Can AI Turn You Into a Creative? S3E1618 août 202600:34:54

Michael and Jhanvi have never edited a video before, and this week they built an entire marketing campaign. They walk through the whole pipeline: Claude Code turning a long prompt about the product into a storyboard of 12 to 16 shots, generating a color scheme and reusable SVG characters, routing clip generation through Runway to Veo, Kling and Seedance, then pulling narration and a score timed to the story from ElevenLabs before stitching it all together with Remotion. Two days to build the process, and it now runs end to end from a phone.

They then get into how the role of video will evolve as it becomes easier and cheaper to create. It has always had a place in sales, marketing, and recruiting. But what about IR, BD, and even research? 



About Hedgineer


Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 


The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 


Subscribe for weekly analysis on AI infrastructure and institutional finance.


Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.


Audio available wherever you get your podcasts.


Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.


Hedgineer.io


Vibecoding: The Right Way | S3E1511 août 202600:48:41

Building application prototypes has never been easier. The ceiling comes after, when someone has to deploy it, host it, and keep it running without much engineering support. This week, Jhanvi and Michael work through what stands between a good prototype and a good application: setting up AI environments that are faster to work in and harder to break, wiring in MCP connectors thoughtfully, and what changes the moment something has to run in production.

Along the way they get into why the same prompt in Cowork and in Claude Desktop produces two very different dashboards, and why only one of them refreshes with live data. They also make the case that not everything needs to be a dashboard, and where scheduling an agent can be more effective. And they share advice for engineers navigating a world with more vibecoding in it, and what providing value looks like when the front office can build its own tools. 

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.

Audio available wherever you get your podcasts.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

Hedgineer.io


How Do You Hedge Against AI? S3E1404 août 202600:36:09

AI names were sold off for several days, a heavily levered AI fund wound down its entire equities book, and then one earnings print reversed most of the damage within hours. The same industry supported two opposite readings in the same day, which says more about how funds are measuring their AI exposure than it does about AI.

Michael and Jhanvi start with why so few funds formally manage their exposure to an AI factor the same way they monitor crowding or market beta, and what happens when crowded exposure to the same handful of names gets booked as idiosyncratic risk and banks are comfortable lending against a portfolio that looks market neutral. From there they get into what makes a business resilient when public sentiment continues influencing public markets, why Microsoft has a head start against their cloud competitors, and how AI is pulling those funds into compute spend they would never have taken on before.

Also in this week's episode: an Anthropic model published a malicious package to PyPI, one of the most trusted repositories in the developer stack, and the accountability question that opens up when a model running inside your infrastructure harms someone outside your company. They also get into the widening gap between the people using AI at work every day and the people booing it off commencement stages, and why Meta may be better positioned than any frontier lab to serve the small businesses through WhatsApp. 



About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.

Audio available wherever you get your podcasts.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.


Hedgineer.io


Crafting an Enterprise AI Policy | S3E1328 juil. 202600:38:53

Almost every fund has a couple of power users spending their weekends in Claude Code, prototyping automations, and proving out how useful AI can be. But then what? How do they hand it to a teammate, and how does a prototype become a production automation that compliance signs off on?

Michael and Jhanvi make the case that the gap is a governance problem sitting upstream of every technical one. Everyone can build with AI. The harder half is getting compliance, IT, and cybersecurity aligned on the enablement guidelines: which tools are approved, on which operating systems, with what runtime and network observability, and who reviews usage after the fact. Answer those and you can put more powerful capabilities in your team's hands, including scheduling, skills, memory, and shared knowledge bases. Also in this episode: the case for sending email as an AI rather than as yourself, why em dashes get a message ignored, and what happened when frontier models refused to help investigate a breach that one of them had been used to cause. 



About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.

Audio available wherever you get your podcasts.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.


Hedgineer.io


Kimi K3: End of the Model Moat? S3E1221 juil. 202600:56:53

Kimi K3 shipped this week, topped multiple coding benchmarks against Fable and Soul, and its full open source release is expected before the end of the month. Where does that leave the frontier model providers? Michael and Jhanvi get into why Anthropic and OpenAI have new incentive to lock down session data, conversation history, model reasoning, tool and skill calls, so a competitor can't distill their models into cheaper alternatives. That leads into Fable's 30 day data retention policy, and a sharper question underneath it: who owns training data that was compiled from knowledge that was never proprietary in the first place?

They also reflect on this week's Hedgineer AI training sessions across clients, and what's separating the top 10% of AI users from everyone else. 


About Hedgineer


Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 



Subscribe for weekly analysis on AI infrastructure and institutional finance.


Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.


Audio available wherever you get your podcasts.


Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.



Hedgineer.io


We Got Rid of Our Forward-Deployed Engineers | S3E1114 juil. 202601:02:14

Hedgineer stopped hiring forward-deployed engineers. Michael and Jhanvi explain why and reflect on when the FDE operating model breaks. Hedge Fund clients showed up assuming a shared context about their business that even the strongest engineers could never have. They also talk through what replaced it: forward-deployed analysts who have worked in similar roles as the teams they're deployed to (TMT research, credit underwriting, fund accounting). After going through extensive AI training with the Hedgineer team, these FDAs are much better equipped to handle building solutions in the forms of agents and skills, leveraging the platform that our AI Engineers build.

Before getting into that, they cover the week in AI: first impressions of Fable (where it earns its cost, and where it's a bazooka for a problem that needed a scalpel), and a teardown of how Claude Tags actually works under the hood, and why Tags and Claude's separate managed-agents runtime still don't talk to each other.



About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 


Subscribe for weekly analysis on AI infrastructure and institutional finance.


Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.


Audio available wherever you get your podcasts.


Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.


Hedgineer.io


What Does It Mean to Own Your Own Context? S3E1007 juil. 202600:35:02

Anthropic has been quietly redacting pieces of what Claude Code and Cowork report back through its telemetry logs. First the model's own reasoning disappeared from the traces. Then, briefly, so did users' prompts. No release notes, no explanation, just a feature flag that got flipped and eventually flipped back. Michael and Jhanvi use the incident to get into a bigger question: what does it actually mean for a firm to own its own context?


Context, in their view, is everything that happens around a model call: the reasoning traces, the prompts, the environment data, the exhaustive record of what a team did with AI. As open-source models close the gap through distillation, frontier labs have a stronger incentive to lock that context down. The conversation gets into what that means for staying model-agnostic, and why a growing field of agent harnesses and open routers adds pressure on that setup.


The discussion then turns to what owning your context makes possible beyond avoiding vendor lock-in. Once a firm is capturing its own usage data, it can build training around what people are actually doing, rather than a generic curriculum, and use that same data to decide where AI adoption should expand next. 


About Hedgineer


Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 


The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 



Subscribe for weekly analysis on AI infrastructure and institutional finance.


Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.


Audio available wherever you get your podcasts.


Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.


Hedgineer.io


Gone Looping | S3E930 juin 202600:54:09

Michael and Jhanvi break down what an agentic loop actually is, how it works under the hood, and what it looks like when investment teams put it to use. From earnings recap to idea generation, the conversation covers how loops shift analysts from reactive prompting to autonomous pipelines that accelerate idea velocity.

We also cover what's new in AI: Claude's new Slack tag feature and the vendor dependency risk it quietly introduces, hyperscaler developments making it easier to run agents at scale, and Estonia's new national policies built to position the country as an AI-forward state.

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.

Audio available wherever you get your podcasts.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

Hedgineer.io


The Future of Compute Futures | S3E816 juin 202600:49:07

Overview


The standard order book matches trades by price and time priority, one at a time. For a fund executing a basket or a pair trade, that means legging into positions sequentially, facing the exposure problem on every leg. In 2016, Kelly Littlepage began building OneChronos around a different premise: let traders express their full intent, and let a mathematical optimization engine find the best simultaneous match.

Ten years later, the same structural problem shows up in compute markets, but worse. Compute is the most perishable commodity ever created; it can't be stored, and transporting it introduces latency that destroys its value. Current proposals for cash-settled compute futures repeat the mistakes of every opaque benchmark market, leaving buyers exposed to manipulation with no physical deliverable backing the contract.

The episode traces a line from FCC Spectrum auctions to modern equities markets to GPU inference token, and the throughline is consistent: markets that let participants express complex, high-level intent outperform markets that force them into rigid, sequential rules. As AI inference fragments across dozens of competing models, the next smart order router won't route equities. It will route tokens.


Guest Bio

Kelly Littlepage is the co-founder and CEO of One Chronos, an ATS powered by combinatorial auctions. He holds a background in computer science, mathematics, control systems, and economics, with deep expertise in electronic market making and electronic capital markets structure.


About Hedgineer


Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 


Subscribe for weekly analysis on AI infrastructure and institutional finance.


Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.


Audio available wherever you get your podcasts.


Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.


Hedgineer.io



Broker Research Has an AI Problem | S3E709 juin 202600:54:07

Sell-side research is the last data category that still resists clean AI integration. US brokers monetize through trade execution, not data sales, which means feeding analyst reports into an LLM removes the attribution that justifies the entire model. No attribution, no incentive to share. That standoff has left buy-side funds cobbling together workarounds for years.

This week brought two competing answers. AlphaSense launched SuperAnalyst, a closed-ecosystem product that bundles research access with its own AI layer. Aiera went the opposite direction with an AI-native research platform built for open integration. The gap between those two bets is essentially the gap between controlling the context window and renting it.

Michael and Jhanvi break down what each approach means for funds actually trying to build research pipelines, and why the choice you make now has infrastructure consequences that outlast any single model generation.

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episodes on Spotify at https://isht.ink/dFj5oaqbe or YouTube at youtube.com/@hedgineer.

Audio available wherever you get your podcasts.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

Hedgineer.io


Driving Alpha via AI Agents in Fundamental Research | S3E602 juin 202601:07:29

The barrier to impressing institutional investors with artificial intelligence is high because portfolio managers and analysts already know their coverage universes deeply. Traditional chatbots that merely summarize 10-Ks or earnings transcripts often act as an enemy to true market comprehension, resulting in weak adoption across fundamental investment teams.

In this episode of The Hedgineer Podcast, hosts Michael Watson and Jhanvi Virani sit down with Brett Caughran, founder of Fundamental Edge, to dissect the structural shift from passive chatbots to active AI agents inside institutional asset management. They explore how top-performing funds are moving past the hype to deploy targeted agent frameworks that act as an analytical exoskeleton around the fundamental research process.

The conversation focuses heavily on the operational realities of data engineering and change management within hedge funds. The hosts break down how curated skill libraries can guide AI tools to operate like senior engineers, allowing non-technical professionals—such as CFOs and COOs—to construct production-grade data pipelines within an hour. They also address the critical necessity of context window management, highlighting why forcing messy research queries and raw data into a single session causes narrative generation to break down, and how separating workflows into distinct, token-optimized agent sessions solves the problem.

Finally, the discussion turns to the macroeconomic and cultural implications of AI adoption on Wall Street. From the power-law distribution of alpha generation to the compression of infrastructure headcounts for new fund launches, this episode provides a realistic, problem-first evaluation of how advanced technology is actively rewriting the hedge fund playbook.

Key Takeaways:

  • The Shift to Agentic Exoskeletons: Chatbots have seen weak adoption because generic summaries destroy institutional comprehension; alpha generation requires highly personalized agents trained on a fund’s historical trades, unique workflows, and internal models.

  • Rigorous Context and Token Management: Merging raw information gathering with narrative generation causes context bloat and degrades output quality; investment professionals must isolate clean research citations in distinct sessions to maintain deterministic control over an LLM's reasoning.

  • Inference-Time Infrastructure Elasticity: Modern frontier models allow funds to execute complex data joins at inference time through Model Context Protocol (MCP) servers, allowing starting managers to launch with leaner infrastructure teams and compress operational headcounts.

  • Observability is the Core of Change Management: Moving from an isolated "AI investor" to an integrated "AI investment firm" requires programmatic observability to track agent tool calls, intercept bad data queries, and convert individual best practices into firm-wide skills.

About the Guest:Brett Caughran is the founder and CEO of Fundamental Edge, an institutional analyst academy providing hedge fund-style training rigor to investment professionals. Previously, he spent over a decade as a fundamental equity investor at leading asset management firms, including Maverick Capital.


About Hedgineer:


Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episode on Spotify or YouTube at youtube.com/@hedgineer.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.



Hedgineer.io


Dev Days & Lock-In Fears: A Frontier Model Race Check-In | S3E526 mai 202600:39:31

Anthropic and Google both had massive dev days recently. And they couldn't be more different. In this episode, Jhanvi and Michael break down what each announcement signals about the frontier model race and where it's headed. Anthropic is doubling down on enterprise agents, memory stores, and "dreaming," while Google is going wide with consumer AI, a multimodal Omni model, and Spark embedded across its entire product suite.

They also get into a question that comes up with clients and candidates alike: how worried should companies actually be about vendor lock-in? Plus: what happens when you run the same agentic harness with different frontier models, why tokens per second is becoming a more important metric, and why you shouldn't switch back and forth between Cowork and ChatGPT. 


Key Takeaways

  • Decouple Architecture via Open Standards: To prevent long-term vendor lock-in, firms should deploy custom skill libraries and organizational knowledge layers as open, text-based formats stored in client-owned GitHub repositories rather than within proprietary model environments.

  • Implement OpenTelemetry Early: The highest hurdle to switching model providers is the loss of historical session data; setting up an independent OpenTelemetry system up front ensures your firm owns its telemetry and interaction data, permitting smooth cross-provider migration.

  • Isolate Compute with Managed Sandboxes: Utilizing self-hosted agent tool containers allows institutional firms to keep localized data execution and tools within their secure cloud environments while securely executing the core inference loop via external APIs.

  • Focus on Immediate ROI Over Early Optimization: Many firms stall their AI adoption by over-engineering cross-cloud or cross-vendor compatibility too early. Successful deployment requires mastering one ecosystem to capture immediate time-to-value before optimizing for compute spend arbitrage.

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episode on Spotify or YouTube at youtube.com/@hedgineer.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

Hedgineer.io


Beyond the Chatbot: Building Agent-Native Enterprises with Mitchell Troyanovsky | S3E419 mai 202601:10:56

The transition from AI as a chatbot to AI as an autonomous agent requires more than just better models; it requires agents capable of regulating their own state and context at scale.

In this episode of The Hedgineer Podcast, co-hosts Michael Watson and Jhanvi Virani sit down with Mitch Troyanovsky, co-founder of Basis, an agent platform specifically designed for the accounting industry. The conversation moves beyond the hype of generative AI to address the engineering realities of building "agent-native" enterprises. Mitch explains why the next frontier of applied machine learning involves closing the loop on self-improving agents—systems that can optimize their own trajectories, contexts, and tools without constant human intervention.

We explore the "single pane of glass" debate: whether specialized platforms like Basis will remain the system of record or if frontier model interfaces will eventually consolidate all enterprise workflows. The discussion delves into the technical nuances of Recursive Language Models (RLMs) and the "Better Intelligence" approach, where models are leveraged to programmatically curate their own context windows to maintain performance over long-duration tasks.

The episode also tackles the cultural shift required for AI adoption. From implementing "Do You Stand By This" (DYSB) protocols to ensure accountability, to the "lexical taxonomy" required to write documentation specifically for LLM consumption rather than human readers, we provide a blueprint for firms looking to move from experimental AI to production-grade agentic systems.


Key Takeaways:

  • Closing the Applied ML Loop: Why the next generation of agents will focus on self-regulation and autonomous state management to handle production workloads.

  • The "Database-ification" of SaaS: How AI agents interacting via API threaten the value proposition of traditional software UIs, potentially reducing many SaaS tools to mere structured data stores.

  • Recursive Language Models (RLMs): A technical look at using model intelligence to dynamically curate context at every forward pass, moving beyond simple "append-only" context windows.

  • Writing for Machines: Why traditional human writing styles are inefficient for LLMs and how "information density" is becoming a critical engineering discipline.



About the Guest:

Mitchell Troyanovsky is the co-founder of Basis, a New York-based platform building AI agents for the accounting industry. He is a leading voice on the future of agentic systems at scale and the implementation of Recursive Language Models in production.

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episode on Spotify or YouTube at youtube.com/@hedgineer.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

Hedgineer.io


Who Owns the Last Mile? Frontier Labs Enter the Consulting Arena | S3E312 mai 202601:02:28

Anthropic just announced an enterprise services venture backed by Goldman, Hellman & Friedman, and Blackstone. OpenAI is raising $4B for something similar. So why are frontier model providers suddenly trying to become consultants?

In Season 3 Episode 3 of The Hedgineer Podcast, Michael and Jhanvi break down what's driving the move: why handing a company a Claude license rarely translates into real automation, and why building domain-specific is critical to successful deployments. The real unlock behind all of this is agent harnesses, which have expanded what AI can do far beyond a chat interface. They dig into how providers are approaching harnesses differently and why state management and organizational memory are the differentiators that not enough people are talking about.

Plus: GPT 4.5 vs. 5.5 cost dynamics, why understanding model caching could save your company thousands of dollars, and whether Apple is sitting on the consumer unlock that could shift public skepticism on AI.  

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episode on Spotify or YouTube at youtube.com/@hedgineer.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

Hedgineer.io


The Energy Behind the Intelligence with Neel Somani | S3E205 mai 202600:51:03

Neel Somani is a quant engineer turned content creator covering power markets, AI infrastructure, and crypto. In this episode of The Hedgineer Podcast, we dig into how the AI boom is reshaping energy markets, how rising compute costs are forcing companies to measure AI ROI, and whether open source models are changing the build vs. buy decision.


About the Guest


Neel Somani is a technologist and researcher focused on the intersection of machine learning, commodities, and formal methods. Formerly a quantitative researcher in the power and commodities space, he has recently gained prominence for his work in mechanistic interpretability and his contributions to solving Erdős problems using large language models.

Follow Neel on X at @neelsomani, TikTok at @neelsalami, and Instagram at @neelsalami


About Hedgineer


Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows. 


The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day. 


Subscribe for weekly analysis on AI infrastructure and institutional finance.


Watch the full episode on Spotify or YouTube at youtube.com/@hedgineer.


Listen wherever you get your podcasts.


Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.


Hedgineer.io


The Art of Building for Agents | S3E128 avr. 202600:52:40

SaaS companies are pivoting: less investment in the dashboard, more in the API. Salesforce's headless MCP suite, Ramp's CLI, Linear's AI connectors — the pattern is the same. Products are being rebuilt for agents, not humans.

In this episode, Jhanvi and Michael dig into what's driving the shift and what it means for funds evaluating their stack. They also get into the architecture question that's coming up with every data vendor they talk to: how do you actually design a good MCP server? They break down the difference between open-source and closed-source skills, where intelligence belongs in the stack, and why the firms that win this next wave won't look like tech companies in the traditional sense.

About Our Hosts: 

Michael Watson is the co-host of The Hedgineer Podcast, CEO of Hedgineer, and a technologist focused on deploying AI within the institutional investment space. 

Jhanvi Virani is the COO of Hedgineer and co-host, specializing in scaling operations and technology platforms for hedge funds.

Subscribe for weekly analysis and trends within AI, Finance, and Technology

Available wherever you get your podcasts!

Video available on YouTube and Spotify

youtube.com/@hedgineer

Questions? Topics you’d like for us to discuss? Email us at podcast@hedgineer.io

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#AIEngineering #InstitutionalInvesting #AssetManagement


Season 2 Finale: Open-Sourcing the Investor Library with Daloopa CEO Thomas Li | S2E1007 avr. 202601:03:04
Season 2 Finale: Open-Sourcing the Investor Library with Daloopa CEO Thomas Li


The Season 2 finale of The Hedgineer Podcast features the return of Thomas Li, Co-founder and CEO of Daloopa, for his third appearance on the show. This episode marks a significant milestone as we transition into a new chapter for the podcast.


Special Announcement: Season 3 and New Format


Before diving into the discussion, host Michael Watson announces a major shift for the upcoming season. Starting next week, The Hedgineer Podcast will move to a weekly release schedule to provide more frequent insights into the rapidly evolving world of technology, data, and AI. Joining the show as a permanent co-host is Jhanvi Virani, Hedgineer’s COO, who will help anchor our weekly updates and industry analysis.


Episode Overview


In this finale, Michael and Thomas explore the decision to open-source Daloopa’s "investor library" of skills and agents—a move that challenges the historically closed-off nature of the financial data ecosystem. They discuss the philosophy behind treating AI agents as "text files" that can be refined by a community of sophisticated investors, effectively turning what was once proprietary alpha into the new industry beta.

The conversation delves into the technical obsession required to serve institutional clients, particularly regarding latency. Thomas explains why Daloopa prioritizes parsing unstructured press wires over waiting for structured SEC filings: in high-stakes markets, saving a few minutes of "server lag" is the difference between a successful trade and a missed opportunity.

We also cover the strategic landscape of building on frontier models. Thomas shares his experience partnering with Anthropic to build their Excel plugin and discusses whether evolving LLMs are a "wind behind the sail" or an existential risk for specialized fintech companies.


Key Takeaways


  • The Open-Source Investor Library: Why Daloopa is providing its corpus of fundamental investing skills to the community and how 100+ hedge funds are already contributing back.
  • Latency as a Moat: The engineering challenge of bypassing SEC server lag by parsing raw press wires to deliver verified data in seconds.
  • Agents vs. Chat: Why the future of finance lies in agentic workflows (like "Scout" and "Claude Code") rather than simple prompt-and-response interfaces.
  • Internal AI Adoption: How Daloopa uses AI internally—from analyzing customer feedback to helping sales teams prep for meetings—without hiring "AI Engineers," but by making everyone an AI user.


Timestamps


  • 00:00 – Season 3 Announcement: Weekly episodes and new co-host Jhanvi Virani
  • 04:15 – The decision to open-source the investor library of skills
  • 11:30 – Why an "Agent" is just a text file and the power of community iteration
  • 18:45 – Monetizing the "Engine": Ferrari’s philosophy applied to financial data
  • 26:20 – The transition from Alpha to Beta in AI-driven research
  • 35:10 – Partnering with Anthropic and the future of Excel-based agents
  • 42:00 – Obsessing over seconds: Parsing press wires vs. SEC filings


About the Guest: Thomas Li is the Co-founder and CEO of Daloopa, a provider of high-fidelity data for company financials and KPIs.


About the Host: Michael Watson is the founder of Hedgineer, building data and AI platforms for institutional asset managers.


Subscribe for weekly analysis starting next season.


youtube.com/@hedgineer


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AI Orchestration: From Custom Skills to Autonomous Hedge Fund Operations | S2E931 mars 202600:39:54
AI Orchestration: From Custom Skills to Autonomous Hedge Fund Operations



Most asset managers treat AI as just a chatbot, failing to bridge the gap between an LLM's general reasoning and the specific, high-stakes workflows of their actual day-to-day.


In this episode of The Hedgineer Podcast, Michael Watson sits down with Jhanvi Virani, COO of Hedgineer, to discuss the practical mechanics of deploying AI within hedge funds and asset managers. Jhanvi details her experience shadowing a CIO to translate their cognitive investment process into a digital skill—a structured framework that allows Claude to synthesize fragmented data from order management systems, SharePoint research, and consensus estimates into polished, institutional-grade outputs in a one-day turnaround. We move beyond simple prompting to explore the "Agentic Loop," discussing how local schedulers and the Claude Agent SDK are enabling systems to run autonomously 24/7.


The conversation also covers the technical nuances of the Claude Ecosystem, comparing developer-centric Claude Code with user-friendly Claude Cowork. Jhanvi shares her on-the-ground findings regarding the limitations of local vs. remote execution and why building a secure, server-side environment is the ultimate bottleneck for scaling AI intelligence across a firm.



Key Takeaways
  • The Skill-Based Unlock: How shadowing investment professionals allows engineers to map complex and manual research workflows into automated skills that produce consistent, high-polish one-pagers.
  • Claude Code vs. Cowork: A breakdown of why developers prefer terminal-based workflows for multitasking, while non-technical users leverage Cowork for scheduled tasks and visual connector management.
  • Building "AI Native" Infrastructure: The 0-to-1 process of auditing fund workflows, building custom MCP (Model Context Protocol) connectors for legacy data vendors, and establishing organizational agent management frameworks.
  • The Self-Healing Feedback Loop: Using usage analytics and "meta-agents" to observe behavior, evaluate performance, and automatically suggest system improvements, creating a self-sufficient AI framework.



Timestamps

00:00 - Introduction and the role of skills in unlocking automation 

04:15 - Evolving daily workflows with Claude Code and Cowork 

08:42 - UI vs. Terminal: Optimizing screen real estate and parallel sessions 

14:30 - Testing the bounds: Automating expense reports and attachment limitations 

17:45 - Windows vs. Linux runtimes and the "Local Scheduler" in Cowork 

22:10 - The Agentic Loop: From Claude Agent SDK to OpenClaw deployments 

29:40 - CIO Shadowing: Translating a day of research into a custom AI skill 

36:50 - The future of autonomous analytics and observation agents 

43:15 - Deliverables for becoming AI Native: Audits, MCP servers, and data warehouses 

51:00 - AI Personification: Authenticity in communication and the risk of "AI slop." 

64:20 - Team expansion in Bangalore and the tech-focus of South India



Guest Bio: Jhanvi Virani is the COO of Hedgineer, where she oversees the deployment of AI infrastructure and automation for institutional asset managers. She specializes in bridging the gap between technical LLM capabilities and high-level investment workflows.


Host Bio: Michael Watson is the founder of Hedgineer and host of the podcast, focusing on the intersection of data science, AI, and hedge fund technology.


Links & Subscribe


Subscribe for weekly analysis on AI and Asset Management.


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Data Liquidity and the Agentic Marketplace: Moving Beyond Bulk SaaS Contracts with Dan Entrup and Freeman Lewin | S2E817 mars 202601:06:50
Data Liquidity and the Agentic Marketplace: Moving Beyond Bulk SaaS Contracts


The traditional model of purchasing financial data is structurally misaligned with the requirements of modern AI development. While hedge funds have historically navigated opaque pricing and rigid, six-figure bulk contracts, the rise of Frontier Labs and agentic workflows demands a shift toward data liquidity and consumption-based procurement.


In this episode, Michael Watson is joined by Dan Entrup (Founder of Agnowledge) and Freeman Lewin (Founder of BrickRoad) to bridge the gap between institutional data strategy and the emerging ML data marketplace. The conversation explores why the "data-centric AI" movement is forcing a reimagining of the supply pipeline, moving away from "buying data to cover your tracks" toward a world where agents autonomously discover, score, and purchase granular datasets for real-time inference.

We analyze the friction within current procurement cycles—often involving over 80 emails for a single deal—and contrast this with the "vibe coding" revolution and the Anthropic "skills" ecosystem. By treating expertise as a distributable text-based asset, firms can bypass traditional SaaS moats and build opinionated, autonomous systems that scale far beyond the capacity of human analyst teams.


Key Takeaways
  • The Shift to Consumption-Based Data: Moving away from bulk annual minimums to consumption models allows firms to trial, backtest, and identify ROI within minutes rather than months, effectively creating a "spot market" for information.
  • Agents as the New Data Buyers: Unlike humans, agents require high-frequency access to small data subsets for accuracy. This creates a need for automated marketplaces where data "sells itself" to machines to maintain trust in agentic outputs.
  • Skills as Monetizable Data: Anthropic’s Model Context Protocol (MCP) and "skills" framework represent a shift where organizational knowledge—such as specific financial modeling styles—becomes a portable, executable asset that can be distributed via marketplaces.
  • The Decline of Legacy SaaS Moats: Software companies that rely on workflow inefficiencies or "proprietary" data that is actually generally available are facing significant valuation pressure as "vibe coding" allows firms to build custom, internal alternatives like CRMs overnight.

Timestamps

00:00 - Introduction to Dan Entrup and Freeman Lewin. 08:45 - The bifurcation of the data industry: Hedge funds vs. Frontier AI Labs. 15:20 - Friction in data procurement: Why it takes 80+ emails to close a deal. 23:10 - Data-centric AI: Why better data now moves the needle more than algorithmic tweaks. 32:45 - Token optimization vs. Weight fine-tuning for enterprise value. 42:15 - Building the Agentic Marketplace: Why data doesn't sell itself to humans. 54:30 - The "SaaS is Dead" debate and the transition to consumption-based revenue. 79:00 - Anthropic Skills: Structuring and distributing expert knowledge at runtime. 98:30 - Vibe coding and the future of the autonomous, multi-billion dollar "small" firm.


About the Guests

Dan Entrup is the Founder of Agnowledge and a veteran data strategist who previously served as Head of Data Strategy for a Fortune 500 company. He specializes in expert network curation and helping firms navigate the complexities of data commerce.

Freeman Lewin is the Founder of BrickRoad, a frontier data lab building an agentic marketplace for data procurement and liquidity. His work focuses on establishing data liquidity through on-chain transaction histories and utility scoring mechanisms.

Michael Watson is the host of The Hedgineer Podcast and founder of Hedgineer, a firm building data and AI platforms for institutional asset managers.


Links & Resources


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AI in Finance: The Data-Centric Strategy with Snowflake's Jonathan Regenstein | S2E716 déc. 202500:52:04

Welcome back to The Hedgineer Podcast, where host Michael Watson dives into the world of AI, data, and technology within asset management, hedge funds, and financial services. In this episode, Michael sits down with Jonathan Regenstein, who leads AI within Financial Services at Snowflake.


This conversation explores the critical role of data and platform strategy in the successful enterprise deployment of AI, moving beyond purely technical wins to focus on commercial outcomes. Jonathan and Michael dissect the evolution of Snowflake from a powerful SQL engine to a unified platform for AI, and debate where the intelligence layer should reside for maximum effectiveness.


❄️ In This Episode, We Discuss:
  • The Power of Data Sharing: How Snowflake's seamless data sharing and Marketplace revolutionized the consumption of alternative data on the buy side, drastically simplifying security and licensing workflows.
  • The AI Layer Debate: A deep dive into whether the AI runtime should live natively within the data platform (Snowflake) using tools like Cortex and Intelligence, or be orchestrated externally by hyperscalers or model providers.
  • Beyond the Technical Win: The shift from technology-driven AI Proofs-of-Concept (POCs) to projects scoped by commercial outcomes—revenue generation or cost reduction.
  • Evaluations are the Product: The crucial importance of robust evaluation frameworks (like those provided by TruEra/TruLens) for agentic workflows to avoid "chaos at scale," and how to involve business leaders—not just engineers—in defining what success looks like.
  • The Semantic Layer's Role: The concept of the semantic model as a first-class citizen in Snowflake, acting as the translator between business language and data, driving accuracy in Text-to-SQL (Cortex Analyst), and building trust with non-technical users.
  • The Future of BI: How AI is driving the complete rethinking of the Business Intelligence (BI) stack, moving beyond static dashboards to dynamic, generative BI that surfaces insights and visualizations on demand.


👤 About Our Guest


Jonathan Regenstein is a key leader in the AI for Financial Services division at Snowflake, driving the platform's strategy in machine learning and artificial intelligence for banks, asset managers, and insurance companies.


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Technology, Talent, IP, and AI: Exploring the Foundations of Modern Hedge Fund Architecture w/ Lucas Rooney | S2E611 nov. 202500:53:07

Welcome back to The Hedgineer Podcast. In this episode, host Michael Watson sits down with crowd-favorite returning guest, Lucas Rooney.

Lucas pulls back the curtain on the "0 to 1" journey of building a new fund, from diligencing the initial idea and recruiting top-tier talent to making the critical "build vs. buy" decisions for a foundational technology stack.


But how does launching a fund today differ from just a few years ago? One answer is AI.


Michael and Lucas dive deep into how the proliferation of AI reframes the entire approach to building systems, forcing a new focus on taxonomy, data labeling, and codifying the "thought process" of an investment from day one.


The conversation shifts to one of the most critical questions facing the industry: How do incentive structures change when an individual's knowledge and intellectual property (IP) can be instantly captured and instilled into the organization's systems?. They explore how firms must re-evaluate compensation and talent, as value shifts from executing perfunctory tasks to the high-level synthesis and compounding of IP.


🎧 In This Episode, We Discuss:
  • The "0 to 1" process of launching a new fund.
  • Key strategies for recruiting passionate technologists and investors.
  • The foundational tech stack: Designing the data/ETL, analytical, trading, and risk layers from scratch.
  • How AI forces better data hygiene and process documentation.
  • The "IP Capture" Problem: Rethinking talent compensation when AI can learn and retain an employee's knowledge permanently.
  • Why hiring is shifting from "task execution" to "IP synthesis" and "compounding".
  • The "Negative Space": Why capturing the bad ideas and hypotheses you didn't run is the next frontier for evaluating skill.


Hosted by Michael Watson, The Hedgineer Podcast dives into AI technology and data in the hedge fund, asset management, and prop trading space.


Follow The Hedgineer Podcast:

  • YouTube: (https://www.youtube.com/@hedgineer)
  • LinkedIn: (https://www.linkedin.com/company/90976838)
  • Twitter: (https://x.com/hedgineering)
  • Instagram: (https://www.instagram.com/hedgineer/)


Don't forget to like, subscribe, and hit the notification bell to stay updated on our latest episodes!


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Beyond the AI Hype with Jason Strimpel | S2E521 oct. 202501:16:22

Beyond the AI Hype with Jason Strimpel


In this episode of The Hedgineer Podcast, host Michael Watson sits down with Jason Strimpel, founder of PyQuant News, long-time Pythonista, and AI enthusiast.

They dive deep into the practical and philosophical implications of artificial intelligence in both asset management and daily life. They break down how the agentic loop works with the Anthropic Agent SDK, the components of good evaluation frameworks, and even how to talk to your kids about AI 

Key topics covered in this episode:


  • Drugs, Sex, and AI: Jason shares his thoughts for new parents: the three things you now need to talk to your kids about are drugs, sex, and AI. Michael and Jason then discuss the difficulty of explaining the difference between humans and AI-powered avatars or toys to children.


  • The "Agentic Loop": The discussion breaks down the simplicity and power of the agentic loop, identifying it as the "core substrate" of modern agentic frameworks. This framework allows a language model to loop, use tools, and determine when to exit to solve complex problems.


  • "Evals are the Product": Michael and Jason iterate on the concept that a robust set of evaluations is the real product. If you can use evals to demonstrate that an agent has harnessed intelligence to solve a specific problem space, you "own that problem".


  • AI vs. Python's Rise: They draw parallels between the current AI boom and the rise of Python in the early 2010s. Both technologies were initially met with skepticism for being "black box" interpreted systems, yet they unlocked massive productivity boosts.


  • Capital Allocation and Moats: The conversation tackles the modern challenge of allocating capital and defending a "software moat" when new AI tools and infrastructure are being commoditized by hyperscalers at an incredible speed.


  • The PyQuant News Story: Jason shares the origin story of his popular PyQuant newsletter, which started as a personal WordPress site for bookmarking research papers and grew into a major resource for the quantitative finance community.


Hosted by Michael Watson, The Hedgineer Podcast dives into AI technology and data in the hedge fund, asset management, and prop trading space.


Follow The Hedgineer Podcast:

YouTube: (https://www.youtube.com/@hedgineer)

LinkedIn: (https://www.linkedin.com/company/90976838)

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Knowledge Graphs, Kuzu, and Building Smarter Agents | S2E424 sept. 202501:10:14

Kuzu, Knowledge Graphs, and the AI Revolution with Prashanth Rao


In this episode of the Hedgineer Podcast, host Michael Watson is joined by Prashanth Rao, AI Engineer at Kuzu, for a deep dive into the world of embedded graph databases and their pivotal role in the age of AI. Building on the previous week's discussion of the columnar database DuckDB, this conversation explores Kuzu, a parallel concept focused on creating high-performance, embedded graph databases.


Michael and Prashanth explore why Kuzu's unique architecture—an embedded, columnar, and strictly-typed system—is delivering incredible speed and scalability for complex analytical queries. They discuss the resurgence of interest in knowledge graphs, driven by the need to impose structure on data for modern AI and LLM workflows. Prashanth explains how LLMs are revolutionizing both the upstream construction of graphs from unstructured data and the downstream querying of these graphs by translating natural language into the Cypher query language.


Tune in to learn about:


  • What Kuzu Is: An in-process, embedded graph database designed from the ground up for query speed and scalability, blending the benefits of columnar processing with the property graph data model.
  • AI and Graph Synergy: How large language models (LLMs) assist in both building knowledge graphs through structured output extraction and accessing them via natural language to Cypher translation.
  • Modern Data Stack Integration: The role of Kuzu as a powerful secondary semantic layer that interoperates seamlessly with primary data stores in data lakes (like Parquet files on S3), DuckDB, and Postgres.
  • Programming with LLMs using DSPy: A detailed look into using DSPy to create structured, modular, and optimizable prompts for more reliable LLM applications, bridging the gap between deterministic code and fully agentic workflows.
  • The Enterprise Knowledge Graph: A discussion on how a knowledge graph can become the single source of truth for understanding complex organizational workflows, data lineage, and interdependencies across an entire enterprise.
  • The Future of Kuzu: A preview of what's next for the Kuzu project, including new graph algorithm capabilities and enhanced concurrency for reads and writes.

Whether you're a data engineer, AI practitioner, or a leader in the asset management space, this episode provides a masterclass on leveraging modern database technology to build powerful, scalable, and intelligent applications.


Hedgineer.io


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DuckDB, Apache Arrow, & the Future of Data Engineering w/ Rusty Conover | S2E309 sept. 202500:58:52

In this episode of The Hedgineer Podcast, host Michael Watson is joined by special guest Rusty Conover, the world's most prolific DuckDB extension builder, for a masterclass on building the next generation of real-time, large-scale data systems.


Rusty, who has an extensive career in data engineering, including at multi-manager hedge funds, pulls back the curtain on what makes DuckDB so revolutionary for developers and data engineers. They explore how its blazingly fast, in-process, C++-based architecture is challenging the big data status quo. The conversation provides a deep dive into the powerful ecosystem growing around DuckDB, from the Apache Arrow columnar format to the evolving landscape of open table formats like Iceberg, Delta Lake, and the new DuckLake.


Join them for a detailed discussion on the nitty-gritty of modern data infrastructure, whether you're building enterprise data platforms or looking for the most efficient tools for your analytics workload.


In this episode, you will learn about:


The DuckDB Revolution: What makes this "blazingly fast" in-process database a game-changer that can simplify and replace entire ETL stacks.

A Tour of DuckDB Extensions: A look inside some of the 15 extensions Rusty has built, from Airport for integrating with Apache Arrow, to Crypto, ShellFS, and TextPlot.


Diving into Apache Arrow: An explanation of the columnar in-memory data format, zero-copy operations, and the Arrow Flight RPC mechanism for efficiently moving data.


The Battle of Open Table Formats: A comparison of Iceberg, Delta Lake, and the new database-centric approach of DuckLake.


DuckDB vs. The World: How DuckDB stacks up against KDB for financial data, ClickHouse for analytics, and its role alongside large-scale compute engines like Apache Spark.


Parquet Deep Dive: The key differences between Parquet V1 and V2 and the importance of modern compression strategies and encodings.


The Future of DuckDB: A sneak peek at powerful upcoming features like time travel and the MERGE INTO statement for simplifying change data capture (CDC) pipelines.


Hosted by Michael Watson, The Hedgineer Podcast dives into AI technology and data in the hedge fund, asset management, and prop trading space.


Follow The Hedgineer Podcast:

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LinkedIn: (https://www.linkedin.com/company/90976838)

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From Viral Reddit Tool to Enterprise AI: The OpenBB Story | S2E226 août 202501:31:39
From Viral Reddit Tool to Enterprise AI: The OpenBB Story | S2E2


Welcome back to Season 2 of The Hedgineer Podcast, where host Michael Watson talks data, AI, and technology in the hedge fund and asset management space.

In this episode, Michael sits down with Didier Lopes, the founder of OpenBB, for a conversation that started five years ago during the meme stock boom. Michael reached out to Didier in 2021 after he shared his "Gamestonk Terminal" on r/wallstreetbets. Michael reached out to Didier if he was interested in a job on his team at Citadel but Didier had other ideas. That initial LinkedIn message from Michael ended up in the pitch deck that helped Didier raise nearly $9 million for his company and the rest is history.


Didier recounts his journey from being a software engineer who automated his personal investment research to becoming the creator of a massively popular open-source project. The Gamestonk Terminal went viral on WallStreetBets and Hacker News, gaining 4,000 GitHub stars in less than 24 hours by cleverly aggregating the free API tiers from hundreds of different data vendor and has evolved into what OpenBB is today.


Join us as we dive into the evolution of a viral tool into a sophisticated enterprise platform and explore the disruptive forces reshaping the financial data landscape.


In this episode, you will learn about:


  • The Origin Story: How a canceled flight during the COVID-19 pandemic led to the creation of the Gamestonk Terminal.
  • From CLI to Enterprise: The strategic pivot from a command-line tool for retail investors to a customizable, SDK-first workspace for financial firms (and then possibly back to CLI with agents).
  • The Data Vendor's Dilemma: A fascinating discussion on the conflict facing companies like FactSet and Capital IQ, whose UI and terminal businesses are threatened by the rise of AI and direct data access through protocols like MCP (Model Context Protocol).
  • The Future of Workflows: Michael explains how he uses AI agents like Claude Code combined with CLI tools to build powerful, autonomous systems for everything from risk management to analyzing entire enterprise data warehouses.
  • The Autonomous Firm: A look into a future where AI enables multi-billion dollar asset managers to operate with fewer than ten people.
  • The Rise of "Acqui-hires": Why the next wave of M&A might value a team's ability to leverage AI far more than the IP they've built.


This is episode is for anyone at the intersection of finance, data science, and artificial intelligence.


Hedgineer.io


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AI in Finance: Eliminating Hallucination & Scaling Workflows w/ Daloopa CEO Thomas Li | S2E112 août 202501:30:56

Welcome back to the Hedgineer Podcast!


We're kicking off Season 2 with one of our favorite guests, Thomas Li, Co-founder and CEO of Daloopa (https://hubs.ly/Q03C7TSR0).


In this episode, we delve into the significant advancements Daloopa has made, including its groundbreaking announcement with Anthropic FIS and its integration into OpenAI. Thomas shares how Daloopa's high-quality, error-free financial data is the key to unlocking the true power of AI for financial analysts. By plugging its verified database into Large Language Models (LLMs), Daloopa is eliminating the critical problem of "hallucination," where AI generates incorrect numbers. This opens up analytical workflows that were previously impossible.


In This Episode, We Discuss:

  • Daloopa's core mission: A relentless focus on accuracy (over 99.9%), comprehensiveness, and speed in financial data.
  • The "Hallucination Problem": Why LLMs like ChatGPT and Claude often fail at financial analysis by generating wrong numbers from the internet.
  • Unlocking New Workflows: How AI with reliable data enables analysts to create deep research reports, summarize 150 earnings calls before the market opens, or run LBO analyses on entire portfolios instantly.
  • A Real-World Example: How a PM used the technology to generate a comprehensive report on the impact of tariffs across all reporting companies before the market opened—a task previously considered impossible.
  • The Future of Pod Shops: How AI impacts hedge fund strategy by increasing a portfolio manager's "at-bats" and "slugging".
  • Behind the Scenes: The story of the Daloopa and Anthropic FIS partnership, rooted in a mutual focus on data quality and solving real customer problems.
  • The "Conference Problem": A look into Daloopa's research on creating a true AI agent inside Excel to assist analysts in real-time during management meetings.


About Our Guest: Thomas Li is the Co-founder and CEO of Daloopa. This company has cemented itself as the highest quality data source for company-specific financials and KPIs. Daloopa is trusted by analysts at the world's leading long-short pod shops and multi-manager funds.

Hosted by Michael Watson, The Hedgineer Podcast dives into AI technology and data in the hedge fund, asset management, and prop trading space.


Follow The Hedgineer Podcast:

  • YouTube: (https://www.youtube.com/@hedgineer)
  • LinkedIn: (https://www.linkedin.com/company/90976838)
  • Twitter: (https://x.com/hedgineering)
  • Instagram: (https://www.instagram.com/hedgineer/)


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The Hedgineer Podcast | Season 2 Announcement04 août 202500:24:30

Special Announcement: Kicking Off Season 2!


In this season 2 kickoff episode, host Michael Watson welcomes listeners back for the second season of The Hedgineer Podcast, the go-to source for discussions on AI, data, and technology within asset management, hedge fund, and prop trading space.


Get ready for an exciting new season featuring a lineup of entrepreneurs and thought leaders. The season kicks off with a return guest, Thomas Li, the CEO of Daloopa, to discuss the significant changes in the AI and data landscape since his last appearance.


Michael also shares the evolution of Hedgineer from a passion project podcast into a thriving company that builds data platforms for a growing list of clients. He details how Hedgineer is leveraging AI tools, such as Claude Code, to accelerate client onboarding and software development, emphasizing the increasing importance of expertise in the age of AI.


On a personal note, Michael shares the joys of becoming a father, life in New York City with his daughter, and highlights from a recent family trip to Spain's Basque Country and Bordeaux, France. Join us for a season of insightful conversations, technological deep dives, and personal growth.


We are incredibly excited for the new topics, guests, and conversations we have lined up.


Listen to the full special announcement now and get ready for an awesome new season!


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Revolutionizing Market Data with Christina Qi of Databento | Episode 1619 déc. 202400:29:19

Welcome to Episode 16 of The Hedgineer Podcast! In this episode, host Michael Watson dives deep into the world of technology, data, and AI in the asset management, hedge fund, and proprietary trading space. Joining Michael is Christina Qi, the founder of Databento.


Michael kicks off the episode by introducing Christina and discussing the disruptive impact of Databento on the real-time market data experience within the asset management hedge fund space. Christina shares her extensive background, including nearly a decade of running a hedge fund and the challenges she faced due to poor data quality and high costs.


Christina explains the motivation behind founding Databento, driven by the need for better data solutions tailored for machine learning and AI applications in trading. She emphasizes the importance of having real-time, high-quality data delivered via API, which was previously lacking in the market.

Throughout their conversation, Christina and Michael explore various topics, including the scalability of data vendors, the differences between working in a data vendor versus a traditional financial firm, and the challenges of managing data in the finance industry. They also discuss the evolving landscape of investors, highlighting the rise of prosumer-type data consumers who require more advanced data services than typical retail users.


The episode also delves into the impact of community-driven platforms like Reddit and the importance of genuine content in fostering meaningful discussions. Christina shares her experiences with different online communities and the challenges of maintaining authenticity in a space often dominated by advertisements.

Overall, this episode provides valuable insights into the intersection of technology, data, and AI in the finance industry, showcasing the innovative solutions offered by Databento and the broader trends shaping the future of asset management and trading.


Don't miss this insightful conversation! Like, comment, and subscribe for more episodes of The Hedgineer Podcast.


Hedgineer.io



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The Future of the Alternative Data Space | Episode 1502 sept. 202400:51:59

Data is maturing at an incredible rate. In turn, the value of data is increasing as new strategies and productization continues to evolve. In episode 15, Eagle Alpha CEO Niall Hurley, discusses the changes and developments in the alternative data space.


Niall highlights emergence of corporates, often times b2b SASS companies, realizing new high margin revenue opportunities by monetizing their data by working with companies like Eagle Alpha to deliver unique insights to their clients. By allowing EA to take on the compliance and economic feasibility testing of bringing new data sets to market, Niall is at the tip of the spear for bringing new insights into the market place faster and helping make better capital allocation decisions.


Historically new data sets are brought to market by an entire entity whose business model is to resell data (Think 1010, Yodlee, etc, or to create new data sets as an aggregator, think Yipit, MScience, etc). It is rare for a corporate to sell direct in a b2c model. It's growing increasingly more challenging to figure out compliance, difficult to find distribution unions, and is not always a significant enough revenue opportunity to justify the resources required to execute.


However, Niall believe change is among us his company is positioned well to act as a market place for the high managing, orthogonal revenue opportunities for corporates to monetize their data.

Additional topics include:


The exploration of new data categories and the continued support for data delivery and go-to-market strategies.


Advancements made by quantitative and multi-strategy funds in utilizing alternative data, and the challenges faced by smaller funds in adopting these data sources


The need for a robust data infrastructure and platform to effectively integrate and analyze alternative data


Is there a need for open-source solutions in risk modeling?.


It’s all here in this incredible episode of the Hedgineer Podcast. Listen here.

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Ep 14 | Storytelling with Data19 août 202400:31:34

At Hedgineer, we believe data has a voice and we are committed to helping you hear what its saying.


In this episode, former Goldman Lead Engineer, now Hedgineer Managing Director Jhanvi Virani joins us to discuss how hedge funds can deliver alpha to their investors by leveraging the Hedgineer platform. Gone are the days of siloed data and non existent processes. 


To thrive as a hedge fund in 2024 and beyond, you need to interact with your data to unlock its true value.Jhanvi explains how her skill set and years of experience at Goldman uniquely position her to solve the most challenging data and analytics problems our customers face. She believes in the power of storytelling, that is has a direct impact on the way your investors evaluate their relationship with your firm.


This is a DO NOT MISS episode. Thanks for joining us.


Key points include:

Interconnectivity between Risk, Research, Trading, Operations, and Investor Relations

Breaking down data silos

Unlocking data

Enabling your data to tell stories

Define and unify processes

Bring your own cloud

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Ep. 13 | The Power and Risks of Artificial Intelligence05 août 202401:03:32

Just about everything in the world of finance is data. It’s only a matter of time that the early adopters and educated users of AI will outrace their competitors to the top.


In Episode 13 of the Hedgineer podcast, host Michael Watson interviews Rob Krzyzanowski, an expert in AI and machine learning with experience at notable firms like Avant, Spring Labs, and Citadel - and also a partner at Hedgineer.


Rob offers his best-in-class view on the value of AI, and specifically, how it translates into platforms that can produce tangible results for hedge funds. We also get a simplified value proposition perspective for large language models, and how they're fundamentally changing the way funds operate.


The conversation also provides a forward-looking view on balancing AI advancements and their application to:

-risk management

-stock classification

-operating efficiencies

-cost reductions


As the team continues it's expansion efforts, Michael wraps the episode with a call for talent. Hedgineer's growth is fueled by world class people. Come join us.


Hedgineer.io

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Ep. 12: Defining The Modern Data-Driven Approach (Playbook) to Investor Relations24 juin 202400:48:08

The hedge fund industry can learn a lot about monetizing data, especially through the lens of CRM - Customer Relationship Management.


In this episode, long-time Salesforce executive Kyle Johnson joins us to discuss how CRM went from a fringe business concept to a core driver of today’s corporate environment. And here’s the key, CRM is really all about data. Names, phone numbers, emails, dates, etc. The genius comes in structuring that information in a format that salespeople can use to drive revenue and improve customer relations overall. 


And when it comes to hedge funds, customers are investors.


Kyle explains how hedge funds can apply this CRM analogy directly  - taking numbers from behind the scenes, structuring the data, then employing it through a platform that works specifically for the fund’s investor relations. 


It’s what CRM did for sales, yet customized for hedge funds.


Key points include: 

  • automating investor outreach
  • using CRM to scale investor relations
  • enhancing brand perception and engagement via social media
  • developing a customer-centric sales model
  • analyzing investor data
  • integrating CRM systems
  • implementing technology solutions for operational efficiency


The time is now for hedge funds to learn from the sales world. Structure their data. Improve investors relations and set new standards of customer care through technology. Thankfully, Kyle reveals it all in this critically valuable episode.



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Ep. 11: Navigating UI and UX in Hedge Funds: Insights from Brian Lee06 mai 202400:56:06

Welcome back to the Hedgineer Podcast, where we delve into the fascinating world of AI, data, and technology for hedge funds, asset managers, and prop trading. In this episode, we’re thrilled to have Brian Lee as our guest. Brian, a former colleague, is a true thought leader when it comes to user interface (UI) and user experience (UX) in the hedge fund space.


Brian’s journey has been nothing short of remarkable. From his early days at Citadel to his recent role as a senior engineer at Figma—a world-class UI development platform—he has honed his skills in creating intuitive tools and systems for portfolio managers and risk analysts. Figma, a powerhouse in the UI design realm, has provided Brian with a unique perspective on the interplay between UI/UX and asset management within hedge funds.


Join us as Brian shares insights from his career journey, including his software engineering work at Intel, where he dived deep into C++ and the inner workings of compute systems. His passion for understanding fundamental system principles led him to explore web technologies and backend development during internships at unicorn companies.


Tune in to gain valuable insights into the dynamic world of UI/UX in finance, straight from the Hedgineer Podcast! 🎙️


Remember to subscribe and stay tuned for more thought-provoking discussions on the intersection of technology and finance. If you’re curious about how UI/UX impacts asset management, this episode is a must-listen! 🚀


For more exciting info and other podcast episodes visit hedgineer.io


Feel free to share your thoughts and questions in the comments below. Happy listening! 🎧🌟


Disclaimer: The views expressed in this podcast are those of the speakers and do not constitute financial advice.

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Ep 10: The Intersection of AI, Entrepreneurship and the Enterprise Evolution15 avr. 202400:25:00
In episode 10 of the Hedgineer Podcast, our founder Michael Watson discusses the importance of intellectual property (IP) ownership and how AI can empower domain experts to create scalable businesses and drive innovation. Watch this rare episode to hear more about the impact of AI on service-based entrepreneurship, including his own journey, and the revolution of enterprise operations beyond chat interfaces.

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Ep 9: The Evolution and Future of Data-Driven Intelligence with Kirk McKeown01 avr. 202401:15:36

 How are the industry’s leading investment firms successfully integrating AI to augment data analysis and fundamental research? We had the opportunity to have Kirk McKeown, founder of Carbon Arc, share how he is using AI to enhance the data collection process and how research teams can leverage intelligence to make better data-driven decisions.


Listen to the full episode to learn more.

_______________________________________________________________________

Welcome to the Hedgineer channel, where we explore the intersection of software engineering, ai, blockchain technology, finance, and more. Each episode features expert guests from diverse industries, including hedge funds and startups, who share their unique perspectives on these topics. From the challenges of software engineering at top companies like SpaceX and Citadel, to the latest trends in AI, hedge funds and DeFi, we cover a wide range of subjects.

_______________________________________________________________________

View More Financial Engineering Videos Below:

Episode 5: Data Management and Licensing with Rich Brown | https://youtu.be/DW1NM_Anhhs

Episode 4: Alternative Data & AI with Sachin Kulkarni | https://youtu.be/aDOdguyARMY

Episode 3 Software & AI in Hedge Fund Investing with Lucas Rooney | https://youtu.be/x78rhK1zCgY

Episode 2 Financial Engineer to Crypto CEO with Neel Somani | https://youtu.be/SIVQ8QxBIu0

Episode 1 A Day In The Life Of A Finance Software Engineer W/ Brian Mahlstedt Ex-SpaceX | Ex-Citadel | https://youtu.be/3VIGPUsKbAE


--------------------------------------------------------------------------------------------------------------------------------------------------------------

WE ARE HIRING!

Visit Hedgineer.io to learn more


Hedgineer is a technology company and media platform founded by Michael Watson (Ex-Citadel MD) building AI and risk management software for hedge funds, trading, and finance.


Website: https://www.hedgineer.io/

LinkedIn: https://www.linkedin.com/in/michaeldavidwatson/


--------------------------------------------------------------------------------------------------------------------------------------------------------------

STAY TUNED:

Slack: https://www.hedgineer.io/join-the-community

Spotify: https://open.spotify.com/show/0Aq6pxdUONA4aJPntsvqf2

https://open.spotify.com/show/0Aq6pxdUONA4aJPntsvqf2

Instagram: https://www.instagram.com/hedgineer/

Twitter: https://twitter.com/hedgineering

LinkedIn: https://www.linkedin.com/company/hedgineer

TikTok: https://www.tiktok.com/@hedgineer

Hosted on Acast. See acast.com/privacy for more information.

Ep 8: Building the Hedge Fund of the Future: Technology, Data, and AI18 mars 202400:31:36

Join us for an in-depth roundtable discussion with the brains behind Hedgineer. Discover how AI and machine learning are revolutionizing risk management in hedge funds. Michael Watson, Brian Mahlstedt, and Gerard Miller explore cutting-edge techniques to identify hidden risks, optimize portfolio construction, and make smarter investment decisions.


Listen to the full episode to learn more.

_______________________________________________________________________

Welcome to the Hedgineer channel, where we explore the intersection of software engineering, ai, blockchain technology, finance, and more. Each episode features expert guests from diverse industries, including hedge funds and startups, who share their unique perspectives on these topics. From the challenges of software engineering at top companies like SpaceX and Citadel, to the latest trends in AI, hedge funds and DeFi, we cover a wide range of subjects.

_______________________________________________________________________

View More Financial Engineering Videos Below:

Episode 5: Data Management and Licensing with Rich Brown | https://youtu.be/DW1NM_Anhhs

Episode 4: Alternative Data & AI with Sachin Kulkarni | https://youtu.be/aDOdguyARMY

Episode 3 Software & AI in Hedge Fund Investing with Lucas Rooney | https://youtu.be/x78rhK1zCgY

Episode 2 Financial Engineer to Crypto CEO with Neel Somani | https://youtu.be/SIVQ8QxBIu0

Episode 1 A Day In The Life Of A Finance Software Engineer W/ Brian Mahlstedt Ex-SpaceX | Ex-Citadel | https://youtu.be/3VIGPUsKbAE


--------------------------------------------------------------------------------------------------------------------------------------------------------------

WE ARE HIRING!

Visit Hedgineer.io to learn more


Hedgineer is a technology company and media platform founded by Michael Watson (Ex-Citadel MD) building AI and risk management software for hedge funds, trading, and finance.


Website: https://www.hedgineer.io/

LinkedIn: https://www.linkedin.com/in/michaeldavidwatson/


--------------------------------------------------------------------------------------------------------------------------------------------------------------

STAY TUNED:

Slack: https://www.hedgineer.io/join-the-community

Spotify: https://open.spotify.com/show/0Aq6pxdUONA4aJPntsvqf2

https://open.spotify.com/show/0Aq6pxdUONA4aJPntsvqf2

Instagram: https://www.instagram.com/hedgineer/

Twitter: https://twitter.com/hedgineering

LinkedIn: https://www.linkedin.com/company/hedgineer

TikTok: https://www.tiktok.com/@hedgineer

Hosted on Acast. See acast.com/privacy for more information.

Ep 7: AI, Innovation, and Insights with Carson Boneck04 mars 202400:47:30

Join Michael Watson, founder of Hedgineer, as he chats with Carson Boneck, the Chief Data Officer of Balyasny Asset Management. They dive into how data, AI and software is being developed and deployed at hedge funds and asset managers. Michael, who used to Equities Technology and Data Engineering at Citadel, and Carson discuss early successful use cases of AI within asset managers and ideate on where they see the space going.


Key Topics Discussed:

Carson's serendipitous path to becoming Balyasny's CDO

The challenges and triumphs of building a world-class data infrastructure

How AI is transforming investment teams in 2024

Balyasny's commitment to premium engagement, innovation, and data quality

Accelerating compliance and legal processes for new AI solutions


Carson highlights the importance of seizing opportunities and adapting to changing circumstances, emphasizing that his philosophy has been to walk through open doors and learn from new experiences.


Listen to the full episode to learn more.

_______________________________________________________________________

Welcome to the Hedgineer channel, where we explore the intersection of software engineering, ai, blockchain technology, finance, and more. Each episode features expert guests from diverse industries, including hedge funds and startups, who share their unique perspectives on these topics. From the challenges of software engineering at top companies like SpaceX and Citadel, to the latest trends in AI, hedge funds and DeFi, we cover a wide range of subjects.

_______________________________________________________________________

View More Financial Engineering Videos Below:

Episode 5: Data Management and Licensing with Rich Brown | https://youtu.be/DW1NM_Anhhs

Episode 4: Alternative Data & AI with Sachin Kulkarni | https://youtu.be/aDOdguyARMY

Episode 3 Software & AI in Hedge Fund Investing with Lucas Rooney | https://youtu.be/x78rhK1zCgY

Episode 2 Financial Engineer to Crypto CEO with Neel Somani | https://youtu.be/SIVQ8QxBIu0

Episode 1 A Day In The Life Of A Finance Software Engineer W/ Brian Mahlstedt Ex-SpaceX | Ex-Citadel | https://youtu.be/3VIGPUsKbAE


--------------------------------------------------------------------------------------------------------------------------------------------------------------

WE ARE HIRING!

Visit Hedgineer.io to learn more


Hedgineer is a technology company and media platform founded by Michael Watson (Ex-Citadel MD) building AI and risk management software for hedge funds, trading, and finance.


Website: https://www.hedgineer.io/

LinkedIn: https://www.linkedin.com/in/michaeldavidwatson/


--------------------------------------------------------------------------------------------------------------------------------------------------------------

STAY TUNED:

Slack: https://www.hedgineer.io/join-the-community

Spotify: https://open.spotify.com/show/0Aq6pxdUONA4aJPntsvqf2

https://open.spotify.com/show/0Aq6pxdUONA4aJPntsvqf2

Instagram: https://www.instagram.com/hedgineer/

Twitter: https://twitter.com/hedgineering

LinkedIn: https://www.linkedin.com/company/hedgineer

TikTok: https://www.tiktok.com/@hedgineer

Hosted on Acast. See acast.com/privacy for more information.

Ep. 6: Using AI to Build One of the Best Datasets for Investing19 juil. 202300:48:31

In the 6th episode of the Hedgineer podcast, Thomas Li, co-founder of Daloopa, delves into the crucial role of precise historical financial data in fundamental investing. The discussion highlights a significant problem faced by financial analysts: the painstaking, time-consuming task of data extraction and management of financial models in Excel. As Michael and Thomas have both experienced first hand this is no easy task, but Daloopa aims to address this issue (and pretty much as solved it) by providing a comprehensive, single-source database for historical fundamentals, ensuring high quality and precise data for fundamental equity investors. This innovation is a game-changer for hedge funds and asset managers, offering them a more efficient and reliable resource for fundamental investing.


The conversation moves towards the unique approach Thomas and team take to structuring financial data. The focus is placed on presenting data exactly as the company reports it, ensuring accuracy over taxonomy in their data model. Thomas also discusses how with the help of machine learning and AI models, the company navigates the complexities of KPIs and adjustments, acting as a 'perfect messenger' of publicly available data.


This is a great episode for financial analyst, hedge fund engineers, entrepreneurship, and anyone interested in learning about a core problems for a fundamental investor.

Hosted on Acast. See acast.com/privacy for more information.

Ep 5: How To Profitably Spend $100M on Data for Trading16 mai 202300:48:26

When it comes to using technology to be at the cutting edge, the quality of the data you are using is the name of the game. In trading that some times means spending tens or even hundreds of millions of dollars for data that gives you insight into the world that very few have. In this episode we bring on Rich Brown who has lead data and sourcing teams at some of the most successful and well hedge funds in the world to shed to light on this industry.


We talk about the different ways that data is used for discretionary and systematic managers. This can include everything from real time exchange feeds, data from bbg terminals, to the most exotic data you could image. We touch on how some alternative data is used to forecast not just price action but more fundamental performance of KPIs that a separate process may then use to forecast future returns.


We also discuss how to think about licensing data to train LLMs where the licensed data my be embedded in the model weights but not easily traced back to the original source. Rich points out that some of this is new but mostly already solved problems, at least contractually, where the products are conscidered derived work products and are likely covered depending on the licensing model used. There is a wealth of insight and we hope that you enjoy this episode as much as we did in creating it.

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EP. 4: Alternative Data and AI11 avr. 202300:39:54

In episode 4, Michael invites Sachin Kullkarni on to discuss alterative data and AI. Sachin is currently head of data science at a multi billion dollar credit hedge fund, and previously was at Point72 as a Sector Data Analyst (SDA) in health care. They discuss how alternative data is used in large hedge funds and how they see the space evolving with Generative AI and Large Language Models (LLMs).


They also look back on the alternative data space and how it has evolved over the past 10 years. Michael and Sachin discuss some of his favorite tools and how they are used including Snowflake, Airflow, Jupyter and Materalize. Then they discuss how they see this landscape evolving over the course of the next couple years as LLMs start to disrupt the space.

Hosted on Acast. See acast.com/privacy for more information.

Ep. 3: Software & AI in Hedge Fund Investing15 mars 202300:46:15

In the third episode of The Hedgineer Podcast, Michael invites equities quant researcher and commodities analyst Lucas (Hog) Rooney to talk about how AI and software engineering can be leveraged for hedge fund investors. In the same way that Python has been a force multiplying tool for Lucas as an investor, LLMs like LLaMa and GPT could be even more impactful for an investor's ability to synthesize information. We talk through how software engineering is developed for fin, how to bridge LLMs into a research process, and what the future may look like. We also go a bit off the beaten path into the back woods of the Pacific Northwest where Lucas guided expeditions into the great unknown.


This is a fun episode because of Lucas's unique journey to end up where he is today. He is a blast to chat with and we hope you enjoy the episode. You can find more about the engineer in all of your favorite apps below:


Slack: https://hedgineer.slack.com/

Instagram: https://www.instagram.com/hedgineer/

Twitter: https://twitter.com/hedgineering

LinkedIn: https://www.linkedin.com/company/hedg...

TikTok: https://www.tiktok.com/@hedgineer

Hosted on Acast. See acast.com/privacy for more information.

Ep. 2 Commodities Quant to Crypto CEO07 mars 202300:30:07

In this episode of the Hedgineer Podcast, Neel Somani, joins us to discuss his journey from being a software engineer and quantitative researcher for Citadel Commodities to a CEO and founder of Eclipse. We talk about how he was able to pivot after the collapse of Terra Luna and raise $15,000,000 to build out a blockchain as a service protocol that leverages the power of ZK rollups.


Careers:

Neel talks us through the transition from a software engineer at AirBnB, to a financial engineer and quantitative researcher at Citadel, then lastly as a founder. Later in the episode he talks about similarities and differences for engineers that decide to work on blockchain projects and how the motivations are similar to financial engineering because it interweaves economics and computer science.


Finance:

He was quick to point out that he now spends very little time writing code, although is still involved in all architecture discussions. One area he spends more time on is business development. He provides insight into the similarities between BD in crypto vs non-crypto companies. We discuss that, similar to equities, the KPIs to focus on for BD, are protocol/sector specific. As Neel points out, for protocols like Eclipse you would look at transaction count, but for something like Gnosis, you look at TVL. We also compare crypto to commodities and get Neel's take on how best to compare the two, and Michael even highlights the comparisons to nation state currencies.


Tech

Neel gives a brief overview of ZK roll-ups and how they provide cryptographic proof of the operations that have been executed to provide the current state of the network. We also touch on the tech stack similarities and differences between financial engineering vs block chain engineering, where the language level differences are pretty minimal if working in Rust. Neel also highlights the importance of Computer Science fundamentals that are especially true when designing an L1.


Hedgineer = Hedge Fund + Engineer


Learn more at https://hedgineer.io or follow us on YouTube, TikTok, Instagram, or Twitter.

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Ep. 1: Aerospace to Hedge Funds28 févr. 202300:49:31

In this episode former SpaceX and Citadel software engineer joins us to discuss his experience joining SpaceX out of college to help on the mission of sending mankind to Mars. After writing software for multiple launches, he made a big career decisions to move from LA to New York and work for Citadel, a major hedge fund. There aren't many people who can compare these two incredible organizations, but Brian is one of them.


Brian and Michael go back and forth talking about their careers and provide unique insight into the career development of engineers behind these major alternative asset managers. And in case you were curious...


Hedgineer = Hedge Fund + Engineer

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