The Hedgineer Podcast

Data engineering in asset management was always a context problem, not a technology problem. The analyst knows what the data means, the data scientist knows how to query it, and the data engineer sits two steps removed from the domain, building pipelines against a business problem nobody translated cleanly. Michael and Jhanvi make the case that AI collapses that chain: you can now apply context at the last mile, at inference time, instead of spending the first 99 miles encoding it into a warehouse that turns into cement. The security master edge cases, the identifier mapping across 300 names, the non-GAAP KPI alignment against Visible Alpha, all of it fits in a cheap model's context window.
So what does a data engineer do now? Build the context layer. Skills, agent instructions, tools, memory, and an observability layer that tells you which agents are failing and why before your users do, then harden pieces into deterministic code only once you actually understand them. Jhanvi and Michael also get into where this breaks: an agent harness that can't respect your data permissions, MCP connectors that authenticate as a service account instead of on behalf of the user, and the question of what accountability looks like when the work is done under an agent's name instead of yours.  

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

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

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

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

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