The Hedgineer Podcast

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

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

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

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

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