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Instinct's agent-to-agent coordination is the most interesting thing a consumer AI app has shipped recently, and Michael and Jhanvi get into how they've been using it. Instinct lives entirely in iMessage. Michael can ask his Instinct to coordinate something with Jhanvi's, and the two agents handle the back-and-forth while each person approves what gets shared. They compare it with Muse, from data connectivity to the experience of interacting with the agent. They also debate where the moat sits when a feature like Instinct's is easy to copy and network effects can be bridged by integration, with accumulated memory about the user as a more durable advantage than any single feature. Finally, they cover the gaps that keep either app from replacing a daily driver, including limited calendar support and no way to read what your agent said on your behalf. The conversation then turns to what consumer AI means for the firms that buy enterprise tools. As people get used to simple, connected assistants at home, the pressure on enterprise AI policies around email and calendar access will grow. They close with model news: a new generation of cheaper, faster releases, the case for small fast models as top-of-funnel classifiers across large volumes of news and filings, and why token speed matters more as agents carry more context into every session. 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. Instagram: https://www.instagram.com/hedgineer/ LinkedIn: linkedin.com/company/hedgineer-io  TikTok: tiktok.com/@hedgineer Twitter: x.com/hedgineering Email us at [email protected] Hedgineer.io

Opus 5.5 shipped at 40% below Fable. Meta Muse explodes in popularity. It's a busy time in the world of AI. Michael and Jhanvi go through their first reactions of Muse. The onboarding asks you to name an agent before you've asked it to do anything, then connects your email and calendar, then asks about your health, your finances, and the relationships you want to work on. It never asks which model you want. It never asks you to build complex AI workflows. Meta pulled human reasoning and expertise out of the loop entirely and gave the harness that call, which is the opposite of how most agent products work today. They also allows users to see the entire file system, so ordinary users are browsing memory files and markdown like a codebase. Whether that survives mass adoption decides which technical concepts become general knowledge, the same way "file" and "firewall" did. The through-line is who gets value. Most of the people currently getting real leverage out of AI work in technology, and that includes funds outside of tech who have bought the same tools and still can't reach the autonomy they read about. Consumer AI is how that closes. Every time someone makes an agent feel obvious to a hundred million people, the floor rises for everyone building on top. They also get into Apple's Siri beta and why the data advantage there remains the most underused in the industry, what the social media rollout should have taught everyone about moving quickly, and Jev, which charges nothing for output tokens and is quietly very good at the boring classification work underneath every agent.  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. Instagram: https://www.instagram.com/hedgineer/ LinkedIn: linkedin.com/company/hedgineer-io  TikTok: tiktok.com/@hedgineer Twitter: x.com/hedgineering Email us at [email protected] Hedgineer.io

OpenAI and Anthropic are calling for a slowdown in frontier AI development. Nvidia and Meta are not. The line runs between companies whose revenue depends entirely on frontier research and companies with tested businesses underneath them. Jhanvi and Michael take apart the incentives behind the debate, and they cover everything from the moat heavier regulation would build for larger players to the data center fights in states like Michigan, where towns are debating whether these centers do more harm than good. Then the question every firm rolling out agents hits in week one: who is the agent logged in as? Authenticating as the user keeps accountability clean, until that person leaves and the job breaks. So is the answer service accounts with pre-configured permissions? Plus the new favorite way of talking to agents, which surprises no one: email.  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 [email protected]. Hedgineer.io

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 [email protected]. 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 [email protected]. 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 [email protected]. 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 [email protected]. 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 [email protected]. Hedgineer.io

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 [email protected]. Hedgineer.io

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 [email protected]. Hedgineer.io

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 [email protected]. 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 [email protected]. 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 [email protected]. 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 [email protected]. 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 [email protected]. Hedgineer.io