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

Hedgineer.io

#AIEngineering #InstitutionalInvesting #AssetManagement

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.

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.

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.

• 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.

• 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

Hedgineer.io

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

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.

• 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.

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.

youtube.com/@hedgineer

Hedgineer.io

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