Welcome to another edition of our Sunday “Resources” stream where we share our most valuable data & resources across four rotating formats:

For 1. and 3., we collaborate with best-in-class partners to ensure you get the highest quality data. For 2. and 4., we leverage our ever-growing product portfolio and share selective snapshots of the most sought-after resources from The Lab.

At the end of this post, you'll find a unique deep dive on “The Agentic Fund” with Yohei Nakajima (General Partner at Untapped Capital) and Max Ruderman (CEO at Harmonic).

✅ Access 30,000+ active LPs for your next fundraise

✅ Join our “AI & Automation for VC” Slack group

✅ Summarize 50+ newsletters with ChatGPT

✅ Evaluating startups with ChatGPT

✅ VC Co-Pilot for deal sourcing

✅ Top 10 Prompts for startup sourcing

✅ Top 10 Prompts for startup screening & due diligence 

✅ Top 10 Prompts for deal winning & closing

Access these and more resources like our Slack community, 100+ masterclasses, automation templates, Notion templates, AI copilots, and more via The Lab.

I'm excited to share one of the latest sessions from our Virtual Roundtable series, which goes deep on how investment firms use AI and automation. This time, we zoomed out to the whole firm and asked what a fund built around agentic workflows actually looks like.

Most private market investors are well past the experimentation phase. Max puts the industry at roughly a 6 out of 10 on AI adoption, ahead of most corporate teams, with a wide spread between the leaders and everyone else. I was joined by:

Yohei Nakajima, General Partner at Untapped Capital, a builder by night and VC by day who created BabyAGI, one of the earliest open-source autonomous agents, and runs his firm on a portable operating system for agents.

Max Ruderman, CEO at Harmonic, the startup discovery platform we use as our primary data backbone at Earlybird, which tracks the startup world in near real time and gives investors an agent, Scout, to source, research, and act on companies.

Their shared conclusion: operational AI is quickly becoming table stakes, the way spreadsheets once did. The edge now comes from where you choose to point your attention and how well you protect your own judgment.

1. Keep your playbook portable. Yohei stores his firm's instructions in GitHub repos, with very little data inside. Ask any of his agents for his current LPs and it follows the trail from his chief of staff repo down to the exact CRM list ID and query. That lets him swap between Claude, ChatGPT, and Gemini at will, without locking into any single platform. He leaves specialist work to specialist providers like Harmonic, since replicating what they do for so many VCs would cost more and run less reliably.

2. Point research agents at the industries you're curious about. Run autonomous research agents that go deep into the industries you care about. Combine datasets that have never been combined, have agents make predictions, then judge those predictions. For ongoing coverage, map a market such as vertical legal tech and refine the list until it reflects how you see the space. Then let background agents in tools like Harmonic watch several markets at once and ping you only when something new happens.

3. Win the 15 minutes before every founder call. A simple call prep skill surfaces which competitors raised recently and key details on the founder in about 20 seconds. At Earlybird, we schedule 15 minutes before each call to prepare, and founders told us we came across as the best-prepared investor. That moment is often where competitive deals are won. Yohei's highest-ROI agents are just as practical: one tells him what to work on each day, and another tracks every intro he has suggested and which ones actually happened. For technical diligence, a coding agent benchmarks a startup's open-source repo against two similar projects.

4. Get your own data agent-ready. If you have 1,000+ unstructured decks and memos sitting on a shared drive, start by asking Claude Code or Codex for setup options with pros and cons, and let it ask about your technical level first. Turn off model training on your data before connecting anything, and always ask for provenance, since a founder's own figure and a web-triangulated estimate deserve different levels of trust. MCP connectors handle research on one company well and broad searches across your whole network poorly. Indexing internal data against a global dataset, as Harmonic does with relationship graphs, email, and CRM data, is one way to close that gap.

5. Form your thesis first, then let agents attack it. Polished memos are now easy to generate and tempting to pass along unread. At Earlybird, we push investors to spend a few minutes on every new opportunity defining their own view and key questions upfront. Then ask several models to strawman it. Yohei's prompt swaps “Is this a good investment?” for “What are the core assumptions that would have to be true to make this company successful?” Watch your phrasing, though: a leading question will almost always get you a convincing answer.

Here’s the link to the full roundtable discussion👇

Stay driven,
Andre