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

  1. 30 Hottest Startups of the Month (January’s list here)

  2. Top Downloaded Resources from The Lab (this is today!)

  3. State of the Market (December’s multiples & benchmarks here)

  4. Top Downloaded Resources from The Lab (“how to integrate data sources and make them actionable with AI” here)

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 “building a hyper-automated micro VC” with Alex Patow from Inflection (ex EQT).

RESOURCES OVERVIEW🛠️

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

List of 312 family offices

List of 59 pension funds

List of 997 accelerators


Access these and more resources like our 100+ masterclasses, automation templates, Notion templates, copilots, and more via our Annual and Premium subscriptions to The Lab below👇

What I read this week🤓

Here’s a summary of the best content that I consumed in the previous week…

1) What Brought Us Here Won’t Bring Us There

This article by “A Smart Bear” explains that after reaching Product/Market Fit, startups must undergo a difficult but essential shift from “Explore” mode, focused on experimentation, speed, and discovery, to “Execute” mode centered on scaling, reliability, quality, and predictable processes.

Many founders fail here by clinging to the behaviors that drove early success, underestimating how radically the company’s needs change as growth accelerates. This transition demands new skills, systems, and often a cultural reset, including letting go of shortcuts, embracing management and process, and redefining the founder’s role.

2) Claude Code Tutorial

Everyone who has been following my “Automating VC” experiment (make sure to join our free Slack group here) knows that I just started playing around with Claude Code, so I read through dozens of starter guides in the past weeks. Here’s one that I liked the most.

The piece argues that getting real value from Claude Code requires thinking before typing: clear planning, explicit architecture, and strong prompting are more important than the model itself.

High-quality output comes from high-quality input, reinforced by tools like plan mode, a disciplined CLAUDE.MD, scoped contexts, and resets.

The biggest gains come when Claude is treated as part of an automated system and not just an interactive assistant.

3) How a16z Became a Top VC Firm (+ Snapshot of Their Returns)

This new piece by Not Boring provides a portrait deep dive on a16z and argues that the firm is best understood not as a traditional VC fund but as a scaled institution designed to compound power, belief, and advantage on behalf of future-defining technology companies.

By consistently betting on larger outcomes, bigger ownership, and heavy investment in platform, policy, media, and talent, a16z has turned scale into an advantage rather than a liability.

In its current “Third Era,” the firm is moving beyond picking winners to actively shaping the environment they compete in, positioning itself as a power broker for the future of technology.

Building a Hyper-Automated Micro VC

I’m excited to share the recording from one of the most watched recordings in our platform The Lab from a deep dive session with Alex Patow from Inflection (ex EQT).

Watch if you want to learn:

  • The minimum estimated budget for a micro VC to start their AI & automation journey, split across data, tools, and HR

  • How micro VCs can negotiate better rates with data providers

  • Why automating your fund is possible now, partly due to the availability of off-the-shelf tooling, improved data quality & AI capabilities

  • Inflection's tech stack, called Computer-Aided Venture Investing (CAVI), which includes Kepler (a research platform) and Pathfinder (a sourcing tool using a knowledge graph)

  • The strategy to "buy versus build," where micro VCs should exhaust off-the-shelf options before committing engineering time to building, since "the most expensive line of code is the one that you write yourself"

  • How the role of engineers / investors has changed, with tools that can write code accelerating the amount of "stuff you can build"

  • … and a lot more

Here’s the link to the full panel discussion👇

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