Skip to main content

​
Welcome

This book is for technical people building software for venture capital funds: data engineers, software engineers, CTOs, and technical founders creating tools for the VC ecosystem. It’s about understanding how VC works, analyzing your specific fund’s needs, and building the right technology without common mistakes. It combines domain knowledge with practical technical guidance from real experience at funds like Inflection and EQT.

​
What This Book Covers

The book is organized into three parts:

Part 1: Understanding VC

Learn how venture capital funds actually work, understand your specific fund’s needs, and avoid common mistakes developers make when starting at a fund.

Part 2: The VC Tech Stack

Explore the technology landscape at VC funds - what tools matter, when to build versus buy, and real examples from working funds.

Part 3: Technical Foundations

Deep dives into data providers, modeling, entity resolution, warehousing, integrations, security, and emerging trends like MCP and AI agents.

​
Who This Is For

You should read this if you:
  • Just joined a VC fund as an engineer or CTO
  • Are building tools or infrastructure for venture capital
  • Want to understand how VC funds operate from a technical perspective
  • Need practical guidance on data modeling, integrations, and architecture for VC
This book is not:
  • An introduction to venture capital investing
  • A guide to becoming a VC or raising money
  • Generic startup or tech company advice

​
Getting Started

Start with Part 1

Begin with the fundamentals of how VC funds work - essential context before building anything.

Quick Reference

Skip to specific topics or use this as a reference guide if you’re already familiar with VC basics.

​
About the Author

Alex Patow has been working at the intersection of technology and venture capital since 2020. He started at EQT as part of the Motherbrain platform, then worked closely with deal teams in EQT’s PE business as part of Motherbrain Labs. He now works at Inflection, a pre-seed/seed deep tech VC fund, as the first engineering hire. He’s been recognized in the Data Driven VC Landscape as a top 20 leader in the field and has given multiple talks on the subject.

​
How to Read This Book

If you’re new to VC, read Part 1 sequentially to build foundational understanding. If you’re building specific features, jump to relevant chapters in Parts 2 and 3. Each chapter is self-contained but builds on concepts from earlier chapters. Code examples, real-world cases, and architectural decisions are included throughout.
This book is continuously updated as the VC technology landscape evolves. The principles remain constant, but specific tools and recommendations reflect current best practices.

​
Contributing

Found an error, have a suggestion, or want to contribute additional content? Contributions are more than welcome! Check out the GitHub repository to open an issue or submit a pull request.