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Reading Paths

Different readers will find different parts of this guide most valuable. Choose your path:

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New to VC Funds

If you just joined a VC fund or are new to the venture capital industry:
1

Start with Part 1

Read all four chapters sequentially to understand how VC works, analyze your specific fund, avoid common mistakes, and build the right data team.
2

Identify Your Fund Type

Use Understanding Your VC Fund to determine your fund’s stage, volume, and strategy - this shapes everything you’ll build.
3

Plan Before Building

Apply lessons from Common Mistakes to avoid jumping in too early and building the wrong thing.

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Experienced with VC

If you’re already familiar with how venture capital works:

Common Mistakes

Skip to the seven most common technical mistakes at VC funds.

Technical Foundations

Jump to Part 3 for deep dives on data modeling, integrations, and architecture.

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Building Specific Features

Looking for guidance on a specific technical challenge?

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Common Questions

This depends on your fund’s stage, resources, and specific needs. See:
Choosing Your Stack covers technology choices with VC-specific reasoning. The short answer: use boring, proven technology that AI coding tools understand well (TypeScript/Python, Next.js, Postgres).
Data Modeling covers the critical distinction between companies and deals, plus all the entity types you need to track. This is one of the most common areas where developers go wrong.
Data Providers covers data providers by category (company data, people data, signals), plus how to evaluate vendors and work with their APIs.
Security and Compliance covers what’s actually sensitive, what audit requirements matter, and how to balance security with productivity. Also see Common Mistakes, #5.