Reading Paths
Different readers will find different parts of this book most valuable. Choose your path: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 three chapters sequentially to understand how VC works, analyze your specific fund, and
avoid common mistakes.
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.
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.
Building Specific Features
Looking for guidance on a specific technical challenge?Data & Infrastructure
Data & Infrastructure
- Data Modeling - How to structure companies vs. deals - Data Providers - Which vendors to use and how - Data Quality - Validation, trust levels, and ground truth - Data Warehousing
- When you need it and how to set it up
Integrations & APIs
Integrations & APIs
- Integrations and APIs - Webhooks, rate limiting, validation - Entity Resolution - Matching companies across data sources - Data Providers - API vs file delivery, authentication
Tools & Platforms
Tools & Platforms
- The VC Tech Stack - Complete survey of what tools matter
- CRM & Deal Flow - Choosing and implementing - Research Platforms - When to build vs. buy - Portfolio Support - Different approaches and strategies
Security & Compliance
Security & Compliance
- Security & Compliance - What matters, what doesn’t - Common Mistakes - Understanding confidentiality requirements (see mistake #5)
By Role
CTOs & Technical Leaders
Priority reading:- Understanding Your VC Fund - Analyze your specific fund’s needs
- Common Mistakes - Avoid expensive errors
- Part 2: The VC Tech Stack - Buy vs. build decisions 4. Part 3: Technical Foundations - Architecture and implementation
Data Engineers
Priority reading:- What is a VC Fund - Domain knowledge essentials
- Data Providers - Which vendors and how to use them
- Data Modeling - Companies, deals, and the investment lifecycle
- Data Warehousing - Setting up your analytics infrastructure
Software Engineers
Priority reading:- What is a VC Fund - Understand the domain
- Part 2: The VC Tech Stack - What tools exist and when to build 3. Choosing Your Stack - Making smart technology choices
- Integrations and APIs - Working with vendor APIs
Founders Building for VC
Priority reading:- Understanding Your VC Fund - Understand your customers
- Part 2: The VC Tech Stack - What tools funds actually use 3. Part 3: Technical Foundations - What matters to your VC customers
Common Questions
Should I build or buy software for my fund?
Should I build or buy software for my fund?
This depends on your fund’s stage, resources, and specific needs. See:
- Common Mistakes, #2
- Part 2: The VC Tech Stack for category-by-category guidance
What technology stack should I use?
What technology stack should I use?
Choosing Your Stack covers technology choices
with VC-specific reasoning. The short answer: use boring, proven technology that AI coding tools
understand well (TypeScript, Next.js, Postgres).
How do I model VC data correctly?
How do I model VC data correctly?
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.
What data providers should I use?
What data providers should I use?
Data Providers covers data providers by category
(company data, people data, signals) with specific vendor recommendations and cost considerations.
How do I handle data security and compliance?
How do I handle data security and compliance?
Security and Compliance covers what’s actually sensitive, what audit requirements matter, and how to balance security with productivity. Also see Common Mistakes, #5.