Loop Engineering and the Future of VC in the Age of AI

Loop Engineering and the Future of VC in the Age of AI

How AI-Native Funds Source, Evaluate, and Remember

Presented by BFC AI Academy — with Chinat Yu

AI is changing venture capital—but the biggest shift isn't better prompts.

It's better loops.

The funds pulling ahead are beginning to build repeatable AI-powered workflows that continuously source companies, evaluate opportunities, capture institutional knowledge, and improve over time.

A prompt answers once.

A loop compounds.

Join Chinat Yu for a practical, one-hour BFC AI Academy session exploring what an AI-native venture fund actually looks like—and how investors can start building these systems today.

No technical background required.

What We'll Cover

1. How Do You Extend Your Network?

Venture deal flow has always been network-bound: you see what your network sees.

AI agents are changing that equation.

We'll explore how AI-native funds can build sourcing loops across:

• Demo days and startup launches
• Founder communities
• Public signals and emerging companies
• Warm-introduction networks
• Continuous opportunity discovery

The goal: expand your fund's reach without expanding partner hours.

2. How Do You Build an AI-Native Evaluation Platform?

What if the first-pass investment memo took 20 minutes instead of three days?

See a live demonstration of an AI evaluation agent that can:

Read sources → evaluate a company against an investment thesis → score key dimensions → draft a first-pass investment memo

while keeping human judgment exactly where it matters most.

This isn't about replacing investors.

It's about giving investors more leverage.

3. How Do You Build a Fund That Remembers?

A venture fund's most valuable asset isn't just its portfolio.

It's everything the team has learned:

Every pitch.
Every pass.
Every founder conversation.
Every follow-up.
Every investment decision.

Yet much of that knowledge disappears into inboxes, documents, and individual memories.

We'll explore what a true "company brain" for a venture fund can look like—using shared agent memory, connectors into existing tools, and AI agents that continuously keep institutional knowledge current.

Inside YC's QM

Y Combinator recently open-sourced QM (Quartermaster), the multiplayer AI-agent harness YC uses across its own operations.

We'll break down:

• What YC actually open-sourced
• How an agent-based operating system is structured
• What QM can—and cannot—do
• What it takes to deploy a similar system
• Where a VC fund should start first

What You'll Walk Away With

By the end of this session, you'll understand:

The Loop Engineering Framework
How to turn repetitive fund workflows into continuously improving agent loops.

The Three Loops of an AI-Native Fund
Sourcing, evaluation, and institutional memory.

A Live AI Deal-Evaluation Workflow
See an agent research, score, and draft a first-pass investment memo from end to end.

The Anatomy of YC's QM
Understand the architecture behind YC's newly open-sourced agent system.

Three Things You Can Build This Week
Practical workflows investors can begin implementing with tools like Claude Code—without building a full engineering team.

Your AI-Native Fund Diagnostic
Identify which workflow your fund should automate first and where human judgment should remain.

Who Should Attend?

This session is designed for:

• VC Partners & Principals exploring AI-native fund operations
• Angel Investors & Syndicate Leads looking to dramatically increase leverage
• Founders who want to understand how AI-native investors may evaluate startups
• Operators moving into venture capital
• Anyone interested in the future of AI-powered investment workflows

No technical background is required.

This is a lecture with live demos + Q&A, not a coding build-along.

Workshop Format

60-Minute Live Session

• ~40 min: Lecture + live demonstrations
• ~20 min: Live Q&A

About the Instructor

Chinat Yu

Chinat brings elite credentials and practical experience:

• Stanford Learning, Design & Technology graduate with expertise in educational innovation
• MLH Top 50 honoree recognized for excellence in hackathon organization
• Award-winning hackathon projects: devpost.com/cyu60
• MLH Top 50 profile: top.mlh.io/2023/profiles/chinat-yu

He has spent the summer teaching AI-agent workshops, building agent systems for enterprise clients, and advising venture investors in the U.S. and Asia on AI transformation.

In this session, he brings those conversations together into a practical operating framework for the next generation of venture funds.

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The future VC firm won't simply use AI.

It will be designed around AI.

Join us to see what that future looks like—and how to start building it today.

Reserve your spot now.