Make Your Own Financial Agent for Investors - Open Registration

​​-Agenda Overview

​​Section 1: Agent Architectures:

​​- Understand basic agentic AI concepts: single vs. multi-agent systems.

​​- Explore ReAct (Reason-Act-Observe) loops for decision-making and function APIs for data access.

​​- Demonstration: Use a LangGraph agent to query Yahoo Finance for cap table stress-tests.

​​- Assignment: Customize a GitHub template for your investment sectors.

​​- Demystify AI agents — break down LLMs, memory, tools, and the Observe → Think → Act loop.

​​- Compare architectures — monolithic vs. multi-agent, and heavyweight frameworks vs. minimalist harnesses.

​​- Explore pi-mono — a "primitives, not features" open-source toolkit for building custom agents.

​​- Build live — code a real VC due diligence research agent from scratch in the final session.

​​Section 2: Automated Deal Sourcing:

​​- Create agents for lead generation using vector embeddings on Crunchbase/LinkedIn data.

​​- Discuss prompt engineering to evaluate founder teams.

​​- Hands-on integration: Combine Airtable with OpenAI agents for real-time matching; assess performance using precision and recall metrics.

​​Section 3: Advanced Due Diligence

​​- Implement hierarchical agents for financial analysis and risk management.

​​- Focus on memory storage for audit trails and human oversight.

​​- Demo: Backtest your portfolio for performance improvements; homework involves a diligence simulation on live data.

​​Section 4: Portfolio Agents & Scaling

​​- Coordinate multi-agent systems for monitoring, exit signals, and rebalancing.

​​- Discuss costs, addressing errors, and deployment methods.

​​- Capstone project: Collaboratively build a "VC Vault Agent"