Building A System Where Agents Plan, Work, Review, And Learn
Description
Listen to the full interview: https://www.youtube.com/watch?v=G0LTv8hQ5Cs #shorts
Summary
Generated by claude-haiku-4-5-20251001Building A System Where Agents Plan, Work, Review, And Learn
Main Topics
- Compound Engineering Philosophy: A systematic approach to work that extends beyond engineering to product development
- Four-Step Agent Workflow: A cyclical process designed for continuous improvement
- Knowledge Retention and Reuse: Storing learned lessons to prevent repeated mistakes
- AI Agent Autonomy: Enabling agents to work independently while maintaining quality standards
Key Points
The Four-Step Compound Engineering Framework
- Planning
- Creating clear, detailed plans about what needs to be built and done
- Establishing explicit requirements upfront
- Execution/Work
- Agents implement the plan
- Writing code and building the actual product
- Translating plans into tangible output
- Review
- Evaluating work quality (similar to traditional code review)
- Identifying both excellent results and problematic outputs ("slop")
- Conducting iterations for improvement
- Compound/Learning (described as "the most important step")
- Capturing insights from the review and planning phases
- Storing lessons learned as knowledge in the repository
- Making this knowledge accessible to agents for future work
Knowledge Compounding Effect
- Agents can access previous mistakes and learnings during planning, work, and review phases
- Prevents recurring errors across iterations
- Creates a growing knowledge base that improves future performance
Notable Quotes
> "The most important step is the compound step."
> "Agents next time they go into planning or when they go into work or review, they can see the mistakes they made before. So they won't make it the next time."
Takeaways
- Systematic Learning: The framework treats mistakes as valuable learning opportunities rather than failures
- Scalability: This approach enables agents to work autonomously while improving over time
- Applicability: The philosophy extends beyond engineering to broader product development contexts
- Knowledge Repository: Success depends on capturing, storing, and accessing lessons learned in an organized system
- Continuous Improvement: Each cycle builds on previous knowledge, creating a compounding effect on quality and efficiency
Transcript
Compound engineering is a philosophy of doing engineering work, but we realize it applies to more than just engineering work. It's product work as well. The initial version of compound engineering really evolved around four steps. First, you make a great plan. So it's very clear what you need to build and do. Then the part where the agent does the work and implements it and actually writes the code. Third, review. So slop comes out or something beautiful comes out. But how do you know it's good? Traditionally, there's a code review and there's some iteration going on there. Then the most important step is the compound step. If anything comes up during that review or during planning that you think is a good learning, you can compound that knowledge back into the system. We store that as knowledge inside the repository. And agents next time they go into planning or when they go into work or review, they can see the mistakes they made before. So they won't make it the next time. than just engineering work. It's product work as well. The initial version of compound engineering really evolved around four steps. First, you make a great plan. So it's very clear what you need to build and do. Then the part where the agent does the work and implements it and actually writes the code. Third review. So slop comes out or something beautiful comes out. But how do you know it's good? Traditionally, there's a code review and there's some iteration going on there. Then the most important step is the compound step. If anything comes up during that review or doing planning that you think is a good learning, you can compound that knowledge back into the system. We store that as knowledge inside the repository. And agents next time they go into planning or when they go into work or review, they can see the mistakes they made before. So they won't make it the next time. And