Overview
Claude’s latest Code feature allows engineers to build hooks into their prompts, sub-agents, and skills, enabling specialized self-validating agents that automatically check their own work. This addresses the critical trust gap in agent automation by adding deterministic validation layers that save engineering time and increase reliability.
Key Takeaways
- Build focused agents that do one thing extraordinarily well - specialized agents with single purposes consistently outperform generalist agents across thousands of runs
- Implement post-tool-use hooks for automatic validation - agents can now run custom validation scripts after every file operation, creating closed-loop systems that catch errors immediately
- Use specialized validation instead of generic checks - each agent should validate work specific to its purpose (CSV formatting, HTML structure, etc.) rather than running broad validation
- Don’t delegate learning to your agents - engineers must still read documentation and understand the tools they’re building with, or risk starting a self-deprecation process where they stop growing
Topics Covered
- 0:00 - Introduction to Agent Validation: Why validation is crucial for agent trust and how Claude Code’s new hook feature enables specialized self-validating agents
- 2:00 - Building Custom Commands with Hooks: Creating a CSV editing command with post-tool-use hooks that automatically validate file operations
- 4:30 - Setting Up Validation Scripts: Organizing validator directories and configuring hooks to run specific validation scripts after tool use
- 7:00 - Testing Self-Validation: Demonstrating how agents automatically detect and fix CSV formatting errors through specialized hooks
- 10:00 - The Power of Specialized Agents: Why focused agents outperform generalist agents and how hooks enable ultra-specialized validation
- 14:30 - Sub-Agents with Validation: Implementing the same validation patterns in sub-agents for parallelization and context isolation
- 17:00 - Scaling Validation Across Teams: Running multiple CSV editing agents in parallel, each with specialized self-validation capabilities
- 20:00 - Engineering Philosophy: The importance of agents validating their work like good engineers do, and avoiding over-reliance on AI for learning
- 23:00 - Real-World Application Demo: Multi-agent financial processing pipeline with specialized validators at each step
- 26:00 - Best Practices and Warnings: How to continue learning as an engineer while leveraging agent automation effectively