How to write a good spec for AI agents
AI Summary
Effective AI agent development requires moving away from massive, monolithic prompts toward modular, spec-driven workflows. By treating specifications as living, version-controlled artifacts, developers can maintain context, enforce boundaries, and improve output quality. The article advocates for a 'plan-first' approach using read-only modes, designing for 'Agent Experience' (AX) through parseable formats like MCP, and leveraging sub-agents to manage complexity without overwhelming the model's attention budget.
Key Takeaways
- Use 'Plan Mode' to allow agents to analyze codebases and draft specs before executing any changes.
- Design for 'Agent Experience' (AX) by providing machine-readable documentation like OpenAPI schemas and llms.txt files.
- Treat specs as code: store them in version control and use them as the source of truth for sub-agents and automated testing.
Why it matters
As AI agents become integral to software development, the 'curse of instructions' and context window limitations often lead to fragile, hallucinated code. Adopting a structured, iterative specification framework ensures that AI agents remain focused, reliable, and aligned with architectural goals.
Conversation 0
Be the first to share your perspective.