Last week, Vercel published research showing that giving coding agents a compact "map" of your documentation dramatically outperforms letting them search for answers on demand. Their eval results: 100% task success rate with the map approach, versus only 79% when agents had to actively look things up. Same agent, same tasks, different approach to context. The difference between working and not working. The insight clicked immediately. At epilot, we maintain 200+ services, custom frameworks, internal APIs, and domain-specific patterns. If we could give Claude Code and other coding agents reliable access to this institutional knowledge-without forcing them to decide when to look things up-it would fundamentally change how people work in our codebase. So we built it. Then we open-sourced the pattern. The Context Problem Here's why this matters: coding agents have a token limit-a ceiling on how much information they can process at once. Think of it like working memory. You can't hand Claude Code your entire codebase and documentation library upfront. It's too much. The traditional solution is skills: the coding agent decides when it needs information and actively looks it up. "I need to know about authentication, let me search for that." It sounds reasonable, but in practice it creates three problems: Decision paralysis - the agent has to decide when to look up docs, and it often guesses wrong Async delay - every lookup is a round-trip, breaking flow Sequencing conflicts - explor
Source:
https://dev.to/epilot/we-made-coding-agents-actually-reliable-by-fixing-one-thing-525b