#context

Introduction to Goroutines in Web Servers Goroutines are the backbone of Go’s...

Context engineering is not paste-the-whole-repo. It is choosing which three slices of real state the model must see to stop inventing your architecture.

Context engineering for AI agents isn't about stuffing more into the prompt. It's about knowing when the context you handed the agent has gone stale, and how to catch that before the agent acts on it.

Agent-generated codebase summaries quietly erase type-level information. The next session builds on a version of your code that never existed, and the compiler won't catch it because the summary isn't the code.

CLAUDE.md, AGENTS.md, and .cursorrules stopped being documentation and became configuration written in English. Treat them like migration scripts: review the diff, smoke-check after refactors, and never paste a snapshot of a contract the agent should read live.

A practical context-engineering guardrail: cap an AI coding agent at three files per task. Bigger changes get split, even when the agent volunteers to do them in one shot.

More system prompts, rules, and context don't always mean better coding agents. Learn the technical mechanisms behind context degradation and how to architect smarter instruction pipelines.

Explore why stuffing more context into AI coding agents degrades performance. Understand attention dilution, context window saturation, and engineering strategies to build smarter context pipelines.

Originally published at Agentic Retrieval: The Loop That Decides When to Search on...

Knowledge Authority | Separating AI Context from Enterprise Decision Rights | R.A.H.S.I....

The ability to let someone else take over your work without needing you for every decision. How to prepare a handover when you work with agents: separating the current state from its history while preserving the reasons.

Introduction Today, I crafted three bespoke wooden items at work: two diecast car shelve...