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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.
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.
I audited the 35 memories my agent keeps about this project. Three were stale, and none of them had been wrong when written: they described a state that expired on its own. The other 80% can't be checked at all, and that isn't a flaw.
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 Many developers use Claude Code and look for ways to reduce token consumption...
Introduction Lately, discussions around token optimization in Claude Code have focused...
Introduction Today, I crafted three bespoke wooden items at work: two diecast car shelve...
More tokens doesn't mean smarter answers. Here's how to engineer context so your LLM actually finds what matters.
Introduction The Fenno Ralli 2026 event has recently captured public attention, largely...
Introduction The case at hand revolves around an attribute table shared by a post...