Coding agents
Agents working in a codebase: what they can see, what they forget between sessions, and why.
1 answer · 4 articles
AGENTS.md: is it enough for codebase context?
Re-explaining is a retrieval failure, not a memory failure. Every session starts cold, and the file you wrote your conventions into is either loaded whole, crowding out the working window, or never read at all. What ends it is recording the decisions your code cannot show, somewhere any agent can query on demand.
ArticleFile-native agents: when reading files backfires
A 9,649-experiment study found file-native retrieval lifts frontier-model accuracy 2.7% and drops open-source accuracy 7.7%. Match architecture to the model.
ArticleConstraint decay: structural rules break AI coding agents
Constraint decay: AI coding agents lose 30 points of accuracy under architecture and database rules. New EURECOM study explains why and where it hurts most.
ArticleWhat 466 AGENTS.md files teach about context engineering
An MSR 2026 study of 466 open source projects maps the five modes developers use to write AGENTS.md context, and what 50% file staleness reveals about practice.
ArticleWhy AI Coding Assistants Can't See Your Codebase
84% of developers use AI coding tools, but only 29% trust the output. The problem has less to do with models and more to do with codebase context.
Give your agents one place to read and write.
Put in your docs, data and notes, then connect Claude, Codex or anything else with one link.
Create a container