Context Engineering
The same model and stack can produce opposite results because context changes the outcome. These six articles draw on 9 months of production data at Méthode Aristote.
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1/6 · Opposite AI results: what context can explain
Anthropic measured merged PRs; METR measured task duration in a different setting. What these results and long-context research establish, and what remains a hypothesis.
· 11 min read - 2
2/6 · Diagnose and repair context drift
Use L0 to L5 to diagnose context drift, then maintain adherence through observation, repair, and replay instead of treating setup as finished.
· 20 min read - 3
3/6 · Mapping the token-reduction toolbox
Compare RTK, Tokenade, Headroom and prompt caching by mechanism, integration and evidence. Smaller tool output does not establish a cheaper completed task.
· 14 min read - 4
4/6 · The responsibilities around context engineering
A map of context engineering responsibilities: architecture, specifications, agent identity and evaluation, with practical directions for existing skills.
· 14 min read - 5
5/6 · The AI instruction system is a product, not a config file
Personal CLAUDE.md to team AI instruction system for six engineers. How Méthode Aristote separates sources, shares modules, and catches behavioral drift in CI.
· 17 min read - 6
6/6 · Portability becomes a Scale concern
Portable instructions require neutral sources, generated runtime outputs, release controls, and behavioral tests. Native primitives alone do not provide portability.
· 17 min read