How do I stop my AI coding agent from forgetting my conventions between sessions? Build persistent context — but tier it. The core distinction: context is not memory. Memory is everything that happened. Context is the deliberately-tiered subset the agent needs now. Dump everything into one file and you have a monolith, not a tier architecture.
The Context Tiering Spectrum
Information has a temperature gradient: hot (consulted every task), warm (specific roles), cold (reference, fetched only when relevant). Agents succeed when these tiers are explicitly designed, not accidentally accumulated.
The numbers that should change your CLAUDE.md
- The usable instruction budget in your permanent core is ~300–500 instructions before instruction-following degrades.
- Information in the middle of a long context is deprioritized relative to the beginning and end (Liu et al., “Lost in the Middle”, arXiv:2307.03172).
- Past ~40–50% of context capacity, performance collapses 30%+. And the finding that settles it: even with perfect retrieval, a long context still dropped performance 13.9–85% (Du et al., 2025, arXiv:2510.05381). Length itself is the poison.
Build up, don’t carve down
Practitioners who start with a curated 20-line context file and grow it intentionally consistently outperform those who start with a generated 200-line version and prune. Curated context — rules you wrote after measuring their impact — earns its place. Auto-generated context occupies budget without proportional benefit. It’s the same persistent-context layer that closes convention drift.
Installable move: audit your Tier 1. Anything temporary, session-specific, or untested doesn’t belong in the permanent core. If everything is in one file, split by temperature.
The full Context Tiering Spectrum + the other two infrastructure pieces: curiochat.ai/software-engineer