Context management is the real bottleneck in AI-assisted coding

After using Cursor and Claude Code daily, I’ve noticed that when an AI coding agent drifts or forgets constraints, we assume it’s a model limitation.

In many cases, it’s context management.

A few observations: - Tokens are not just limits. They’re attention competition. - Even before hitting the hard window limit, attention dilution happens. - Coding tasks degrade faster than chat because of dependency density and multi-representation juggling (diffs, logs, tests).

I started managing context deliberately: - Always write a contract - Chunk sessions by intent - Snapshot state and restart - Prefer on-demand CLI instead of preloading large MCP responses

It dramatically improved the stability of the agent.

Curious how others are handling context optimization.