Context management is the real bottleneck in AI-assisted coding

1 points by hoangnnguyen 5mo ago ↗ HN

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.

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hoangnnguyen 5mo ago ↗

I also wrote a detailed breakdown of: - How tokens and context windows actually affect stability - Why coding degrades faster - A practical context stack model - Why on-demand CLI retrieval is often more context-efficient

Full post: https://codeaholicguy.com/2026/02/14/tokens-context-windows-...