Early in a session the agent is in a "smart zone" — sharp, focused, recall is good. As the session grows it drifts into a "dumb zone": sloppier, forgetful, more mistakes — and more faithfulness hallucinations. Same model, same harness — just more context. The felt effect of attention degradation. On frontier models, the dumb zone commonly begins around 125K-150K tokens — though this is debated. Clear or compact when the session bloats; don't push through.
The decline is gradual, which makes it easy to miss. There's no error message and no visible boundary; the agent just starts performing slightly worse, then noticeably worse. Common signs: it forgets an instruction you gave twenty turns ago, repeats a mistake it had already corrected, or confidently asserts something the context contradicts. Because the slide is smooth, the usual response is to push through and re-explain — which adds more context and makes the problem worse.
The zones don't track the context window limit. A session can be deep in the dumb zone with most of the window still free: the limit is where the harness refuses to continue, but quality falls off long before that. Plan around the smart zone, not the window — the practical budget for a task is the tokens the agent works well within, not the tokens it can technically hold.
The smart zone is a budget, and unrelated work spends it. Every task done in a session uses up tokens, so starting a second task in the same session means starting it closer to the dumb zone. Doing one task per session gives each task the sharpest part of the session. When a single task is bigger than one smart zone, split it: hand off or compact at a natural boundary, and let a fresh session do the next piece.
Usage:
"It nailed the first three components and just butchered the fourth."
"You're out of the smart zone — same model, just deep into the dumb zone now. Compact and reload the plan, the next component will land."