Disabling Thinking Trades Speed for Coding Agents
The thread frames “thinking off” as a latency and harness-reliability optimization for agentic coding, not a general rule. In tight tool loops, hidden reasoning can waste tokens, slow round trips, and sometimes interfere with tool calls or even trigger looping behavior. Several commenters also note the opposite case: for newer reasoning-trained models, leaving thinking on can improve planning, bug fixing, and final review, so the best setting depends on whether the model is in plan mode, execute mode, or a hard-debug stage.
The hot take: “thinking off” is useful when the agent is mostly doing mechanical work, but it is often the wrong default for real coding quality.
- –Best case for disabling it: obvious next-step tool loops where the model should just read, edit, or run tests.
- –Main upside: lower latency and fewer wasted output tokens, which matters a lot when every tool call is interactive.
- –Main risk: shallower reasoning, worse handling of tricky bugs, and more subtle mistakes on nontrivial tasks.
- –Several commenters argue for a split workflow: think during planning and review, stay direct during execution.
- –The answer is model- and harness-dependent; some local stacks benefit from it, while others get worse.
DISCOVERED
4h ago
2026-04-27
PUBLISHED
7h ago
2026-04-27
RELEVANCE
AUTHOR
ThingRexCom