# Reasoning disclosure > The model worked for thirty seconds and the viewer wants to know whether it understood the question. - Canonical: https://patterns.konigi.com/ai-assistants/reasoning-disclosure - Group: Grounding and disclosure - Level: implementation - Status: published - Updated: September 12, 2026 - Also called: thinking, chain of thought, show work --- ## Problem A hard question produces forty seconds of nothing before the first word of the answer. During that silence the viewer can't tell whether the model understood the question, misread a key term, or is about to spend the whole answer solving a different problem. ## Solution Stream the intermediate reasoning on a separate track from the answer, collapsed by default, with a one-line summary and a duration visible without expanding. This does two distinct jobs and the second is the one that justifies it. The first is filling the wait, which any progress treatment could do. The second is letting the viewer catch a misread premise at second three instead of second forty. Someone who sees the model restate their question wrongly can stop and re-ask immediately, and that's worth more than the entire content of the reasoning. Collapsed by default is the right posture. The reasoning runs longer than the answer and matters less. A viewer who reads eight hundred words of deliberation to reach a two-hundred-word conclusion has been given a worse product—not a more transparent one. The summary line carries the catchable information; the expansion is for debugging and for the rare case where the path matters more than the destination. Summarised rather than raw is increasingly the shipped form, and Anthropic's documentation describes the mechanism directly: a `display: "summarized"` setting streams a condensed version of the reasoning rather than the full chain, preserving the key ideas with minimal added latency so the summary can still stream as it arrives. Summarising is the right default for a consumer surface. The full trace belongs behind a developer affordance. The honesty limit needs stating, because this pattern is routinely oversold. The visible reasoning is a narration produced alongside the answer, not an execution trace of the computation that produced it. NN/g is direct about the constraint: models are complex enough that even their engineers can't always accurately trace the reasons behind an output. Labelling this panel as why the model answered the way it did claims something the system can't deliver. Labelling it as the model's working is accurate and still useful. Naming matters more here than in most patterns. "Thinking" anthropomorphises and sets an expectation of interiority. Something closer to the mechanism reads better and ages better, and a duration next to it does more for trust than an adjective. ## Use when Reasoning takes long enough that the wait needs explaining, and the task has a premise that could be misread. Analysis and multi-step problems qualify, and so does any question loose enough to be read two ways. ## Don't use when The answer arrives in two seconds, or the task has no interesting intermediate state. A disclosure panel over a lookup manufactures the appearance of deliberation and slows the product's felt speed for nothing. ## Trade-offs Exposed reasoning invites the viewer to argue with the process rather than evaluate the result, which is usually a worse use of their attention. It leaks the model's uncertainty in a way the polished answer hides, which is more honest and lowers confidence even when the answer is right. Raw traces occasionally contain content the product would rather not show, which is one reason summarisation wins. Once reasoning is visible, people optimise their prompts against it. They tune for the narration instead of the output. ## Checklist - Is it collapsed by default? - Does the collapsed line carry enough for the viewer to catch a misread question? - Is a duration shown, and is it the real one? - Does the panel claim to explain why, or to show working? - Can the viewer stop generation from inside the reasoning phase? - Does reasoning count toward usage limits, and is that visible? - Is the reasoning included when the answer is copied, shared, or exported? - Does a screen reader get the summary without the whole trace? - What happens when reasoning is longer than the answer? - Is raw reasoning ever shown, and has anyone read a hundred samples of it? ## Compare **Claude** streams a summarised version of its reasoning by default and keeps the full trace behind an API setting. The panel is calibration for a reader, not a log for a developer. **ChatGPT** shows a running progress narration during longer reasoning, so the disclosure doubles as the progress indicator for the pre-answer wait. **Gemini** presents its reasoning as a structured plan more than a monologue, which is easier to skim and further from what the model actually did. **Perplexity** mostly spends this space on the search steps instead. Showing what it looked for is more verifiable than showing what it concluded. ## Related Streaming response is the track the answer arrives on while this one runs alongside. Tool call trace is the same disclosure for actions rather than thoughts. Citation chip explains origin where this explains path. Stop generation has to remain reachable during the reasoning phase. Response collapse is the same fold applied to the answer itself. ## Related patterns - [Streaming response](https://patterns.konigi.com/ai-assistants/streaming-response) — A model takes ten seconds to finish a thought, and ten seconds of spinner reads as broken. - [Tool call trace](https://patterns.konigi.com/ai-assistants/tool-call-trace) — The assistant did something in the world, and the viewer only sees the sentence describing it afterwards. - [Citation chip](https://patterns.konigi.com/ai-assistants/citation-chip) — A well-sourced paragraph and a fabricated one read identically until the viewer can see where each claim came from. - [Stop generation](https://patterns.konigi.com/ai-assistants/stop-generation) — The answer went wrong in its first sentence and the viewer has to sit through the other four hundred words. - [Response collapse](https://patterns.konigi.com/ai-assistants/response-collapse) — One answer runs to eight screens and buries every other turn in the conversation. ## Sources - [Anthropic, Extended thinking](https://docs.anthropic.com/en/docs/build-with-claude/extended-thinking) - [Nielsen Norman Group, Explainable AI in Chat Interfaces](https://www.nngroup.com/articles/explainable-ai/) - [Microsoft HAX Toolkit, Guideline 11, Make clear why the system did what it did](https://www.microsoft.com/en-us/haxtoolkit/guideline/make-clear-why-the-system-did-what-it-did/) --- Screenshots on patterns.konigi.com are reproduced for commentary and criticism. 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