They don't agree.

Chatbots tend to add context, caveats and offers of further help because they are trained to be helpful and thorough. Clear, specific instructions about what to leave out, what format to use and how long to be generally reduce this. Positive framing ('reply with just the answer') plus a format spec and an example is usually more reliable than a negative-only instruction. Adherence is not perfect, so for strict needs you can use structured output modes or post-process the response. Results vary by model and tool.

• State the constraint directly, e.g. 'Respond with only the answer. No introduction, explanation, or closing remarks.'
• Specify the format and length, such as one word, one sentence, a number, or JSON only.
• Put the instruction in the system prompt or at the start of the conversation so it persists.
• Show an example of the desired output (few-shot) so the bot copies the style.
• Models may still add extras sometimes, so you can restate the rule or ask it to revise: 'Repeat, answer only.'

For tighter control, specify the desired length or format, such as “one sentence” or “only the requested list.” Allow essential qualifications so brevity does not make the answer misleading.

Large language models are tuned via reinforcement learning from human feedback (RLHF) to be helpful, polite, and conversational, which frequently leads them to add introductory remarks ('Sure, here is...') and concluding advice. To override this behavior, prompt engineers combine direct negative instructions ('No preamble', 'Provide only the final answer') with explicit formatting constraints (such as requesting pure JSON, Markdown tables, or a defined character or sentence limit). Providing one or two few-shot examples that illustrate the desired concise output format further reinforces adherence.

• Explicit negative constraints (e.g., 'Do not include conversational filler, intro, or concluding remarks') significantly reduce superfluous text.
• Specifying a strict format, such as asking for output in JSON, raw text, or a single sentence, forces the model to omit commentary.
• System prompts or custom instructions set at the session level establish consistent boundaries across repeated queries.
• Few-shot examples demonstrating direct, commentary-free answers guide models through pattern matching.

This is a how-to question rather than a factual claim, so it is answered with practical guidance. Empirically, instruction-following improves when the constraint is explicit, positive where possible (state the exact format), specific about what to omit, demonstrated with an example, and placed both in the system prompt and at the point of the request. Constraints are also easier to satisfy when they can be checked mechanically, such as a one-sentence limit or a single JSON object. Caveat: no prompt makes compliance absolute — models may still add warnings or caveats on safety-relevant questions, and instruction adherence varies by model and version, so treating the output as best-effort rather than guaranteed is realistic.

• Direct imperatives such as "Answer only the question" or "Output only the requested value" are the standard first step in prompting guides.
• Negative-only instructions ("don't ramble") are weaker than a positive format rule ("reply with exactly one sentence" or "return a single JSON object").
• Naming specific extras to omit — preamble, restated question, background, caveats, apologies, offers of further help — works better than a general "no commentary."
• One or two short examples showing a bare answer with no surrounding text (few-shot prompting) reliably steer the output shape.
• Repeating the constraint at the end of the user message, and setting it in the system prompt, improves adherence; no wording guarantees it for every model or every question.

AI bots respond to the structure and clarity of the prompt. By using concise, specific instructions and avoiding open-ended questions, you reduce the likelihood of receiving unnecessary commentary. Specifying the output format (e.g., JSON, bullet points, or a single word) further ensures the response adheres to the requested brevity. This approach is widely used in technical and professional settings where precision is prioritized.

• Use direct, unambiguous language in prompts.
• Specify the output format (e.g., JSON, single sentence).
• Explicitly state that no additional commentary is required.
• Avoid open-ended or conversational phrasing.
• Examples: 'Answer in one word: Yes or No' or 'Respond with only the requested information.'