Self-Doubt Prompting
What it does
A method that adds an instruction to the prompt that first asks the model to check the completeness of data in the question, then provide a brief answer. This reduces the model's 'self-doubt', cutting response length by 37-80% while simultaneously improving accuracy by eliminating excessive reasoning and repetition.
When it helps
Use this technique when the model generates excessively long and repetitive responses, losing efficiency. Especially useful in situations requiring a precise and concise answer without excessive reasoning. Apply to tasks where the model tends to recheck obvious conclusions or cannot critically evaluate the correctness of the question itself. Ideal for optimizing token costs while maintaining or improving answer quality. Effective in scenarios where speed and conciseness are important.
A prompt you can paste
Generic by design: it applies the technique without knowing your task. Adapt the marked parts.
**Role:** You are an AI assistant designed to be highly efficient and accurate. **Context:** You will be given a task that requires reasoning or analysis. **Task:** [INSERT TASK HERE] **KEY INSTRUCTION:** Before you begin your reasoning or analysis, first check if all necessary information is available in the provided task description. If key details are missing or ambiguous, clearly state what information is needed and why. If the information is sufficient, proceed to complete the task using the minimum number of tokens and steps required for a comprehensive and accurate answer. **Output Format:** [SPECIFY DESIRED OUTPUT FORMAT HERE, e.g., "Numbered list", "Table", "JSON"]
If this one does not fit, the two closest alternatives in the corpus are Anti-Bias Prompting and Tabular Prompting, which target the same failure from a different angle.
Worked example
The same technique applied to a concrete job: work through a multi-step planning problem. Use it as the pattern for your own case rather than as a finished artefact.
**Role:** You are an expert AI assistant specializing in planning and problem-solving. **Context:** I need to plan a multi-day trip to Saint Petersburg for a family of two adults and two children (ages 7 and 12) in July. Our budget for entertainment and food is medium. We are interested in both major attractions and unique experiences that would appeal to children. **Task:** Create a detailed 4-day itinerary for this trip. **KEY INSTRUCTION:** Before generating the itinerary, carefully check if all necessary information is available in my request. If any critical details are missing for creating a high-quality plan (e.g., specific interests beyond "unusual for children," preferred pace of activities, dietary restrictions, exact dates), first ask clarifying questions to gather that information. Once all necessary details are confirmed or deemed sufficient, provide a concise and clear itinerary in a table format: Day | Morning | Afternoon | Evening. **Output Format:** A table detailing the 4-day itinerary, followed by brief explanations for key activities, especially those catering to children's interests.
Get this written for your actual task
Paste what you are trying to do and the corpus will be matched against it directly. Free, no account, about ten seconds.
single retrieval pass
That number is low on purpose, and it is real. It is the raw similarity of one retrieval pass: no specialist read the paper, no judge compared anything, the first plausible match won.
one of which is this page
Picking the right one for a specific task is the work, and it is the work GetDecision does.
| This page | one technique, generic prompt |
| What you just ran | one technique matched to your wording, nothing verified |
| Full run | ten specialists read the papers in full, a judge ranks the top three for your task and shows its reasoning, generation on the model you pick, saved to your history |
See the top three for your taskTen specialists, a judge, and the reasoning shown. Free account, first run included.
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