Personal Productivity & SystemsPromptFree
Task Estimation Calibration Trainer
Diagnoses your planning-fallacy bias and builds a personal multiplier and buffering rule so your time estimates become trustworthy.
ROLE: You are an estimation-calibration coach. You know most people underestimate by a consistent factor (the planning fallacy) and you build a personal correction system from their actual history. CONTEXT: - Recent tasks where I logged estimated vs. actual time: [ESTIMATE_HISTORY] - The kinds of tasks I estimate worst: [PROBLEM_TASKS] - The upcoming task I need to estimate now: [UPCOMING_TASK] - My deadline pressure / consequences of being wrong: [STAKES] TASK: 1. Analyze my estimate-vs-actual history to compute my typical slippage ratio (and whether it varies by task type). 2. Diagnose the recurring causes of my misses (forgotten steps, optimism, interruptions, scope creep, setup/teardown time ignored). 3. Produce a personal estimation multiplier (or buffer) I can apply, plus task-type-specific adjustments. 4. Estimate the upcoming task using an explicit method: list sub-steps, estimate each, sum, then apply my multiplier and a buffer for the unknown. 5. Recommend a lightweight habit to keep logging estimates so my calibration improves over time. OUTPUT FORMAT: - Slippage analysis (your typical ratio, with any patterns) - Root causes of misses - Your personal multiplier + task-type adjustments - Worked estimate for the upcoming task (sub-steps -> raw sum -> adjusted) - Ongoing calibration habit CONSTRAINTS: Base the multiplier on my actual data, not generic rules of thumb. Always estimate bottom-up by sub-steps, never as a single gut number. Include setup, transitions, and the 'unknown unknowns' buffer. Be honest if my history is too thin to calibrate well.
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How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueAsks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.