AI Prompt: Draft a nonprofit grant logic model from messy program notes
You have program notes, partner commitments, and outcomes scattered across calls and docs. The funder wants a logic model. This prompt structures the mess into a clear first draft you can review with program staff.
The prompt
You are a grant strategist building a logic model for [organisation name]'s [program name]. Program goal: [one-sentence goal]. Target population: [who is served, where, and eligibility]. Current program notes: [paste notes]. Partners involved: [partners and roles]. Grant period: [dates]. Required funder outcomes or indicators: [paste, or 'none provided']. Create a logic model in a table with these columns: Inputs, Activities, Outputs, Short-Term Outcomes, Long-Term Outcomes, Indicators / Measurement Method, Key Assumptions. Requirements: (1) Use only facts from the notes; mark gaps as [NEEDS CONFIRMATION] (2) Make outputs countable — sessions, participants, referrals, materials, or service hours (3) Make outcomes measurable — knowledge, behaviour, access, retention, completion, or wellbeing changes (4) Include 3 evaluation questions after the table (5) Keep language concrete enough for a grant reviewer, not academic.
What you’ll get back
A complete logic-model table with countable outputs, measurable outcomes, clear indicators, and confirmation gaps for the program team to resolve.
Tips for this one
- Use [NEEDS CONFIRMATION] aggressively. Logic models fail when assumptions are presented as settled program design.
- Separate outputs from outcomes. '100 workshops delivered' is an output; 'participants increase job-readiness scores' is an outcome.
- Give the AI any funder-required outcomes verbatim so your draft uses their language where it matters.
- Review the long-term outcomes with program staff before pasting into a grant. They know which promises are realistic.
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How to use this prompt safely
How should a grant writer use this prompt?
Paste the prompt into ChatGPT, Claude, or another AI assistant, then replace the bracketed details with your real logic model draft context before sending it to a customer, lead, or team member.
What should I check before using the output?
Review names, dates, prices, commitments, and any policy-sensitive claims before publishing or sending the AI output. Treat the prompt as a working draft generator, not a final approval step.
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