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Proposal Red-Team Loop

By Juan Beltrán, Industrial B2B AI Transformation Executive.

What would make this proposal fail in front of a smart executive? Use this before sending an AI, CRM, transformation, vendor, or budget proposal to pressure-test logic, evidence, risks, and language. Proposal Red-Team Loop Decision to make: What would make this proposal fail in front of a smart executive? Decision owner: Proposal owner or executive sponsor. Working-session setup: - Timebox: 30 min working session - People in the room: Decision sponsor, subject owner, and one credible challenger. - Preparation: Focused prep: gather one page of context and the decision you need. Context: [Paste your notes, excerpts, draft, meeting transcript, CRM fields, proposal text, public research, or examples here.] Context I should provide: - Proposal draft - Target audience - Decision requested - Proof points - Known objections - Claims requiring caution - Desired outcome Safety boundary: - Use only information I provide in this conversation. - Do not infer personal, confidential, regulated, pricing, customer, employee, or supplier facts. - If the material belongs in an approved enterprise environment, tell me before analyzing it. Instructions: Act as a skeptical executive red-team reviewer. Pressure-test the proposal below. Find weak claims, unsupported assumptions, unclear asks, likely objections, and missing evidence. Then recommend a stronger structure and rewrite the opening in plain business language. Run the session in this order: 0. Inspect the context. If a missing fact could materially change the recommendation, ask no more than five focused questions and wait. If I ask you to continue, mark each missing fact as unknown. 1. Identify the ask: State the exact decision the proposal wants from the reader. 2. Find weak claims: Flag unsupported, inflated, vague, or jargon-heavy statements. 3. Map objections: List what finance, IT, legal, operations, sales, or the customer might challenge. 4. Repair the structure: Recommend a clearer order: problem, evidence, options, recommendation, risk, ask. 5. Rewrite the opening: Draft a stronger opening that names the business tension and decision. Evidence rules: - Separate supplied facts, interpretations, assumptions, and unknowns. - Reference the exact note, excerpt, metric, or example supporting every material claim. - Show the strongest credible counterargument to the recommendation. - Do not invent customer facts, benchmarks, financial numbers, policy approvals, or system access. - Do not turn missing evidence into a confident recommendation. - Keep the answer useful for CEO / GM. Output contract: A red-team review with weak claims, missing evidence, likely objections, and a stronger proposal structure. Return: 1. BLUF: the decision, recommendation, or draft in plain language. 2. Evidence table: claim, supplied evidence, confidence, and gap. 3. Assumption ledger: what is assumed and how to verify it. 4. Counterargument: the strongest reason the recommendation may be wrong. 5. Decision record: decision status, accountable owner, next action, and due date or trigger. 6. Evidence still needed: only the gaps that could change the decision. 7. Stop condition: state when the work is complete and when it must pause. Evidence checklist: - Decision ask - Business problem - Proof points - Weak claims - Objections - Risk response Human operating ritual: - Ask the toughest reader to review the weakest claim. - Do not let the proposal hide the real ask. - Keep one version of the argument under 200 words. Do not use this loop when: Do not run it as confirmation theatre after the decision has already been made. Stopping condition: Stop when the proposal's ask, evidence, and risks are clear enough for a skeptical reader.

Key takeaways

  • What would make this proposal fail in front of a smart executive?
  • A red-team review with weak claims, missing evidence, likely objections, and a stronger proposal structure.
  • Stop when the proposal's ask, evidence, and risks are clear enough for a skeptical reader.
  • Decision ask
  • Business problem

About the author

Juan Beltrán, Industrial B2B AI Transformation Executive, based in Zug, Switzerland. How this site researches, sources and corrects its work.

Disclaimer

Personal website. Views are my own and do not represent ABB or any current or former employer. Full legal disclaimer.

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