Charlie Greenman
Charlie Greenman
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Full-cycle observational product intelligence

A twelve-prompt no-contact playlist for turning public behavior, language, alternatives, experience reports, and category change into bounded product input without inventing customer certainty.

12 prompts across 4 chapters. Follow them in order while each decision authorizes the next step. Hold, revisit, reject, and conditional branches take their named return path.

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Use this when

Use this when a working product exists and direct outreach is unavailable or intentionally avoided. The sequence observes legitimately accessible public material and authorized aggregate data, never contacts people, and never treats generated scenarios as feedback. It can support problem hypotheses and reversible product review, but it cannot prove willingness to pay, adoption, retention, or realized value without actual behavior.

  • Full-cycle product development begins at the shared Product feedback gate, then decides whether the bounded evidence has earned discovery, delivery, release, and measurement.
  • Full-cycle GTM adds commercial evidence that public observation cannot prove, including commitment, activation, retention, and economics.

Chapter 1

Product and research foundation

Ground observation in the implemented product, authorize no-contact methods, and choose a small source portfolio before collecting signals.

  1. 1.1 Current product and job baseline
  2. 1.2 Public evidence research policy
  3. 1.3 Public evidence source map

Chapter 2

Public signal observation

Observe search language, public experience reports, alternatives, workarounds, and category changes inside registered samples.

  1. 2.1 Search-demand and question mining
  2. 2.2 Review, complaint, and issue mining
  3. 2.3 Alternative and workaround discovery
  4. 2.4 Competitor behavior and change analysis

Chapter 3

Evidence and pattern synthesis

Normalize source types, deduplicate underlying events, derive bounded problem patterns, and challenge them with explicitly synthetic cases.

  1. 3.1 Observational evidence normalization
  2. 3.2 Observational problem-pattern synthesis
  3. 3.3 Synthetic scenario and edge-case stress testing

Chapter 4

Opportunity and product handoff

Nominate a small evidence-capped candidate set, then pass it through the shared Product feedback gate without authorizing roadmap work.

  1. 4.1 Observational opportunity ranking
  2. 4.2 Product feedback