Stop Selling to Dead Markets.

This process works best when you supply evidence and context. In return, the AI analyzes relationships, weighs signals, and explains its reasoning. Its job is to map the field and score the nodes against evidence. Your role is to supply that evidence, review the output, and make the decisions. The AI is not invested in any particular outcome and does not protect preferences or prior decisions. The output may be confident and may surface conclusions you disagree with.

This method was developed from 25 years of marketing and sales-analysis experience across CPG and software companies, then pressure-tested through extensive AI interrogation and refinement. The AI can help structure and accelerate the diagnostic, but the quality of the outcome still depends on evidence, context, and operator judgment.

The report is a scorecard based on the evidence provided — its purpose is to identify gaps, tensions, and blind spots, and to offer additional angles on how your product appears in the market. Use it to pressure-test assumptions and see the field from perspectives that may not be immediately visible. Agreement is not required. Evaluation and judgment remain with you.

Write one sentence that defines what decision this diagnostic is being used to make. This is your anchor for the entire run.

Unknown beats invented.

If you do not know something, mark it as Unknown in the Customer Template. Do not speculate, and do not rely on the AI to fill gaps.

The 6-Node Field Diagnostic is a structured AI analysis tool. Business details, customer evidence, and context documents are loaded into the session. The AI then rates each of the 6 nodes (Pain, Desire, Proof, Identity, Resistance, Permission) on a scale of 1–10, calculates the Field State (Resting, Building, Ready, or Critical), identifies the primary blocker, and outputs a recommended strategy direction.

A full run usually produces a structured report of roughly 15 to 20 pages, depending on the depth of the source material. The report should give you:

Think of it as a strategy memo written by an analyst who has read everything you gave them, traced the patterns, and has no emotional attachment to your preferred answer. The value of running the diagnostic is that it can synthesize a large amount of structured context quickly, provided the input is good enough and the prompt architecture is disciplined.

Output quality scales directly with input quality. A vague briefing will produce a polished report built on thin foundations. A specific, evidence-grounded briefing will produce something much closer to decision-grade.

The toolkit is meant to do more than generate one attractive answer. Its real purpose is to make the process repeatable across different markets, segments, products, product stages, and strategic questions. It gives you copy-and-paste templates with fill-in fields, built-in checks to catch optimism bias and inflated Node scores, a structure for clarifying weak outputs instead of accepting them too early, and a short list of common failure modes that tend to show up in the first few runs. For operators who want to push the work further, it also includes optimization guidance meant to move the output from merely useful to genuinely decision-grade.

The simplest way to think about this workflow is:

The first output is a draft diagnostic, not the final answer. Good operators push on it, challenge it, ask what is missing, ask what was assumed, and test whether the scoring still holds under pressure.