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Business Transformation Journey Contract

These instructions apply to every journey under src/pages/journeys/**.

Route​

Use biz-dev-ai-transformation for any material journey build, rebuild, or transformation report. The skill owns the executable method and specialist orchestration. This file owns the durable repository boundaries the skill must respect.

Business folders supply local truth. Read the target journey's _flow material before drawing conclusions. Prefer _flow/1-input/; accept legacy input locations such as _flow/_input/, raw-analysis/, or a clearly named business brief. Derive the business name, decision-maker, worldview, tools, claims, and unknowns from those files. Never hard-code one business into the shared standard or launch prompt.

Product Boundary​

The public journey is the business transformation report:

index -> Reality -> Dream -> Bridge -> self-serve action
  • index orients the decision-maker and opens the journey.
  • reality makes the current system, binding constraint, unknowns, and cost of drift recognisable.
  • dream makes one concrete two-year position, meaningful human role, and cost of delay tangible.
  • bridge backcasts the smallest credible proof with an owner, gauge, date, alternatives, and kill signal.

Do not create a separate report page. Do not let one page consume another page's decision job. Every page must teach one useful lesson and enable one observable behaviour.

Use the no-purchase test:

If the reader never hires Dreamineering, are they still better able to understand, steer, and improve their business?

Evidence And Publication Boundary​

  • Treat supplied business claims as inputs until their evidence status is known.
  • Keep private inputs, research notes, reasoning, and evaluation inside _flow.
  • Never expose an _flow or other private path from a rendered page.
  • Public research cannot upgrade unknown private operating numbers.
  • Do not present projected ROI as measured fact.
  • Approved claims and copy pass through the journey's data contract before rendering.
  • Keep human comprehension and business outcomes UNTESTED until actually observed.

Research is a method, not a required folder. Do not create new 2-research, 3-rhetoric, or 4-presentation process folders. Retain only decision-changing evidence in an existing local artifact or one _flow/evidence-ledger.md when persistent traceability is necessary. Write the single strategy handoff to _flow/strategy-contract.json and validate it before changing public claims.

Existing journeys may retain legacy source material and their current JavaScript or TypeScript shape. Preserve user work. Do not rename or delete legacy evidence merely to make the folder look current. New pages use .tsx.

Standard-Work Improvement​

Treat biz-dev-ai-transformation and this contract as the current best-known standard. Close every journey by classifying observed variance:

  • Input — local business evidence was missing or weak;
  • Execution — the existing method was not followed;
  • Local — this business needs a genuine specialization;
  • Shared standard — the common method caused, missed, or failed to prevent the defect.

Keep business-specific corrections local. Improve the owning skill or this contract only when a run supplies evidence that the correction should help other businesses, names how the next run will verify it, and receives human approval. Do not copy shared procedure into local AGENTS.md files. One approved improvement to the standard should lift every later journey.

Done​

A journey is complete when:

  • every public claim traces to evidence and the strategy contract;
  • Reality, Dream, and Bridge perform distinct jobs;
  • the first proof is bounded, owned, measurable, dated, and killable;
  • a cold reader can name the constraint, better position, first action, and reason to stop;
  • at least one useful action remains possible without Dreamineering;
  • relevant strategy, formatting, link, type, mobile, legibility, and rendered-interface checks pass;
  • residual unknowns name an owner and the cheapest verification step; and
  • reusable production learning has improved the shared standard for the next journey.