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Case-Study-Led Offer

Retell one engagement in enough operational detail that the reader recognizes their own situation in it.

Free involved Special Offer Structures

What it adds

The AI builder works from your delivery records, project documentation, and cleared client materials to build a page anchored on a single narrated engagement rather than a wall of logos. It converts because a reader who matches the starting conditions can project the process onto themselves without you asserting anything about their outcome. The goal is inbound inquiries from buyers who self-identify with the documented situation.

What your builder is told to do

7

The actual instructions, in order.
  1. 1

    Read the supplied project files and select one engagement with the most complete documentation and explicit publication clearance. Documentation completeness matters more than impressiveness.

  2. 2

    Verify clearance before writing anything. If no clearance record exists, anonymize to the level the clearance permits, or select a different engagement. Never publish client identity or figures without documented permission.

  3. 3

    Open with the starting conditions in operational detail — team shape, tooling, constraints, and the specific symptom — so a matching reader recognizes their own environment.

  4. 4

    Narrate the work as a sequence of decisions, including at least one point where the approach changed and why. Frictionless narratives read as fiction.

  5. 5

    Report results only as the source records document them, with the measurement method and time window attached. Where a figure is unavailable, describe the qualitative change instead of estimating.

  6. 6

    Add a "this applies if" block translating the starting conditions into a self-check the reader can run against their own situation.

  7. 7

    Set breakpoints: on mobile the narrative is a vertical read with the starting-conditions block sticky at top and a mid-article CTA; on tablet the decision sequence renders as a side timeline beside the prose; on desktop starting conditions, decision timeline, and results sit in a three-region layout with the timeline anchoring scroll position.

Edge cases it handles

5

The things an agent skips when you only say "build a case-study-led offer".
  • The engagement's results are strong but unmeasured; publish the process and state the absence of measurement.
  • The client permits the story but not the name; write it with a described profile rather than an invented alias.
  • Part of the work failed; include it — a documented setback strengthens the account and must not be edited out.
  • The reader's situation matches the symptom but not the scale; state the scale boundary in the applies-if block.
  • Multiple engagements are candidates; pick one and note the others in the assumptions report rather than blending them.

Definition of done

7

Your builder is required to check every one of these before reporting the work finished.
  • Exactly one engagement is narrated and it has a documented clearance record.
  • Starting conditions are stated in operational detail sufficient for reader self-matching.
  • The narrative includes at least one documented change of approach.
  • Every result cites its measurement method and time window from source records.
  • No client name, figure, or quotation appears without documented permission.
  • Mobile, tablet, and desktop each present the full narrative with the starting-conditions block accessible throughout.
  • The builder reports which project files it used, the clearance basis, and which figures are unavailable.

Related offer files

How it works

  1. 1

    Copy the link

    Grab the Markdown blueprint URL for this offer type.

  2. 2

    Give it to your builder

    Paste it into Claude Code, Cursor, Codex, or whatever AI builder is already working in your app.

  3. 3

    It maps, then builds

    Your agent reads the blueprint first, then builds the offer into your app around the product, audience, and stack.

Works with your stack

These blueprints are written to adapt. They tell the agent to detect your framework, match your existing design system, and use your source files instead of guessing the offer.

Need it tighter than that? Customize the offer file and tell it exactly which source docs and stack to use.