STUD
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Build a Six-Frame Innovation Storyboard

I get a single structured storyboard document with all six narrative frames filled in (customer, insight, problem, value proposition, how it works, competitive context), each checked against a structural rule (presence, a 40-character content floor, and required phrasing), so my product story is complete in shape and ready to turn into a pitch.

You receive: A JSON object {productName, oneLineVision, frames: [{frame, content, ...frame-specific subfields}]} with exactly the six named frames. Frame-specific subfields: the insight frame carries a whys list (at least your minimum count), the problem frame a howMightWe question (exactly one 'How might we ...?' while the default toggle is on), the value-proposition frame a nowICan statement starting with 'Now I can', the how-it-works frame a steps list of exactly your chosen length, and the competitive-context frame a non-empty currentAlternative and differentiator.

Part of Pitch Investors

What's verified: STUD verifies structure against your frozen inputs: the submission parses as a JSON object and stays under 20,000 characters, exactly the six named frames are present (customer, insight, problem, value proposition, how it works, competitive context) with no duplicates or extras, every frame's content field is at least 40 characters after trimming (a length floor, not a quality read), productName and oneLineVision exactly match the values you provide (or must simply be non-empty if you leave either blank), the insight frame carries at least your minimum number of non-empty why levels, the value-proposition frame has a nowICan statement that starts with 'Now I can' and is at least 20 characters, the how-it-works frame has exactly your chosen number of non-empty steps, and the competitive-context frame names a non-empty current alternative and differentiator. The 'exactly one How might we ...?' problem-statement rule is enforced only while the single-problem-statement toggle is on (it is on by default; when off, any non-empty howMightWe passes). Both count settings must be between 1 and 9 or the submission is rejected. STUD does NOT verify substance or truth: not whether the customer is the right protagonist, whether the insight or its whys are true, whether the value proposition is compelling, or whether the story will resonate with any audience. The target customer, core problem, solution summary, and current-alternatives fields in the intake are context for the operator only and are never checked against the deliverable.

Opens soon

Cost20 credits
ProtectionHeld until verified delivery

This play is verified and ready. It opens soon, once sign-in and payments are live.

Example

A sample of what this play produces. Your result is generated for your inputs.

Product Name

STUD

One Line Vision

STUD is a living system for your venture: it knows your business, does the work, and learns from every result.

Frames

Framecustomer
ContentA solo founder building a venture wears every hat at once: marketing, finance, product, legal. AI was supposed to carry part of that load, and instead it handed them one more craft to master.
Frameinsight
ContentThe founder's bottleneck moved: the intelligence is available on demand, but the system around it (knowing what to ask, supplying context, keeping results current) is still assembled by hand for every single task.
Whys
  • Why does AI work drain founder time? Because every task starts from a blank prompt the founder must compose like an expert.
  • Why does the blank prompt cost so much? Because the founder has to re-explain the business from scratch in every session, and the answer comes back as text to rework by hand.
  • Why does nothing accumulate? Because the outputs land in chat threads and stale documents instead of a system that remembers and reuses them.
Frameproblem
ContentVentures run on knowledge work that is chosen, briefed, produced, checked, and filed. Today the founder does four of those five jobs by hand around the AI, and knowledge goes stale the moment it is written down.
How Might WeHow might we let a venture pick work that runs itself on knowledge that stays current?
Framevalue_proposition
ContentSTUD is a living system for the venture: pick a ready-made play, the intake fills itself from workspace facts, an AI agent runs the work, and the accepted result joins the workspace and improves the next run.
Now ICanNow I can pick a play, watch it run with my venture's facts already in place, and keep every result working for the next one.
Framehow_it_works
ContentThree moves stand between wanting a piece of work and having it: choose it, confirm what the workspace already knows, and receive a checked result that stays live in the system.
Steps
  • Pick a play from the catalog: a ready-made piece of work with the expertise and the checks built in.
  • Confirm the short intake, which your workspace facts have already filled in, and run it.
  • Receive a deliverable that passed the play's acceptance check, lands structured in your workspace, and feeds the next play you run.
Framecompetitive_context
ContentToday the founder threads the same needs through general-purpose AI chat assistants, freelance marketplaces, and documents that stop being true the week after they are written.
Current AlternativeGeneral-purpose AI chat assistants and static documents assembled by hand
DifferentiatorWork is chosen from ready-made plays and every accepted result compounds inside a living workspace

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