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Build an Idea Resume (internal innovation pitch document)
A complete, well-formed idea-resume JSON document with all four required sections (problem, idea, evidence, investment case) populated to the buyer's minimum-evidence and ROI thresholds, ready to hand to a decision-maker.
You receive: A JSON object: { idea_title, problem: { statement, causes[], effects[], evidence_points[] }, idea: { summary, implementation_path[], ideal_result }, evidence: { data_points[ {label, value, unit, source_type} ], external_validation[] }, investment_case: { company_benefits[], people_benefits[], cost_estimate {amount, currency, basis}, expected_return {amount, currency, basis}, roi_ratio } }
Part of Pitch Investors
What's verified: STUD verifies that the idea resume is structurally complete, hits the buyer's evidence/cause/step minimums, has well-formed money fields, and that the stated ROI ratio is arithmetically consistent with cost and return. STUD does NOT verify that the data points are true, that the idea is actually good, that the ROI is realistic, or that the boss will be persuaded.
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.
Idea title
Onboarding as a play: state your venture once
Problem
StatementSTUD sells a living system that knows your business, does the work, and learns from every result, yet every new buyer lands in an empty workspace. Their first intake asks them to type everything about their venture by hand, which is the exact blank-page problem STUD exists to remove. In our illustrative launch scenario only 40 of 200 signups activate in month 1, and the first five minutes are where we lose them.
Causes
- A new workspace holds zero facts, so the first play's intake cannot fill itself and the buyer types every field cold.
- Onboarding is a tour, not a run: nothing the buyer does before their first commissioned play leaves structured facts behind.
- The catalog's 265 plays all assume workspace context exists; none of them is responsible for creating it.
Effects
- In the illustrative launch scenario only 40 of 200 signups activate in month 1, and only 25 remain by month 3.
- The first session shows the buyer a blank form instead of the living system the pitch promised, so the compounding loop never starts.
- Content-led acquisition spend (illustrative blended CAC about 40 dollars) is spent on signups who never reach a first result.
Evidence points
- Launch signups (illustrative scenario)
- Activated buyers in month 1 (illustrative scenario)
- Retained buyers at month 3 (illustrative scenario)
Idea
SummaryMake onboarding itself a play: State your venture once. The buyer's first run is a guided capture whose deliverable is their starter fact set (name, one-liner, what it does, target customer, pricing, stage), landed as structured workspace facts, the same store every later intake reads. The second play they open fills itself, which makes the living-system promise true in the first session instead of asserted in the copy. We choose this over adding more catalog supply because 265 plays already exceed what an unactivated buyer will ever see; the binding constraint this quarter is the first five minutes, not the shelf.
Implementation path
- Author the State-your-venture-once onboarding play: a short guided intake whose deliverable is the buyer's starter fact set.
- Route the deliverable's fields into the fact store when the run lands, so the run itself populates the workspace and there is nothing to copy by hand.
- Make it the default first action for a new workspace: the empty state opens this play, priced at the low end of the 10 to 40 credit range.
- Show the payoff immediately: once the facts land, surface three recommended plays whose intakes now display as pre-filled.
- Instrument the funnel: signups, onboarding runs completed, second play run in session one, month-1 activation, month-3 retention.
Ideal resultA new buyer's second play intake fills itself within their first session, and month-1 activation in the launch cohort model moves from 20 percent toward 30 percent.
Evidence
Data points
| Label | Value | Unit | Source type |
|---|---|---|---|
| Launch signups (illustrative scenario) | 200 | signups | internal_data |
| Activated buyers in month 1 (illustrative scenario) | 40 | buyers | internal_data |
| Retained buyers at month 3 (illustrative scenario) | 25 | buyers | internal_data |
| Live catalog size | 265 | plays | internal_data |
| AI agents market size, 2025 (cited external estimate) | 8 | billion USD | market_research |
External validation
- The AI agents market is about 8 billion dollars in 2025, growing 42 to 50 percent CAGR (cited external estimates): the buyers exist, and the gap is first-session activation rather than demand.
- Every alternative a buyer compares us to (general-purpose AI chat assistants, freelance marketplaces, static documentation tools) starts each engagement from a blank context, so a first session that ends with a self-filling intake is a visible difference.
Investment case
Company benefits
- More of the same acquisition spend converts: at an illustrative blended CAC of about 40 dollars, each additional activated buyer is recovered spend at an estimated 87 percent gross margin (modeled 85 to 90 at launch prices).
- The fact store fills at signup, so every later run starts smarter: the compounding loop that is the product's whole thesis begins on day one.
- Retention compounds from a larger activated base: the illustrative model holds month-3 retention at 62.5 percent and moves activation, the cheaper lever.
People benefits
- The founder-operator's concierge capacity (30 plays a week in the launch model) stops being spent walking new buyers through blank forms.
- New buyers reach a first useful result in one session instead of abandoning at an empty intake.
Cost estimate
Amount6000
CurrencyUSD
BasisIllustrative: about three weeks of contract engineering at 40 hours a week and 50 dollars an hour to author the onboarding play, wire deliverable fields into the fact store, and instrument the funnel. This is a model for decision purposes; no budget is committed and entity formation is pending.
Expected return
Amount18000
CurrencyUSD
BasisIllustrative model, not a forecast: lifting month-1 activation from 20 to 30 percent on monthly cohorts of 200 signups adds about 12 month-3 retained accounts per cohort at the scenario's 62.5 percent retention. Ten post-build cohorts yield 120 incremental accounts averaging half a year of revenue in year one at the illustrative 300 dollars annual revenue per account: 120 x 300 x 0.5 = 18,000 dollars.
Roi ratio3
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