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Value proposition canvas
A complete value proposition canvas for your product as a six-section JSON document: each section meets its minimum entry count, every entry is a phrase of at least two words, no section repeats an entry, and the products and services list stays distinct from the pain relievers and gain creators.
You receive: JSON document with six top-level keys: customerJobs, customerPains, customerGains, productsAndServices, painRelievers, gainCreators. Each is an array of strings; every entry is a non-empty phrase of at least two words, and no entry repeats within a section. When derived from a source enhanced business model canvas, an optional additions array lists the entries that are new relative to the source.
Part of Get First Users
What's verified: STUD verifies the deliverable parses as a JSON object with all six canvas sections present as arrays (customerJobs, customerPains, customerGains, productsAndServices, painRelievers, gainCreators), that every entry is a string and reads as a phrase of at least two words after trimming, that each section meets its minimum count of qualifying entries (your intake settings, defaults 3 for customer jobs, pains, and gains, 2 for products and services, pain relievers, and gain creators; blank or one-word entries never count toward a minimum), that no section repeats an entry (ignoring case and surrounding spaces), and that no products and services string reappears in painRelievers or gainCreators (ignoring case and surrounding spaces). Derivation mode: when you supply a source canvas in the optional sourceCanvas field (it pre-fills from your accepted enhanced business model canvas run when you have one), three further checks run: the source must parse as an enhanced canvas with value_proposition and customer_segments boxes; every entry must either appear verbatim in the source's mapped box (customer jobs, pains, and gains against the customer segments box; products and services, pain relievers, and gain creators against the value proposition box; ignoring case and surrounding spaces) or be listed in the deliverable's additions array; and every additions entry must appear in a section. Leaving sourceCanvas blank keeps the contract exactly as above. Checks run in order, and a structural failure (a deliverable that does not parse, or a missing or mistyped section) stops the run there, so the verdict names only the checks that ran. STUD does NOT verify that entries are true, insightful, or well matched to the product, customer segment, or notes you give in the intake (those brief the operator and freeze into the order without being machine-checked), does NOT verify that the pasted source canvas matches any particular past run, and does NOT judge whether an addition is a good idea: an addition only has to be labeled.
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Example
A sample of what this play produces. Your result is generated for your inputs.
Value Map
Customer Profile
Gain Creators
- Each accepted result feeds the next play
- The workspace compounds the venture's knowledge
- Checked delivery makes results safe to use immediately
Gains
- Work that starts itself from what the venture already knows
- A workspace that gets smarter with every run
- Results ready to use and reuse without rework
Products & Services
- A catalog of ready-made plays run by AI agents
- A workspace fact store that pre-fills every intake
- Structured deliverables checked before they land
Customer Jobs
- Get marketing, finance, and product work done while staying small
- Keep the venture's facts and plans current
- Turn a stated outcome into finished work
Pain Relievers
- Plays replace prompt writing with picking
- Facts stated once flow into every run
- Results land structured and stay current
Pains
- Every AI session starts from a blank prompt and zero context
- The same company facts get re-explained in every tool
- Finished work goes stale in documents and chat threads
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