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Why-now three-forces trendcasting register
A three-forces 'Why now?' register for your named idea: exactly one economic, one social, and one technology force, each a distinct change with a cost/demand-marker-tagged impact, plus a market-window statement in recency language.
You receive: A JSON object { ideaName, forces: [ { forceType, change, impactOnCostOrDemand } x3 ], marketWindowStatement }, at most 20,000 characters. forceType must be exactly one each of: economic, social, technology. Each impactOnCostOrDemand must contain at least one of the exact markers: cost, price, demand, customers, margin, revenue, %, percent, $. marketWindowStatement must contain at least one of the exact markers: now, window, recently, just, emerging, opened, this year.
Part of Pitch Investors
Example
A sample of what this play produces. Your result is generated for your inputs.
- Idea Name
- STUD.com
- Market Window Statement
- The window is open now. The AI agents market is about $8B in 2025 and growing 42 to 50 percent a year on cited external estimates, agent-run work is emerging as a default buying category for small teams, and the compounding advantage goes to whichever system becomes a venture's living memory first: every month a workspace accumulates facts and results is a month a later entrant cannot replay. STUD is moving through that window now, pre-seed and in soft launch, with 265 live plays across 14 playbooks already running the pattern.
| Force Type | Change | Impact On Cost Or Demand |
|---|---|---|
| economic | The price of finished knowledge work collapsed: a complete structured deliverable from an AI agent now runs 250 to 1,000 credits per play ($10 to $40 at STUD's $0.04 credit peg, most plays 500 credits or $20), well below what the same brief costs when bought as human hours on a freelance marketplace. | Drops the marginal cost of a finished deliverable to about $20, charged only when a run is accepted, so work a lean team used to defer or batch into a contractor budget becomes routine demand: a $20 to $200 prepaid credit pack that never expires now funds a standing operating cadence rather than a single outsourced brief. |
| social | Staying small stopped being a compromise and became the plan: solo and early-stage founders and small product teams now expect to cover marketing, finance, product, and engineering themselves with AI in the loop, and handing a defined outcome to an agent now reads as normal working practice. | Grows the pool of customers who arrive already intending to buy outcomes rather than hours, and moves demand away from adding headcount toward a system that holds what the business knows and does the work, which is exactly the purchase a catalog of ready-made plays serves. |
| technology | AI models crossed the line where an agent can carry real knowledge work end to end, yet getting that work out of a blank prompt is still manual craft: you re-explain the business every session and carry outputs by hand, so a workspace that remembers, plus plays that run from a short intake, became buildable this year. | Turns one-off prompting into compounding capability: a fact stated once flows into every run and each result leaves the system knowing more, so deliverable quality rises at a flat cost per play and a venture's spend compounds with its workspace instead of resetting to zero each session. |
Opens soon
STUD opens runs for everyone soon, on every play at once.
Scope of the check
What's verified: STUD verifies the deliverable is a JSON object of at most 20,000 characters whose ideaName is non-empty and matches your idea name (case-insensitive), with exactly three forces (one each of forceType economic, social, technology), each change non-empty, pairwise distinct (case-insensitive), and at least the minimum word count (your setting, default 6, clamped to the 3 to 60 range), each impactOnCostOrDemand containing at least one of the exact markers: cost, price, demand, customers, margin, revenue, %, percent, $, and a marketWindowStatement containing at least one of the exact markers: now, window, recently, just, emerging, opened, this year. These marker checks are exact-word presence checks, not meaning checks. STUD does NOT verify the forces are factually real, correctly classified, or economically sound, that the stated impacts or window are true, or that marker words are used meaningfully. The product-description and target-customer intake fields inform the operator and are not machine-checked.
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