Turn a fuzzy business need into requirements a team can build from — interrogate the need into concrete requirements, shape them as user stories, and write the PRD.
'Build me a dashboard' means five different products to the five people in the room, and the gap doesn't surface until someone's built the wrong one. Requirements are the boring document that prevents that — the concrete statement of what the product must do, for whom, and how you'll know it's done. The trap is treating a one-line ask as if it were a spec. This workflow puts an assistant to work interrogating the need into real requirements, shapes them into testable user stories, and writes the document the team can build from and argue against.
Each step uses an existing NewPrompt tool, pre-filled by a matching resource. Open the resource to read it, or jump straight into the tool with the inputs ready.
Interrogate the need into requirements
Set up an assistant whose job is to pull a fuzzy business need apart into concrete requirements — asking the who, what, why, and edge cases — instead of nodding along to 'build me an X'.
Shape them as user stories
Turn the requirements into structured user stories — as a role, I want a capability, so that an outcome — with the variable parts explicit, so each one is testable and assignable rather than a vague wish.
Write the requirements document
Assemble the stories, constraints, and acceptance criteria into a product requirements document the team can build from — not a paragraph that means something different to everyone who reads it.
A vague business need becomes a written requirements document — concrete user stories, constraints, and acceptance criteria — so the team builds the same product instead of three different ones from the same sentence.
Use this one to define WHAT the product must do — the full set of requirements, user stories, and acceptance criteria. Use MVP Planning after, to cut that set down to the slice that ships first. Requirements come first; the MVP is a prioritized subset of them.
Requirements state what the product must do; architecture decides how you'll build it. Run this workflow first — its PRD and user stories become the input the AI Project Architecture Workflow designs against. WHAT before HOW, and the same requirements also feed the MVP cut.
No — it interrogates the need you bring and structures the answers. The product decisions stay yours; the workflow makes them explicit, testable, and written down.
A written product requirements document (PRD). Step 1 interrogates the need into concrete requirements, step 2 shapes them into testable user stories (as a role, I want a capability, so that an outcome), and step 3 assembles stories, constraints, and acceptance criteria into a PRD the team builds from.
Work the three steps in your own AI tool: use the system-prompt-generator to set up a requirements-interrogating assistant, the prompt-variable-builder to shape user stories, and the markdown-output-builder for the PRD. NewPrompt supplies the prompts and step order; you run each prompt and own the final document.
Bring the business need or product idea and its context — who it's for, the problem, and any known constraints. Step 1 questions that raw need into concrete requirements. You don't need a spec; the workflow builds one from what you supply, so vaguer input just means more interrogation.
Complete build journeys that include this workflow as a stage.
The full path from idea to a shipped SaaS MVP — define and scope the requirements, design the architecture, API, and data model, then build it reviewed, tested, secured, cost-controlled, and deployed.
The full path to an AI document processing system — define the use case, design the intake pipeline, extract fields from unstructured documents, classify and route them, pin the output contract, evaluate accuracy, then ship it monitored.
The full path to an AI content moderation system — define the policy and label taxonomy, extract signals from user content, classify it against policy, emit structured decisions, evaluate false positives and negatives, wire enforcement and review queues, review abuse risks, then ship.
The full path to an AI research assistant — define its scope, organize the source corpus, ground responses in references, extract key facts, synthesize findings, check groundedness, then validate it for use.
The full path to an AI meeting assistant — define the use case, turn transcripts into structured notes, extract decisions and action items, classify follow-ups, write a shareable summary, evaluate accuracy, then ready it for the team.
The full path to a backend you can put clients on — define the requirements, design the architecture, API contract, data model, and access control, then build it reviewed, tested, secured, and shipped.
The full path to an applicant tracking system — model jobs, candidates, and hiring stages, generate job descriptions and screening prompts, parse résumés into structured data, design the hiring API, set roles, review security, then ship.
The full path to a booking and reservation system — model resources, availability, and reservations, design the booking API, set customer accounts, wire calendar and notification integrations, design the UI, review security, then ship.
The full path to an inventory management system — model products, stock, locations, and movements, design the inventory API, set roles, plan supplier and POS integrations, design the UI, review data-integrity risks, then ship.
The full path to an internal admin panel — model the operational data it manages, design the management API, define RBAC and admin permissions, design the tables and forms, review risky admin actions, then ship to trusted internal users.
The full path to a two-sided platform — define the buyer-and-seller requirements, model the data, design the API, build roles and permissions, wire integrations, design the UI, then test, secure, and ship it.
The full path to a CRM that fits your sales process — define the contacts, deals, and pipeline, model the data that ties them together, then build the roles, integrations, and pipeline UI, and ship.
The full path to a store you own end to end — model the catalog and orders, design the storefront and checkout, add customer accounts and payments, then secure it, test it, and ship.
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