Design an API on its contract instead of discovering it endpoint by endpoint — model the resources, design the endpoints and payloads, pin the contract, then review it before code locks it in.
An API designed endpoint-by-endpoint as you code becomes a contract you can't change — clients depend on every accident, and the inconsistencies calcify into a permanent surface you maintain forever. The expensive decisions are made up front: what the resources are, how the endpoints map to them, what the payloads and validation rules look like, how errors and versions behave. 'Ask AI to write the endpoint' skips all of that and hands you the first plausible shape. This workflow designs the API as a contract first — resources, endpoints, payloads, versioning — and reviews it before code makes it permanent.
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.
Model the resources and boundaries
Before endpoints, name the resources the API exposes and where its boundaries sit. Anchor the model as an architect so it reasons about the nouns and their relationships, not the first route that comes to mind.
Design the endpoints, payloads, and validation
Work the design one decision at a time: which endpoints each resource needs, the request and response payloads, the validation rules, and how errors are shaped — consistently across the whole surface, not per-route improvisation.
Pin the contract and versioning
Turn the design into a precise contract — request and response schemas, error formats, and a versioning rule — so clients build against something stable instead of whatever the implementation happens to return.
Review the design before it's code
Run the design past a review lens — consistency across endpoints, error handling, breaking-change risk, missing validation — while it's still cheap to change, because once clients depend on it the contract is fixed.
An API designed as a contract before implementation — resources modeled, endpoints and payloads decided, request/response schemas and versioning pinned, and the whole surface reviewed for consistency — so you build against a deliberate design instead of hardening accidents into a contract clients can't escape.
Architecture decides the system's overall structure — services, boundaries, data flow. This workflow zooms into one surface: the API contract, walking resources, endpoints, payloads, versioning, and a design review. Set the architecture first, then run this to design the APIs that live inside it.
Design the API contract first with this workflow, then model the data behind it with the AI Database Design Workflow. The endpoints clients depend on and the tables they never see are distinct artifacts that inform each other — but let the contract you're committing to lead.
No. It structures the resource model, surfaces inconsistencies, and pressure-tests the contract so your design is deliberate. The API decisions — and the compatibility promises you make to clients — stay yours.
A pinned API contract: named resources and boundaries, endpoints with request and response payloads, validation rules, error formats, and a versioning rule — reviewed for consistency and gaps before code locks it. You build against this deliberate design instead of hardening accidents into a contract clients can't escape.
Work the four steps in your own AI tool: anchor an architect role to model resources and boundaries, design endpoints, payloads, and validation one decision at a time, pin the request/response schemas and versioning rule, then review the whole surface. NewPrompt supplies each step's prompt and links; you run them.
Step four runs the design past a review lens — consistency across endpoints, error handling, breaking-change risk, missing validation — while changes are still cheap. The prompt and API review checklist surface gaps, but confirming the contract is sound and safe to commit to clients is your call.
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 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 automation that survives the real world — wire the integrations and triggers, design the control API, move the data through validated stages, evaluate the AI steps, then deploy.
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.
The full path to a pipeline that moves data without corrupting it — design the ingestion and transforms, extract and structure the sources, gate the quality, store it, then deliver and ship it monitored.
Code you can refactor on a quiet afternoon. A field you shipped is somebody else's dependency — you don't fix it, you version it. What an hour of contract review buys: method semantics, a truthful error model, retries, authorization, and compatibility you didn't mean to promise.
Design a schema on its data, not a hunch — model the entities and relationships, set the constraints that protect integrity, plan indexes around real queries, then document the schema and migration.
Design a system's architecture on its real trade-offs instead of a confident diagram — put the model in an architect's seat, work the decisions one at a time, and write down the why.
Connect systems so they don't break each other — map the integration boundaries, design the event and webhook contracts, plan retries and failure handling, then document the integration.