Build an API Backend with AI
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.
Overview
A backend is the part of a product clients build against and can't easily walk back — every endpoint shape, every table, every auth assumption becomes a contract the moment something depends on it. This blueprint builds that backend deliberately, and only the backend: no UI, no marketing site, just the API and the system behind it. It runs the real path an experienced team takes — pin down what the API must do, decide the architecture, design the contract and the data model before writing them into code, then build with the discipline that keeps a backend trustworthy: reviewed, tested, security-checked, and shipped with a rollback. Each stage is a NewPrompt playbook you can run on its own; together they carry an API from a requirement to a running service clients can depend on. You write the code and own the calls; the blueprint makes sure the load-bearing decisions happen in the right order.
The journey
Each stage runs a NewPrompt playbook, with a supporting resource and tool. Work them in order — the output of each stage feeds the next.
-
Define what the backend must do
Before any design, turn the need into written requirements — the operations the API exposes, the rules, the acceptance criteria — so the whole build aims at the same target.
Outcome Requirements the backend build can start from.
-
Design the architecture
Decide how the backend is structured — boundaries, data flow, the trade-offs that are expensive to reverse — and write the decisions down before the first line of code.
Outcome An architecture decided on its trade-offs and documented.
-
Design the API contract
Pin the surface clients depend on — resources, endpoints, payloads, validation, and a versioning rule — as a contract before code makes it permanent.
Outcome An API contract clients can build against.
-
Design the data model
Model the entities, relationships, and constraints behind the API, and plan the indexes the real queries need — the schema is the hardest thing to change later, so design it on its data.
Outcome A schema designed on its entities, constraints, and queries.
-
Design auth and access control
A backend's endpoints are reachable, so decide how callers prove who they are and what each may do — authentication, roles, and permissions — and review the design for gaps before the endpoints exist to exploit.
Outcome An access-control model designed and reviewed before build.
-
Review the code as you build
As endpoints land, review them against your conventions with severity-ranked findings — so the backend doesn't accumulate the debt that makes the next version miserable.
Outcome Changes reviewed for correctness and design before they merge.
-
Lock behavior down with tests
Build a test suite that fails for real reasons across unit, integration, and edge cases — so you can keep shipping endpoints without breaking the ones clients already use.
Outcome Tests that catch real regressions in the API.
-
Run a security review
A backend is the exposed surface and the data behind it. Review the auth and input paths the way an attacker would, and back the findings with tests, before it's reachable.
Outcome Exposed paths reviewed for vulnerabilities and guarded by tests.
-
Ship it to production
Cross the gap between tested and live — assess release readiness, plan the deploy and its rollback, and set up monitoring — so the backend goes into production deliberately, not hopefully.
Outcome The backend shipped with a rollback path and monitoring.
Expected outcome
An API backend designed before it was built and built with discipline — requirements pinned, architecture and contracts decided, the data model deliberate, and the code reviewed, tested, security-checked, and shipped with a rollback — a service clients can build against instead of a set of endpoints that hardened by accident.