From Idea to Production with an AI Coding Agent
The eight-step loop behind every project on this platform: idea, research, PRD, architecture, tasks, agent sessions, review, deployment.
The steps look obvious written down; the value is in what each step produces before the next one starts. Skipping the paper steps is how AI projects turn into demo-quality code.
Idea
Write the problem in two sentences: who hurts, and how badly. If you cannot name the user, stop here; an agent cannot fix a fuzzy target.
Research
Check what exists: competitors, libraries, prior art in your own codebase. One hour here regularly deletes a week of building.
PRD
Turn the idea into a requirements document with explicit out-of-scope items. The PRD generator on this site produces a solid draft from a short form.
Architecture
Decide the stack, the data model and the module boundaries before generating any code. Blueprints on this site are worked examples of this step.
Tasks
Slice the build into tasks an agent can finish in one session, each with a definition of done. Outcome-sized, not "work on the app".
Claude Code
Run the tasks. Keep CLAUDE.md current, work in small diffs, and make the agent run tests after every change it makes.
Code Review
Review agent diffs like a colleague wrote them, because one did. Read the tests first; weak tests are where agent work quietly rots.
Deployment
Ship behind a pipeline: lint, tests, build, deploy. Agents make code cheap to produce, which makes verification the thing worth investing in.