AI-driven product development in twelve phases. Twenty eight days of focused work for an experienced team, longer for first timers. This is the operating rhythm behind every AI Implementation we run, refined across a decade of mid market engineering.
The whole speed advantage of AI driven build collapses if the brief is fuzzy. The Plan movement is short by design, but it is where ninety percent of the engineering decisions actually happen. Skip it and you debug your spec in production.
Problem framing, user interviews if needed, kill criteria. We name the smallest version of the product that proves the bet before we touch a tool.
Sharp written PRDs per surface, edge cases listed, acceptance criteria explicit, success metrics defined. This is the meatiest phase of Plan because every later phase reads from it. Fuzzy here means fuzzy everywhere, so we take the time to make the contract real before any code is written.
Tokens, type, components, layout primitives. Half a day, not two weeks, because we are codifying constraints for the AI build, not redesigning the wheel.
With a sharp spec and a tight design system, the actual code is the easy part. Five phases, roughly two weeks of focused work. The order is deliberate: frontend first so the spec proves itself in pixels before backend complexity lands.
The biggest single phase. We build the interface against fixtures first so the PRD proves itself before backend work begins.
Endpoints, schema, jobs. Short because the contract was already nailed down in the PRD and exercised in the frontend.
Replace fixtures with real endpoints, integrate auth, plug in third party APIs. Where most build phases bog down. Ours doesn't because the contract held.
The honest day. Real users, real edge cases, real timing bugs. We budget for it because pretending it isn't there is how schedules slip.
Microcopy, empty states, error states, loading states, motion. The difference between something that ships and something people actually use.
Shipping is not deployment. It is hardening, refactor, deploy, and the maintenance posture that starts the day after launch. Most teams treat phase 11 as the finish line. We treat it as the start of phase 12.
Security pass, rate limits, input validation, secrets audit, observability. The unglamorous day that prevents the glamorous incident.
The last pass at the parts you knew you'd come back to. Now the spec is final, the code can be made coherent rather than just correct.
Infra, CI, staging, prod, DNS, observability dashboards, rollback plan. Boring on purpose. The boring part is what stays up at 3am.
Patches, dependency drift, schema migrations, on call. The phase no one wants to talk about, which is exactly why it kills more products than any other.
Fuzzy PRD, fuzzy software. Sharp PRD, shippable software.
AI driven build only collapses months into days if the brief is crisp. A team of agents will move very fast in whatever direction you point them. The point of phases 1 to 3 is to point them at the right thing before a single line of code is written.
This is where most teams trying to ride the AI wave stall. It is not the tooling, the model, or the framework. It is the spec. The teams that ship are the teams that learned to write PRDs that survive contact with real users and real data.
BMAD style multi agent setups make this concrete. Each role has an owner, each artifact has a producer. The brief is no longer a wiki page, it is a contract.
For an experienced builder. Longer for first timers. Each phase has an honest estimate so the team plans calendar time, not hopeful hours.
Start with AI Diagnose for a written plan you keep. Or book a thirty minute call if you want to scope an Implementation directly.