Plans before it builds
Before touching code, Build investigates the current state of your codebase and everything already planned, so new work never conflicts with or duplicates what's in flight.
BuildState the goal · Ship the feature
You state the goal. Build ships the feature.
Interactor Build is AI that continuously improves your product. Tell it what your customers want, in plain language. AI agents plan, build, test, and review every feature — and nothing is released without your engineer's approval.
We build Build with Build: from request to released feature in ~4 hours, median, on our own product.
The problem
Vibe coding is still coding.
AI made writing code faster — but someone still sits in front of a computer all day, prompting it line by line. As a founder or product owner, that someone shouldn't be you. Your customers are waiting on features. Your roadmap is tied to revenue. And the feature lifecycle is still so long that you get a handful of iterations a year — half-baked features ship, nobody uses them, and the people who actually talk to customers still can't touch the product.
Build changes what you ask for. You don't describe the code you want written. You state the goal — what your customers need — and AI agents do the rest. The gap between the person who owns the product and the codebase finally closes.
Iteration compounds. Improve 1% a day and the product is 36× better in a year. The bottleneck was never ideas — it's the lifecycle.
What it is
An AI product team — not a coding assistant.
Build is made for product owners, founders, and PMs — no coding required. Think of it as GitHub for product management: one shared place where your team collaborates on what gets built, sees what has been built, and watches the product improve every day.
Finds everything a change touches
Ask to change one feature and Build follows it through everything it touches — help pages, tutorials, docs — so the whole product stays consistent, not just the code.
Tested before you ever see it
Every feature ships with a full test suite and coverage. Deliberately slower per feature, dramatically less likely to break.
Your engineers hold the gate
Nothing is released without an engineer's approval. Build does the building, testing, and reviewing; your team keeps final say.
Never loses its place
Runs are stateful. If a machine crashes or a rate limit hits, work resumes exactly where it left off — and merge conflicts are resolved automatically.
How it works
From request to release, in five steps.
The Build loop
01
State the goal — In plain language: “Customers keep abandoning checkout — let them pay without creating an account.” Goals, not specs. No tickets, no code.
02
Build investigates — It reads the current code and everything already planned, then comes back with a plan you can read and approve.
03
Agents build, test, review — A fleet of AI agents writes the feature, builds the test suite, and reviews the work — with the right model on each phase: deep-reasoning models for planning, fast models for execution.
04
Your engineer approves — The result arrives as a finished, tested, reviewed change. Your engineer approves it or sends it back with a comment.
05
Released — everywhere it matters — The feature goes live, and every doc, help page, and tutorial it touches is updated in the same release.
The obvious question
“Can't I just use Claude?” Claude is the engine. Build is the factory.
If you're a Claude power user, you already know the drill: plan on the strongest model, execute on the fast one, restart after every rate limit, re-explain context after every crash, and watch tokens disappear into stale context. Build does all of that in software. Orchestration, retries, and restarts are handled by code — not by burning tokens. Context is optimized per task and stale context is never carried forward, so the same work uses far fewer tokens. And when you do work side-by-side with Claude, the day disappears. Hand the work to Build instead — and spend those hours with customers and stakeholders.
Software-run orchestration
Tokens go to building, not babysitting.
Optimized context
No stale context carried between tasks.
Fleet-managed restarts
Rate limits and crashes never lose work.
Your product could be improving right now.
One goal, stated in plain language, is enough to start.