Hand Shipwright a ticket. Specialized agents — PM, architects, backend, frontend, QA, security, DevOps — take it through the real lifecycle and deliver a merged, tested change. Every step is inspectable and gated.
From a one-line ticket to a shipped, tested app — this is the exact path every mission takes, on repeat.
Scroll to walk through one real mission — from filing the ticket to the “shipped” notification.
Anthropic, OpenAI-compatible, local Ollama — or your own Claude Code CLI seat. Bind a model per agent, with failover and live metering.
GitHub, Jira, Slack, a real Chrome for QA. One click to connect — the team uses them the way your engineers would.
Describe the work in a line — “Build a notes app with an API and UI.” Pick an autonomy level and dispatch. That’s the whole ask.
The PM specs it, the CTO plans it, and engineers build their slices in parallel. Every step streams into the console as it happens.
Missions in flight, agents on shift, spend and tokens — the command center reflects reality in real time, no refresh.
Each slice is a card. It flows To Do → In Progress → QA → Done as the team codes, reviews, and verifies — evidence attached.
QA passes, the merge gate clears with your sign-off, it deploys — and you can boot the built app on a live URL to test it yourself.
Real screens from the running app. It plays on its own — or pick a screen to jump straight to it.
Single-agent coding tools and open-source agent harnesses put one agent in a loop that you babysit. Shipwright is a company — specialist roles, a real lifecycle, gates, and verification you can actually trust.
The QA harness runs the app’s own server, drives a real browser, and grades each acceptance criterion by behaviour — then halts rather than force-ship broken work.
PM, architects, engineers, QA, reviewer, and a CTO move work through a decision graph with escalation and rework — the way a real team converges, not one agent iterating alone.
Get pinged the moment a mission needs you, then approve a gate, answer a question, or check status right from Slack, WhatsApp, or email — no dashboard required.
Not a chatbot — a company. Providers, skills, memory, integrations, and guardrails, working together.
A full AI team takes a ticket through spec, plan, build, code review, QA, and ship — a decision graph, not a straight line.
Role-matched engineers build their slices in parallel git worktrees, then merge. Only the failing part rebuilds on rework.
The harness boots the app's own server, drives headless Chromium, and checks each acceptance criterion by behaviour.
Manual, assisted, supervised, or autonomous. Even autonomous can't force-push or auto-approve a risky merge.
Bind Anthropic, OpenAI-compatible, local Ollama, or your Claude Code CLI seat per agent, with failover and live metering.
Boot any shipped mission on a free localhost port and open it live — real API and UI, not a snapshot.
Opt-in alerts on Slack, WhatsApp, and email when a mission is blocked, needs approval, ships, or halts — reply to approve, reject, or ask for status without opening the app.
Select several repos — a service and its gateway — and prompt once. A new API gets wired into the gateway in the same run, under one review → QA → ship gate.
The org keeps a reusable skill library and a workspace memory it recalls into new missions — so decisions stay consistent across the codebase.
Each agent owns a role and a model binding, collaborates through a shared ledger and memory, and reports every action.
Set a default for the workspace and override per mission. Higher levels ask for fewer confirmations — the guardrails always hold.
The team proposes every step and waits for you.
Drafts spec & code; you approve each phase.
Builds & tests autonomously; merge & deploy wait for your sign-off.
Ships end-to-end within the guardrails you set.
Explore the code, run it locally, and watch the team take a ticket from intake to a merged PR.