Every PR, story & PRD —
validated in seconds.
Baton probes the work your team and your AI agents produce — against your own ADRs and standards — and posts findings where you already read them. No files in your repos. Nothing new to learn on day one.
Your AI tools are single-player
Every major AI development tool was built for a single developer at a keyboard. When a team of twelve sits in a room to use it, eleven become spectators. The BA routes input through Slack. The architect can't inject constraints. The PM watches. And the context files in your repos? Advisory, stale, and silently ignored — researchers call it Context Drift, and it compounds into technical debt with no warning.
7.2%
reduction in delivery stability with AI adoption
DORA 2024
65%
of enterprise AI agent failures trace to stale context
Atlan 2026
19%
slower on real tasks despite feeling 20% faster
METR RCT
Start without changing a single workflow
No files deposited in your repos. No new tool to learn on day one. Baton meets your team where the work already happens — and gets stricter only as fast as you want it to.
Connect GitHub, Jira & Confluence
Every PR, story, and PRD is validated against your architectural standards within seconds of landing. Findings appear as PR reviews and ticket comments — where your team already reads.
Plug live context into your agents
One config entry connects Cursor, Claude Code, or Copilot to the Baton MCP server. Your agents pull current ADRs, standards, and story context at runtime — no stale files in any repo.
Enforce before the agent writes
Pre-edit hooks in Claude Code and Cursor require a Baton precheck before any file is modified. The agent cannot start work outside its defined scope — not asked, enforced.
Run workers under Constraint Objects
When you're ready, Baton-native workers execute stories under machine-enforced scope, rules, and stopping points — with human gates at every step.
How Baton works
The baton passes from role to role. Every handoff is constrained, validated, and logged.
Define
BA writes the story. Worker converts it to structured acceptance criteria with your architectural context loaded.
Business AnalystBuild
Workers execute under constraints. Developers review, not author. Every PR is bounded by scope, rules, and stopping points.
Development TeamShip
Validators challenge. Gates enforce. The full chain — from prompt to commit — is logged and auditable.
Entire TeamBuilt for teams that need to trust what ships
Every feature exists because we watched teams fail without it.
Constraint Objects
Before any worker runs, Baton generates a machine-readable specification that binds the agent to specific files, rules, and stopping points. Not advisory. Enforced.
Context Manifest
Every document the agent has loaded is visible before it starts. Stale ADRs are flagged amber. Missing standards block execution. The AI never works blind.
6 Human Gates
Requirements, design, code, tests, infrastructure, deployment. Every gate is non-bypassable. Validators run before every approval. No rubber-stamping.
Multiplayer Interruption
Any team member can comment on a card mid-execution. Add context, redirect the agent, ask questions, or escalate. Interruptions become organizational memory.
Active Validation Probes
Baton doesn't wait to be consulted. It probes every PR, story, and PRD the moment it lands — validated against your ADRs and standards, findings posted where your team already works.
Full Audit Trail
Every prompt, every response, every approval decision — logged with timestamp, author, and git commit hash. EU AI Act Article 12 enforcement begins August 2026. Baton is ready.
The board is the persistent memory
Every story, every constraint, every approval decision — visible to the whole team in real time.
Push reminders respect local timezone
Zero-state for empty dashboard
Meal swap shows offline error state
Recipe import navigates back on success
Feature tour slide index fix
Built from real observations
Baton was born from watching enterprise teams struggle with the same problem: powerful AI tools built for one developer, leaving the rest of the team on the sidelines.
Pass the baton.
Ship the software.
Start with probes on the work you already ship — zero workflow change. Grow into the execution layer where every role has a seat and every AI decision is auditable.