Follow push to verified live
One call tracks CI, merge, artifact, deploy, and health — no polling, no stitched-together status checks.
Product features
The CI/CD pipeline your agent can operate, end to end.
Agentic Pipeline tests every push and ships every merge. These are the features behind that loop: live evidence while runs execute, MCP control for AI coding agents, safe pipeline evolution, and agentic workflows that end at verified live — not just at a green check.
Agent control
Your agent operates the run.
The control surface is MCP-native: explicit, typed tools your coding agent calls from the session it already works in.
Screenshot — slipstream_follow timeline inside an agent sessionimage placeholder
Live resumable logs
Agents inspect evidence while the run executes and resume mid-stream without replaying the whole log.
Structured failure diagnosis
A red run comes back as a failing stage, an evidence tail, a classification, and a next action.
Safe reruns
Restart exactly the failed work. Deploy reruns always ask before touching production.
Prewarm before push
Agent intent wakes compute before GitHub emits the push, cutting cold-start wait.
Durable task recovery
Long delivery journeys survive client disconnects: reconnect with the same task and keep following.
MCP-native control surface
Works from Codex, Claude Code, Cursor, and any MCP-capable agent — with truthful terminal states.
Fast feedback engine
Feedback while it still matters.
Speed comes from doing less work, in the right place, at the right time — and always showing why.
Screenshot — run DAG with change-scoped skips and parallel stagesimage placeholder
Warm persistent workspaces
Repository state persists between runs, so pushes skip the rebuild-from-zero tax.
Change-scoped stages
Only the checks your change affects actually run — and every skip states its reason.
Parallel DAG execution
Independent checks run concurrently; dependencies stay explicit, not implied.
Shared build and test cache
Work done once is reused across machines and runs — fewer repeated installs, builds, and tests.
Warm-first routing
Work lands on the executor most likely to already hold the useful repository state.
Resource-aware scheduling
CPU, memory, and exclusivity match the workload, so contention never masquerades as a failing test.
Bounded feedback loops
Hard ceilings fail fast. Stuck work is stopped and classified instead of consuming your agent's attention.
Safe pipeline evolution
Change the pipeline like code.
The pipeline is a contract in your repo — read, validated, sandboxed, and promoted by pull request.
Screenshot — recipe validation and a guarded sandbox run resultimage placeholder
Read the effective recipe
Agents see the exact delivery contract that will run, including inherited defaults.
All-errors validation
Every recipe problem in one pass — not one edit-run-error cycle per issue.
Guarded sandbox runs
Test pipeline changes without ever touching the production required check.
Dry-run change preview
See exactly what a promotion will change before it mutates anything.
PR-only recipe promotion
Pipeline changes get the same review and audit trail as application code.
Recipe insights and recommendations
Evidence-backed suggestions to cut redundant work and shorten the critical path.
Build and ship
Green means verified live.
The journey doesn't end at a check. It ends when the intended version is serving, healthy, in production.
Screenshot — push-to-live journey: CI → artifact → deploy → healthimage placeholder
GitHub required check
Pull requests, reviews, and branch protection stay exactly as your team knows them.
Artifact-first delivery
Build once, record the digest, promote the same artifact — deploys never rebuild.
Ship on green
A green main run starts the reviewed, repo-owned deploy contract automatically.
Health and version verification
Confirms the intended version is actually serving after deploy — evidence, not assumption.
Change-scoped deploys
Unaffected services are skipped with the reason stated — live, no-op, or CI-only, truthfully.
Fleet operations
See where every minute goes.
One workspace for humans, one truth shared with agents: the same timeline, the same evidence.
Screenshot — speed insights: p50/p95, slow stages, critical pathimage placeholder
Live runs workspace
Search, filter, and inspect run DAGs, timing, logs, and recovery actions in one place.
Push-to-live fleet view
Delivery state across every repository — not a wall of checks that stops at CI.
Speed and critical-path insights
p50/p95, slow stages, regressions, and where time is actually spent.
Capacity and machine state
Queue depth, warm capacity, active machines, and scaling behavior at a glance.
Cache effectiveness
Whether cached work actually shortened the loop — hits, misses, and time saved.
Agent activity and MCP usage
Which control operations agents use and where their workflows stall.
Platform health and alerts
Distinguishes your repo failing from the delivery platform degrading.
Tenant-safe fleet access
Platform owners get fleet control; tenants see only their own repository evidence.
Onboarding
Connected in one sitting.
No code moves. Install the GitHub App, keep the recipe in your repo, connect your agent.
Screenshot — MCP install commands and the readiness checkimage placeholder
GitHub App connection
Connect repositories and post the required check without moving your code hosting.
Self-serve readiness check
Know what's missing before the first production run — as machine-actionable blockers.
One-click MCP installs
Ready-to-run install commands for Codex, Claude Code, Cursor, and VS Code.
OAuth, passkey, and org access
A secure dashboard entry for humans, with organization boundaries preserved.
Tests every push · Ships every merge
Open dashboard Put every feature behind your agent.
Install the MCP server, connect one repo, and follow the first push to verified live.