cypress

A software factory
for production features.

The control plane for multi-agentic engineering — guidable, auditable, ready to ship.

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4 features in flight · 2 awaiting human decision · 1 ready to ship
Cypress factory floor diagram Four parallel feature production lines moving left to right through six stations — Code, Infra, Config, Security, Observability, Rollout — toward a Ready gate. Agents work at stations; humans intervene at inspection points. A faint graph of the control plane sits underneath. control plane · versioned graph 00 intent 01 code 02 infra 03 config 04 security 05 observability 06 rollout → ready FE-117 checkout v2 FE-118 rate limiter human · review FE-119 webhook retry agent · config-bot FE-120 audit log human · decide claude code oncall · canary verified in progress human pending
features in, features out. nothing on trust.

Agents can build.
They can't run a factory.

A diff isn't a feature. A feature is code, infra, config, security, observability, and rollout — coordinated. The gap is where teams improvise.

  1. i.

    Copilots assumed one developer. The frontier is many agents.

    Single-session tools don't compose. Run four agents in parallel and humans become the glue — chasing context across Git, Terraform, LaunchDarkly, Datadog, Slack.

  2. ii.

    Every feature is hand-assembled.

    Decisions and evidence scatter across tools and memory. The next agent — or reviewer — starts from zero.

  3. iii.

    No control plane. Just improvisation.

    What ships, what's safe, what's verified — all of it lives in Slack threads and heads. Add agents, improvisation scales. Trust doesn't.

  4. iv.

    Verification stopped meaning anything.

    96% of developers don't fully trust AI output. 48% verify it. Tests pass; production breaks. "Ready to ship" became a vibe.

Disconnected workstations today Disconnected workstations — Git, Linear, Slack, Datadog, Terraform, LaunchDarkly — each with a lone agent or human. Fragmented dotted feature outlines scatter across the canvas; no station connects to another. git main · 412 branches A linear CYP · 38 open H terraform plan: 17 changes A launchdarkly 114 flags H datadog p95 · 312ms H slack #deploys · 1.2k/d A ? ? ?
the work happens. the factory doesn't exist.

A factory floor
for production features.

A software factory has to do four things. We do them.

01

Guidable.

Every feature follows the same path: intent → code → infra → config → verification → rollout. Agents pick up at any station. Humans gate at any point. Nothing skips.

02

Auditable.

Every change carries its provenance: which agent, which approver, which checks, which evidence. The audit trail is the byproduct of the work.

03

Verifiable.

Production-readiness is computed, not vibed. Ships only when every check passes against real evidence — Terraform plan, canary metric, security delta.

04

Coherent at scale.

One versioned graph holds every feature in flight. Agents read from it. Humans gate against it. More agents = more payoff.

Shared factory floor with evidence graph Agents and humans on a shared floor moving features as discrete units through stations. Each station emits an artifact — plan, diff, metric, approval — into a graph layer below. A Ready gate at the right glows based on assembled evidence. ↑ factory floor ↓ evidence graph code + diff infra + tf plan config + flag set security + delta observability + canary rollout + approval ready all green A claude code A infra-bot H review A canary H approve diff #2410 +124 / −38 tf plan 17 changes flag set 5% cohort sec delta no new caps canary p95 −4% approval @kira one graph · one truth
features move. evidence accumulates. nothing ships on trust.

The control plane
underneath.

At the core: a versioned graph of every artifact and dependency in flight. Agents read it. Humans gate against it. Verification computes against it.

A.

Decoupled from execution.

Agents are the data plane — they write code, propose Terraform, set flags. The control plane sequences, verifies, ships. Same pattern that lets Kubernetes run thousands of pods.

B.

Policy and verification as code.

Define what "ready to ship" means: canary windows, security checks, approval rules. Enforced across every change, every agent.

C.

One source of truth, many surfaces.

Surfaces through tools you already use — PRs, CI checks, Slack, dashboards. No new tool to live in.

Three-layer architecture Top: data plane — coding agents and human IDEs. Middle: control plane — a versioned graph of code, infra, config, verifications, ready. Bottom: surfaces — PR checks, Slack, dashboard — all rendering from the same graph. data plane · execution claude code writes code cursor writes code infra agent tf plan human ide edits · review write artifacts read context · gates control plane · versioned graph artifacts + dependencies + decisions code v3 infra v8 config v2 verifications 6 / 6 passing ready ✓ render surfaces · one graph, many views github · pr #482 cypress · code ✓ cypress · infra ✓ cypress · canary ✓ cypress · ready ✓ slack · #deploys FE-118 awaiting decision security · review needed FE-117 shipped canary · p95 −4% dashboard · flights in flight 4 awaiting 2 shipped · 7d 14 p50 lead time 3.4h

Built for teams
running many agents.

If you're running Claude Code, Cursor, Codex, or custom agents in parallel — and feeling the coordination tax.

platform

Platform engineers tired of being the human glue between agents, CI, infra, and reviewers.

leadership

Engineering leaders scaling agent adoption without scaling production risk.

staff+

Staff+ engineers keeping the system coherent as the team ships faster.

Run more agents.
Keep the system intact.

If you're running multiple AI coding agents in production, we'd like to talk.

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