AI made writing code trivial.
Getting it to production is still brutal.
We fixed the second part.
Your AI agent can ship a feature in 20 minutes. Then you spend three weeks gluing GitHub Actions, IAM policies, CloudFormation, secret managers, observability dashboards, and rollback runbooks before any of it sees a user.
StrictOps gives you a working pipeline on day one — three real environments (dev / stage / prod) provisioned in your own AWS account, owned by you, with the safety rails a real production system needs.
No CloudFormation. No Dockerfiles. No YAML hell. Just push code, ship code.
Built for builders,
not infrastructure experts.
Three things StrictOps does that your AI editor can't — and that you really don't want to learn yourself.
AI-native workflow
Claude opens a PR → GitHub runs checks → it flows through dev, then stage, then prod with explicit human approval at the gate. Your AI agents work inside your own GitHub account, on your policies.
Production without pain
No AWS complexity. No CI/CD setup. No security guesswork. We bootstrap dev + stage + prod environments, deploy pipelines, observability, and rollback policies — on day one.
Your infrastructure, always
StrictOps doesn't host your app. Everything runs in YOUR AWS account via a scoped cross-account role. No platform lock-in, no hidden abstractions, no future migration tax when you outgrow us.
Two ways to ship the
thing your AI just wrote.
Pick whichever you prefer. We've heard convincing arguments for both.
Roll your own platform
- ✕ Wire GitHub Actions to AWS. Re-wire when IAM rotates.
- ✕ Write Terraform / CDK / CloudFormation by hand. Or learn one and migrate later.
- ✕ Build canary deploys, rollbacks, and error-budget gates from scratch.
- ✕ Stand up CloudWatch dashboards, log routing, alerting — yourself.
- ✕ Hire a platform engineer at $220K while runway burns.
- ✕ Discover you wrote a secret to logs three months in.
strictops init
- ✓ GitHub ↔ AWS link in one click. Rotation handled.
- ✓ Infra-as-code generated from your repo's reality, not your guesses.
- ✓ Canary, rollback, and error-rate gates wired by default.
- ✓ CloudWatch dashboards, log routing, alerting — bootstrapped.
- ✓ No platform engineer needed until you're past Series A.
- ✓ Policy guardrails block the dumb stuff before it ships.
We slot in.
We don't swallow.
StrictOps is the layer between your AI tools and your AWS account. Your code stays in your repo. Your infrastructure stays in your account. Cancel us tomorrow and your production keeps running — because it's yours.
Meets you where you work.
Terminal, AI editor, browser. Pick your weapon — they all hit the same control plane.
StrictOps CLI
Detect, initialize, validate, deploy. One command, one source of truth.
→ strictops init
→ strictops deploy --env prod
MCP Server
Validate strictops.yml inside Claude Desktop, Cursor, or any MCP-aware editor — before you push.
ask strictops: "why did build #128 fail?"
AI Assistant
Claude Sonnet 4.6 with live access to your deployments, logs, alarms, and config — built into the console.
→ roll back prod to a8f3e1
↳ done · 11s
Ready to ship
with AI?
Vibe coding gets you to v1. StrictOps gets you to production — without learning DevOps.