AI coding tools make it easier to build the first version.
They do not make production disappear.
The code still needs secrets, deploys, domains, logs, cost controls, rollback, database safety, auth, jobs, queues, and someone who understands what changed. That gap is where many startups get stuck: the app works locally, the demo works on a hosted platform, but nobody has a clear picture of the infrastructure around it.
This checklist is for that moment.
Why This Matters Now
GitHub's Octoverse showed record developer activity in 2025, with AI and agents reshaping software work. Stack Overflow's 2025 survey also showed the trust gap: developers widely use AI tools, but many do not trust their accuracy, especially experienced developers accountable for production systems. DORA's 2025 AI-assisted software development report made the same point in another way: AI amplifies the system around it.
That is the right frame for startups.
AI can help you move faster. If your cloud operations are unclear, it can also make the unclear parts arrive sooner.
The Production Checklist
1. Know What Is Running
Before a launch, answer:
- Which services are deployed?
- Where are they deployed?
- Which domains point to them?
- Which cloud resources do they depend on?
- Which repo and commit produced the current deploy?
- Which background jobs run?
- Which queues, buckets, databases, and APIs are touched?
If nobody can answer this quickly, do not add more automation yet.
Use Clanker Cloud to ask the live environment:
Map this app's infrastructure across GitHub, cloud resources, Kubernetes, Cloudflare, and deploy targets.
The goal is a current map, not a diagram from last month.
2. Check Secrets And Credentials
Common startup failure:
.envfiles copied between machines.- Long-lived cloud keys.
- Shared admin credentials.
- Secrets in CI logs.
- Production and staging using the same token.
- AI chat history containing sensitive config.
Minimum standard:
- One secret source of truth.
- Separate production and staging credentials.
- No secrets pasted into hosted chat.
- Local credential use where possible.
- Review before agents touch secret-dependent workflows.
This is where Clanker Cloud's local-first model matters. The app should help agents understand infrastructure without turning cloud credentials into chat content.
3. Check Cost Before Traffic
Look for:
- Always-on compute.
- Minimum instances.
- Oversized databases.
- Unbounded queues.
- Debug logs.
- NAT or data transfer paths.
- GPU or AI evaluation jobs.
- Preview environments.
- Storage growth.
Startups should not wait for a surprise bill to learn FinOps.
Ask:
What cloud resources could create a surprise bill if traffic grows 10x this week?
The answer should include evidence and owners.
4. Check Security Exposure
Before launch:
- Public routes.
- Admin paths.
- Database networking.
- Storage bucket access.
- Cloudflare Access or equivalent controls.
- Kubernetes ingress.
- IAM roles and service accounts.
- GitHub Actions permissions.
- CORS and callback URLs.
Do not ask an agent to "secure the app" without boundaries. Ask it to list findings, evidence, risk, and proposed fixes for review.
5. Check Observability
You need enough visibility to answer:
- Is the app up?
- Are users hitting errors?
- Which deploy introduced the problem?
- Are queues backing up?
- Is the database saturated?
- Are external APIs failing?
- Are logs too noisy or too quiet?
- What is the rollback?
You do not need a perfect observability stack on day one. You need enough signals to debug the first real incident.
6. Check Rollback
Every production app needs a rollback path:
- Previous deploy.
- Database migration strategy.
- Feature flag or config rollback.
- DNS or route rollback.
- Queue drain or pause.
- Incident owner.
If the rollback depends on memory, write it down before launch.
What Clanker Cloud Should Produce
For a vibe-coded app, the first useful artifact is a production readiness report:
System map
Known cloud resources
Secrets and credential risks
Public exposure
Cost risk
Observability gaps
Deploy and rollback path
Recommended fixes
Review-required actions
That report is useful to a founder, a first DevOps hire, and an AI agent preparing the next PR.
Startup Version
If you are two engineers:
- Connect the providers you already use.
- Run a readiness scan.
- Fix secrets, exposure, and rollback first.
- Leave platform engineering for later.
- Keep every destructive action behind manual review.
Enterprise Version
If you are inside a larger company:
- Treat AI-built apps like normal production apps.
- Require owner, service, environment, and cost labels.
- Attach cloud context to the PR.
- Review MCP/tool access.
- Require rollback and security evidence before deploy.
The checklist does not get smaller because AI wrote the code.
The Takeaway
Vibe coding changes how apps are created. It does not remove operations.
Clanker Cloud should be the local AI Ops workspace that helps builders and agents understand the real cloud around the app before it becomes production risk.
Sources
Move the repo from prototype to production
Install the desktop app, connect GitHub plus one cloud provider, and review the deployment plan before Clanker Cloud touches real infrastructure.