Alert
Alert Summarizer posts the structured error
It is 1:37 in the morning.
Your messaging feature is broken in production.
You wake up at seven.
A pull request is waiting. Root cause named. Tests added. Ready to review.
You read it over coffee. Merge it at 7:15.
You did not wake up for it.
Not in a vendor cloud. Not in a demo. On my actual dev machine in Montreal. If a Mentorly alert fires at 2 AM tonight, exactly what I just described will happen.
Mentorly is a Rails and Next.js SaaS with real paying customers. For the last 20 days, an agent has been handling production incidents in this codebase. Autonomously. While I sleep.
Agent drafts. I review and merge. On an enterprise SaaS with real customers, the agent never touches production unilaterally.
C3 only sees errors a pipeline I built has already structured, summarized, and routed to the right Slack channel with the right prompt bound to the right repo.
Instead of an agent running in someone else's sandbox, your own development environment runs on an always-on cloud VM. Same project. Same tools. Same credentials. You SSH in from your laptop like any remote dev box.
It is your dev machine. Just always on.
Nothing about C3 is "someone else's cloud running my code." It is my machine, relocated. This one design choice is where everything else follows from.
Every piece is in Terraform. Version controlled. Under five dollars a month per environment. Silent when healthy.
Claude Code Routines and Managed Agents are real and useful, but they are sandboxed. That is their design. C3 is the other shape of the same idea.
| Capability | Anthropic Routines / Managed Agents | C3 |
|---|---|---|
| Where it runs | Anthropic cloud sandbox | Your always-on dev machine |
| Production database | No direct access | Read-only via your existing query scripts |
| Cloud CLI & secrets | Scoped connectors | Azure CLI, kubectl, Key Vault via managed identity |
| Session continuity | Run-to-completion | Resume on web, phone, terminal, VS Code |
| Model choice | Claude only | Claude Code, OpenAI Codex, OpenClaude, anything |
| Prompt & behavior | Anthropic-defined shape | Plain markdown files in ~/.c3/prompts/ |
Your machine. Your credentials. Your real tools.
No. The difference is context.
The AI sees: one paragraph of text. No repo. No logs. No history.
The developer starts from zero. The agent starts from ninety.
Consistency is what makes an agent trustworthy in production. Not intelligence. Not speed. The same shape, every time.
April 2, 1:47 PM. Alert fires. Duo Security SAML. Config key mismatch.
"After PR #696 renamed `dy` to `davidyurman`, David Yurman's Duo Security can now reach the callback endpoint."
The agent named its own prior PR.
Cause and effect reasoning across two days on real customer production.
On an enterprise SaaS, the agent does not touch production unilaterally. Ever.
Review. Merge. Ship.
Agent saves investigation time. Not judgment time.
Example: PR #709. Agent investigated correctly, opened the PR. I reviewed and closed it.
"Consider enabling the react-hooks exhaustive-deps ESLint rule project-wide to catch render-time side effects earlier."
That is not a patch. That is a team lesson.
Production error response is one use case. The same platform runs the rest of my day.
Every morning I get three independent reports on new agent-related GitHub repos. Three different models. Three different perspectives. Same question.
I tweak the prompts. The output evolves with my taste.
I set intentions. Not tasks.
A session is not a pipeline step that runs to completion. It is a conversation you can join and leave from any device.
| Where you start | How |
|---|---|
| Slack or Discord | Alert fires. Agent picks up the prompt bound to the channel and starts. |
| Web browser | c3-chip.ideaplaces.com, pick a prompt, click start. |
| Phone | Same URL. From the car, the pickup line, a cafe. |
| Terminal | claude --resume <uuid> picks up exactly where the agent left off. |
| VS Code | Session streams into a side panel. Take over, type, hand it back. |
Most of the time the agent completes the full PR alone. Sometimes it hands you a super-professional 80%, and you step in to finish.
Start anywhere. Continue anywhere.
| Metric | Value |
|---|---|
| Days running continuously on Mentorly | 20 |
| PRs drafted by the agent | 17+ |
| PRs I reviewed and merged | 17+ |
| PRs I reviewed and closed (judgment call mine) | 1 · PR #709 |
| Production incidents escalated off-hours | 0 |
| Typical alert to PR time | 5 to 16 minutes |
| Monthly cost of the upstream pipeline | Under $5 per environment |
No. And that is the point.
| Requirement | What you need already built |
|---|---|
| Structured logging | A contract every service follows |
| One observability sink | Errors flowing to a single destination |
| Channel routing | Each error class bound to the right prompt and repo |
| Confidence gate | Your team's decision rules encoded in prompts |
| Always-on dev machine | Pre-authenticated with production tooling |
Without the pipeline, you get hallucinated file paths and shotgun fixes. With it, you get autonomous incident response that merges before you wake up.
The agent is the last step. You already built the first nine.
30 minutes to your first trigger. The investment is writing prompts. That is where your team's expertise gets encoded into reusable infrastructure.
Claude Max subscription. One Azure B2ms VM at $60/month. Total under $500/month for unlimited sessions across every project.
Sandboxed. They cannot query your production database, use your Azure CLI, access your Key Vault, or resume a conversation across your devices. C3 runs where your code lives.
Safety lives in the prompt, not the platform. Production channels get read-only investigation and PR-only fixes. Test channels get full access. You write the rules per channel.