CodeOpsAI is an AI DevOps engineer that joins your Slack, picks up tickets, and ships pipelines, Kubernetes manifests, and deployments through your normal pull-request workflow. Days of waiting become minutes of reviewing.
payments-api service. It's Node 20, deploys to prod-eu.#PR-2841 with a 3-stage GHA pipeline (lint→test→deploy), arm64+amd64 matrix, and OIDC to your eu-prod registry. Tagged @david-r for review.AI assistants have reshaped how fast code gets written — daily users now merge nearly twice the pull requests and ship a growing share of production code straight from prompts. The work around the code — pipelines, environments, configs, deploys — still runs at human speed.
If AI can write the code, it can write the pipeline, the manifest, and the deploy fix too — at the same pace. One Slack message in, one PR out, minutes later. No new dashboard, no new tab; developers ask in the channel they already use, and your team reviews in the GitHub workflow they already trust.
Each agent is expert in one domain. They share org context — when the Pipeline Agent ships a workflow, the Kubernetes Agent already knows about it.
Most "AI for DevOps" today is autocomplete inside an editor or a chatbot that hallucinates YAML. CodeOpsAI is built differently — from the ground up to operate inside your organization, not in a generic context.
Every artifact reflects how your org actually works — your registries, your environment topology, your secrets manager — not how a template author assumed it works.
The Pipeline Agent's output is the Kubernetes Agent's input. The Deployment Agent's rollout is the Monitoring Agent's signal. A team, not a collection of disconnected bots.
Every infrastructure-modifying action goes through approval. For most orgs, that's a GitHub PR review — your existing process, not a new one to learn or audit.
When an approver edits a generated artifact, the agent learns the preference. Approval rates climb over weeks as the output increasingly matches your team's standards.
We're looking for design partners — engineering orgs willing to deploy CodeOpsAI alongside their DevOps team and tell us what works. Early access, dedicated support, partnership pricing.