AI Product Build Pipeline
Our end-to-end process for shipping an AI-native product feature: scoping the real user workflow first, prototyping against production-shaped data, and shipping behind a flag with evals in place before it's exposed to real users.
What this template does
Our end-to-end process for shipping an AI-native product feature: scoping the real user workflow first, prototyping against production-shaped data, and shipping behind a flag with evals in place before it's exposed to real users. It's categorized in our directory under Dev & Agent Automation — agent coordination, CI/CD glue, and developer-tool integrations — including our own Claude Code + n8n templates.
Integrations
Setup steps
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AI Agent Production Deployment Checklist
How we take an agent from a working laptop demo to production: scoped credentials instead of a master key, a sandboxed execution environment, eval gates before shipping a prompt change, observability on every run, and a rollback path.
API Rate Limit Watchdog
Monitors how close a workflow's API calls are running to a provider's rate limit and throttles or pauses execution before you get hard-blocked, instead of finding out from a stack of failed calls.
Claude Code Skills System
How we standardize repeatable engineering work as versioned Claude Code skills, so every build starts from a proven playbook — publishing, audits, image pipelines, SEO checks, and deploy safety are all captured as skills, not one-off prompts.
Deployment Notification to Slack
Posts a Slack message with the commit, author, and environment whenever a deploy completes, so the team has a running log of what shipped and when without checking a CI dashboard.
FROM A PATTERN TO YOUR SYSTEM
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