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
- GitHub
- Vercel
Setup steps
- 1Scope the actual user workflow the feature needs to support, not an idealized version.
- 2Prototype against production-shaped data so the demo doesn't collapse on real inputs.
- 3Write evals for the feature's expected behavior before wiring it to a live prompt.
- 4Ship behind a feature flag and roll out gradually while watching the evals.
More Dev templates
Other dev & agent automation templates in our directory.
n8n + Claude Code Agent Coordinator
A Telegram-triggered n8n workflow that routes messages to a LangChain agent (via OpenRouter) with buffered memory, custom tools, and an SSH node that runs commands against a remote Claude Code session — built to coordinate multiple agent tasks from a chat interface.
n8n Claude Code Terminal Bridge
A minimal n8n workflow that exposes a chat trigger, formats the incoming message with a Set node, and pipes it over SSH into a running Claude Code CLI session — the smallest possible bridge between a chat UI and a real terminal agent.
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.
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.