Developer
Pick a starting point. Each guide is short and self-contained.
If you're working on AI for your own work
You've got prompts, skills, and maybe a custom GPT or two. You want to make them work for your team.
- How to build an AI agent → A six-step walkthrough for turning a workflow you do every week into something your team can run.
- Turn a skill into a runbook → Already have a Claude skill or a custom GPT? Fastest path to making it reliable.
- For operators → The pitch for people who've already built their own AI setup and want to deploy it.
- For builders → Reliable agents, durable execution, OpenAI-compatible API, no framework to stand up.
Documentation & setup
For wiring Jetty into your coding agent, in five minutes.
- Install the agent skill → Claude Code, Codex, Gemini CLI, Cursor, VS Code, Windsurf, Zed, or any MCP-compatible client.
- docs.jetty.io → For the API reference, agent configuration, sandbox snapshots, webhook payloads — everything past the conceptual material — see the developer docs.
Operationalizing Your Agent
You're past the experimentation phase and trying to figure out how to scale this responsibly.
- For teams → Visibility, security, and vendor portability for the AI workflows your team relies on.
- Model- and agent-agnostic → Why your runbooks should outlive any one vendor's pricing decision.
Concepts
The thinking behind how Jetty works.
- What is a runbook? → The format. Skills + standards = runbooks.
- Blog Longer-form thinking on evaluation, runbooks, and what we learn shipping AI in