Databricks built Omnigent as a “meta-harness” that sits atop existing agent frameworks—Claude Code, Codex, Pi or custom SDKs—and turns them into interoperable components. Instead of juggling separate windows and copy-pasting between agents, Docs or Slack, you define agents once and swap models or harnesses with a single line of code. Omnigent layers in stateful policies to control costs, permissions and security at runtime, not with in-prompt guardrails. You can combine multiple models or subagents, track each session’s LLM spend (for instance, pause after $100), and enforce contextual rules like requiring human approval before a git push if new npm packages were installed. On top of that common API, you get real-time collaboration via sharable URLs, a web/UI client plus mobile and macOS apps, and cloud execution on providers like Modal or Daytona. A flexible OS sandbox intercepts network requests—so you can inject secrets only when and where you approve. Authors define agents in YAML and port them across harnesses or mix them in one workflow without rewriting logic. The project is open-source under Apache 2.0, available now in alpha on GitHub, and already deploys to Fly.io, Railway or your own infrastructure. Future plans include meta-level optimization with GEPA, code-based introspection modules and broader harness integrations.