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What Is a Meta-Harness for AI Agents? Omnigent explained

Databricks6 July 2026Watch on YouTube

Part of series

Ep. 5 · Omnigent: AI Agent Orkestratie

Databricks introduceert Omnigent, het open-source meta-framework dat meerdere AI-agenten combineert in één gecontroleerde, interoperabele workflow.

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What you'll learn

  • A harness is all the software around the language model and determines how much context is actually sent per prompt.
  • Two tokens of input can in reality add up to tens of thousands of tokens because a harness includes context, tools and files.
  • Every custom agent has its own harness that only understands itself, which is why agents from different vendors cannot cooperate.
  • Omnigent is an open-source meta-harness layer that sits above agents and lets you compose multiple models and agents into one workflow.
  • With Omnigent you can switch between agents and set cost controls across all of them.

Frequently asked questions

What is a harness in AI terms?
A harness is all the software around the large language model. The model generates tokens; the harness handles the rest, such as file connections, security permissions, the user interface and tool code. It is what turns a model into an agent.
Why does even a simple prompt like 'hello' cost so many tokens?
When you type 'hello' into something like the closed code, you think you are spending two tokens, but in reality it is closer to 30,000. The harness sends context, files, permissions and tools along to the model as well.
What is a meta-harness and what does Omnigent do?
A meta-harness is a layer that sits above individual agent harnesses. Omnigent from Databricks is such an open-source meta-harness and lets agents from different vendors talk to each other, so you can compose them into a single workflow.

Topics

ai agentsorchestrationagent frameworksinfrastructure

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Description from the channel

AI agents are getting more powerful, but the way we run them is still fragmented. Every agent has its own harness, context, permissions, interface, and workflow. That’s why Databricks introduced Omnigent: a new layer above individual agents and a meta-harness for agent orchestration. Instead of managing agents one by one, Omnigent gives you a common layer to compose, control, and collaborate across agents. With Omnigent, you can: • orchestrate multiple agents in one workflow • combine different harnesses without rewriting everything • build custom agents and swap models or harnesses with one-line changes • apply policies, permissions, sandboxing, and spend controls • collaborate on live agent sessions from terminal, browser, desktop, or phone The growth has been wild: Omnigent already has 6,300+ GitHub stars less than a month after launch. ⭐ GitHub repository: https://github.com/omnigent-ai/omnigent