World Wire

Databricks released Omnigent , an open source ‘meta-harness’ for AI agents. The project ships under the Apache 2.0 license. The Databricks AI team built it with Neon. A harness is the wrapper around a model that turns it into an agent. Claude Code, Codex, and Pi are harnesses. Omnigent sits one level above them. It treats each harness as an interchangeable part of a larger system. Many engineers now juggle four or five agents at once. They copy text between coding agents, search tools, Docs, and Slack. Each harness only understands its own sessions. Omnigent adds a shared layer where composition, control, and collaboration live. What is Omnigent Omnigent is a common interface above command-line agents and agent SDKs. It wraps terminal coding agents such as Claude Code, Codex, and Pi. It also wraps SDKs like OpenAI Agents and the Claude Agents SDK. The design rests on one observation. However a harness calls its model internally, the user-facing interface...

In this tutorial, we implement a QwenPaw workflow that provides a practical environment for building and testing an agent-powered assistant. We install and initialize QwenPaw, configure its working directory, set up authentication, connect optional model providers via Colab secrets, and create a structured workspace with custom skills and local knowledge files. We also launch the QwenPaw Console via a Colab-accessible URL, expose it through an optional Cloudflare tunnel, and test the streaming chat API programmatically, enabling us to use QwenPaw both as an interactive assistant and as an API-driven agent framework. Copy Code Copied Use a different Browser import os import sys import json import time import uuid import shlex import signal import shutil import socket import secrets import pathlib import subprocess from datetime import datetime RESET_QWENPAW = False PORT = int(os.environ.get("QWENPAW_COLAB_PORT", "8088")) ROOT = pathlib.Path("/content/qwe...