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DeepSeek just open-sourced an AI coding agent that lives inside your team's GitHub and works in the background, built around one idea: take as little human attention as possible. 🧪
On October 31, 2026, DeepSeek's Harness team published dsh-superagent on GitHub under the MIT license, together with a design article called "Exploring Super-agent Design: Towards a More Autonomous Agent System." Within about a day the repository passed 6,000 stars. Here's what it is, how it works and what the fine print says.
Chapters
0:00 The short version
0:12 01 What happened
0:32 02 What's a super-agent?
0:48 03 How it works: one Router, many Workers
1:18 04 Polite by design
1:39 05 Does it work? DeepSeek's numbers
2:01 06 The fine print
2:13 07 Should you try it?
2:32 Your turn
What you'll learn
• Why DeepSeek says human attention, not the model, is the limit: in its observation a person can follow only 3 to 5 active agent sessions at once.
• The two-layer design: an always-on Router reads GitHub comments, pull requests and (optionally) Feishu messages, opens a Ticket for each allowed request, and gives every Ticket its own Worker session and folder. Results go back to the same conversation, often as a pull request.
• The "polite by design" rules from the project's philosophy doc: confirm once, stay quiet while working, speak only for a result, a question or a failure. Proactive work needs a written team rule and starts in "observe" mode, which only records what the agent would have done.
• DeepSeek's own test: in a simulation with about 300 messages and 20 real requests, p95 task time was 15.7 minutes for the super-agent vs 29.5 minutes for a single session with sub-agents, about 1.9x faster. These are DeepSeek's numbers on simulated messages; real code quality was not measured (as summarised by MarkTechPost).
• The fine print: the README calls it a research prototype for reference only, not an official DeepSeek product. Bloomberg reports it is aimed at Anthropic's Claude Code (as cited by The Next Web).
• What you need: DeepSeek Harness, Node.js, git, Python, tmux and the GitHub CLI. Setup is done by your own coding agent following SETUP.md.
Would you let an AI agent watch your team's chats? Tell us in the comments 👇
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Keywords: DeepSeek, DeepSeek super agent, dsh-superagent, DeepSeek Harness, AI coding agent, open source AI agent, Claude Code alternative, autonomous agent, GitHub AI agent, AI news, tech explainer
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