SteadyVane
Daily brief · November 4, 2026

DeepSeek released Super-Agent, an open-source prototype coding agent aimed at Claude Code

3 items that moved, with the numbers. Measured by SteadyVane, fact-checked, and graded before publishing.

DeepSeek released Super-Agent, an open-source prototype coding agent aimed at Claude Code

32,106 → 60,939views of a video about it in 36 h · 40 commentsabout 5.5× the typical pace of other tracked AI-tool videos

Super-Agent is an open-source prototype coding agent. It works on one GitHub repository and can optionally listen to Feishu, ByteDance's workplace chat app. Per the DeepSeek Harness team's WeChat post, it can proactively monitor developers' group chats for coding issues and suggest solutions without being summoned. The code is on GitHub as dsh-superagent under an MIT licence.

A video about it went from 32,106 to 60,939 views in 36 hours - about 5.5 times the typical pace of other AI-tool videos SteadyVane tracks on YouTube. It has 667 likes and 40 comments. One more video about it has 59,405 views, so the two have 120,344 views between them.

Why it matters: It is a release meant to challenge Claude Code, and an agent that decides on its own when to start work is the part to watch if you use coding agents.

DeepSeek calls it a research prototype, not an official DeepSeek product. Weigh it accordingly.
Sources: YouTube 1 · YouTube 2

Scalekit's AgentKit is an MCP gateway that lets agents act as a specific user in apps like Gmail and Slack

301 → 368votes on Product Hunt in 8 h · 88 commentsabout 12× the typical pace of other tracked Product Hunt products

AgentKit connects AI agents to 600+ connectors and 30,000+ tools through one MCP gateway. It runs each user's OAuth flow, stores their tokens in a vault and executes tool calls as that user in apps like Gmail, Slack and Salesforce.

AgentKit's Product Hunt post went from 301 to 368 votes in 8 hours - about 12 times the typical pace of other products SteadyVane tracks on Product Hunt. It has 88 comments and was published about 30 hours ago.

Why it matters: Letting an agent touch a real inbox or CRM raises the question of whose credentials it uses. Per-user access, where a developer defines which tools an agent can reach and which user it acts as, is the part worth checking in any agent setup.

An agent that can do everything is a demo. An agent that can only do what this user allows is closer to production.

MIT's Iceberg Index measures which skills AI can already perform; a video says entry-level work is what it replaces

27,152 → 390,684views of a video about it in 8 h · 998 commentsabout 284× the typical pace of other tracked AI-tool videos

The Iceberg Index is a labor simulation tool built by MIT and Oak Ridge National Laboratory. It maps more than 32,000 skills across 923 occupations in 3,000 counties and measures where current AI systems can already perform those skills. A video from The Infographics Show says the findings point to entry-level work, not entire professions.

A video about it went from 27,152 to 390,684 views in 8 hours - about 284 times the typical pace of other AI-tool videos SteadyVane tracks on YouTube. It has 4,332 likes and 998 comments, about 10 hours after it was published.

Why it matters: The index measures technical exposure, not displacement outcomes or adoption timelines, so it describes what AI could do, not what employers have done. If you hire or work in junior roles, read the study itself and not just the headline version.

Exposure is a map, not a layoff list. The video's framing is the creator's claim, and it was not confirmed here.

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