- Anthropic wires AI agents into real-world machines
- Rowan’s Corner: Whispering to AI agents
- Use these AI skills to make better decisions quickly
- UK trials live-video AI in brain surgery
Image source: AnthropicThe Rundown: Anthropic just introduced the Model Hardware Standard in research preview, which lets AI agents look up, learn, and run factory machines like microscopes, robotic arms, and other lab gear that previously needed custom code — built to spread in an industry-standard way similar to the company’s Model Context Protocol (MCP). The details: - Anthropic claims setup times of “hours or minutes” under the new spec, down from the weeks specialists currently spend hand-wiring instruments.
- Machine owners describe their equipment in natural language, with MHS turning it into a reference file agents can read to learn how to operate the device.
- In one test, Claude taught itself to align a laser by trial and error, then simplified the routine into a script that automated the job in a single pass.
- An open-source release is planned at a later date, with Tecan, QIAGEN, and AWS partnering and both Hugging Face and Raspberry Pi adding it to their device lines.
The Rundown: Agents are non-deterministic and dependent on models, prompts, and tools that change without warning. Traditional engineering playbooks no longer translate. LangChain’s new guide breaks down the Agentic Operating Model, aligning people, process, and technology to build, deploy, and scale agents across your organization.In the guide, you’ll learn: - Why AI agents don’t break like traditional software
- The engineering stack that covers the entire agent lifecycle
- How to shift from “build and deploy” to “operate and improve”
Image source: @tmiyatake1 on XRowan: Back in October of last year, I visited several startup offices in San Francisco and noticed the early innings of a trend — developers were using tools like Wispr Flow to multitask across workflows and control AI agents more efficiently, entirely by voice.Fast forward to today, and that trend has only accelerated.SF tech trends are fascinating because there’s something new every week, but most never escape the early-adopter bubble. Every so often, though, one breaks out and becomes huge for everyone.Now that Apple is shipping an AI dictation keyboard in iOS 27 (alongside a fully rebuilt Siri AI), I’m fully convinced: whispering to AI is breaking out of the bubble.I don’t take personal recommendations lightly, but this one's worth hopping on if you haven’t already.Here’s why:- Speed and context. You speak at ~150 words per minute and type at maybe 60. But the underrated part is that spoken prompts are naturally 2–3x longer, so you include the context you’d skip when typing.
- It turns you into a director of agents. A common workflow is to have several tabs of agents open at once, focus on ONE window, whisper a 60-second brief, release, let the agent work, review, and move to the next.
- The AI dictation apps are so good that you can literally whisper to them, and it catches nearly everything. That’s the only way this works in an office of 50 people.
- Open Claude Code in Terminal and install makerskills with /plugin marketplace add coreyhaines31/makerskills, followed by /plugin install makerskills@makerskills.
- Use the repository’s routing table to match the problem to a skill: /unstuck when you keep circling the same wall or /decide when you need to choose between real options.
- Describe the situation and answer the follow-up questions. When social-fetch could not pull our X post and suggested a paid scraping API, /unstuck challenged the assumption that the video needed that demo.
- Try the framework on another job. /decide compared two hypothetical client projects, tested how reversible the choice was, recommended one, and set a date to revisit the decision.
The Rundown: Enterprises are quickly deploying and scaling AI agents, but at what cost? The latest Gartner webinar unpacks how leaders avoid the orchestration overlap and governance gaps that often undercut their efforts.In this webinar, you’ll learn how to:- Cut through AI orchestration complexity
- Close critical governance gaps
- Build a trusted agentic AI framework
Image source: UCLH / BBCThe Rundown: UK surgeons just announced the first brain surgery ever performed with a live AI assistant, with a University College of London system watching in real-time through a surgical camera and flagging hidden arteries and optic nerves to avoid during the removal of a tumor. The details: - Patient Rhys Hibbert had no symptoms until a seizure in late 2024 revealed an 11mm pituitary growth that slowly narrowed his field of vision.
- Surgeons reached the tumor through Hibbert’s nose, while AI watched the camera feed on its own monitor and marked the safest spots to cut and areas to avoid.
- The AI trained on hundreds of labeled videos of past removals, with surgeon Hani Marcus saying it saw “more operations than most surgeons see or do in a lifetime.”
- The patient’s vision was restored within days following the successful removal, with the team now moving toward larger trials of the AI system.
Switch - Bring any AI agent into Slack, Teams, Discord, and more. Open source. No migration. No platform lock-in.*
Cohere Parse 5 - SOTA model for converting docs into machine-readable data
Gemini Omni 1.1 Flash - Google’s upgraded video model
H3 Max - fal's MiniMax H3 remixed video model tuned for speed and quality
- Read our last AI newsletter: The Ox Alpha mystery ends with Z.ai
- Read our last Tech newsletter: Apple’s Mac Mini makes an AI comeback
- Read our last Robotics newsletter: Cyborg roaches become tiny paramedics
- Today’s AI tool guide: Use these AI skills to make better decisions quickly
- RSVP to next workshop on Sept. 2: Build an AI operating system for your 1:1s
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