- Anthropic's Claude tackles protein design
- Nate's Notebook: Uber's tiger team playbook
- Use the Loop Method for better ChatGPT results
- Replit adds Free Mode for routine work
Anthropic's Claude tackles protein designImage source: AnthropicThe Rundown: Anthropic just published research showing Claude ran protein-design campaigns largely on its own, a key step in drug discovery, with its designs yielding working molecules on 14 targets out of 15 at success rates above the industry norm.The details: - The company tested its Mythos Preview and Opus 4.8 models, letting them run autonomously with one expert-written prompt, internet access, and tools.
- Anthropic didn’t do the actual lab work; Twist Bioscience and Adaptyv Bio created the candidates in their own labs and ran the measurements.
- The Claude models hit 22-35% success rates on molecules that actually gripped their target, which Anthropic says beats the typical 10-15%.
- Opus 5 separately opened raw instrument files with no lab software, measuring a sample at 96.4% pure in 19 minutes; the lab’s own report took four days.
See what's burning before it becomes your next fire drill
The Rundown: Somewhere in your customer feedback right now, a small issue is about to become a big one. Unwrap gives you AI-powered visibility to catch issues while they’re still embers, not after they’ve become a fire.Unwrap’s proactive approach gets you:- 50% faster root cause investigation on support tickets
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Nate's Notebook: Uber's tiger team playbook
The Rundown: Each week, Rundown AI educator Nate Grahek breaks down what he's seeing while teaching real teams to use AI. This week, he kicks off a three-part series on capturing AI ROI: big companies, small businesses, then individuals.Nate: Remember when Uber made headlines for blowing through its entire 2026 AI budget in four months? Their CTO started capping employee AI use and declared the "tokenmaxxing era" over.Now the same CTO, Praveen Neppalli Naga, has posted what Uber did next. That's what makes this case study worth your attention: it's a company learning in public from an expensive mistake.I've been saying it for months: unsubsidized, full-rate frontier models are simply too expensive to hand to everybody in a large org and let them figure it out. And enterprise AI is harder to begin with, navigating security, large data complexity, and privacy.Uber's answer was the scalpel. They call them Agentic Pods, and each is only two people: one AI-proficient engineer and one domain expert from Finance, Marketing, Ops, etc., running a surprisingly short 10-day sprint. Shadow the expert, build alongside them, ship.The result: a financial pacing report that took a key player two full days now runs in 10 minutes. That's the mindset I want big companies to steal. Your first AI projects have to earn you the right to swing bigger. Enterprise needs to start acting more like bootstrappers: quick, pragmatic efficiency wins, not the flashy long-roadmap bet.Next week, part 2: How small businesses can take advantage of this moment while many enterprises are too slow to figure this out.AI TRAINING
Use the Loop Method for better ChatGPT resultsThe Rundown: In this guide, you will learn how to improve any repeated ChatGPT workflow with the review-based "Loop Method.” We created it to improve our video editing and image generation skills, but you can try it on anything!Step-by-step:- Open ChatGPT Work and find a workflow that needs improvement: a skill, project folder, or process that works inconsistently
- Prompt: "Improve this workflow in 3 loops. Have a panel of sub-agents adversarially review each loop. Done when [definition of done]"
- Use /goal to assign ChatGPT a deliverable you want the workflow to build. Let it run three loops, taking anywhere from 15 minutes to an hour
- Test the improved workflow. If it still needs work, tell Codex to codify ambiguous work into scripts
Join 60,000 builders and leaders at AWS re:Invent
The Rundown: AWS re:Invent brings 2,200+ sessions to Las Vegas, and 70% are hands-on. Join builders’ sessions, workshops, code talks and more to learn by doing, not just through sessions.While onsite, you can:- Bring edge-case questions to engineers and partners building on AWS
- Test services against realistic workloads in sandbox environments
- Access certification exam discounts, with bootcamp-style prep during the week
Replit adds Free Mode for routine work
Image source: ReplitThe Rundown: Replit launched Free Mode, a new setting for its $20 and $100 paid plans that runs everyday chats/tasks on OpenAI’s GPT-5.6 Luna without eating up user credits — with the company crediting Luna’s 80% price cut for making the math work.The details: - Replit says its $20/month Core plan scales as much as 30x usage with Free Mode, adding 30 hours per month of chat using the efficient model.
- Bigger builds still burn credits in the higher-performance modes, and the agent can route to OAI's Sol for a harder step before handing users back to Luna.
- Replit president Michele Catasta called the default-on setup “radical”, arguing plenty of tasks need a smaller, cheaper model, not an expensive frontier one.
- Catasta said Free Mode is "the first of many launches" with OAI, with Sam Altman saying he foresees a "renaissance-level entrepreneurial boom."
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Everything else in AI todayGlean:GO San Francisco, August 26-27 - The intelligence era is here. Join us in person or virtually to make AI part of your everyday work and get more time back for the work that matters. Register now.*Stripe officially announced its acquisition of OpenRouter, while reportedly telling investors that Jan. 1, 2026, was the start of “the singularity.”Chinese AI lab Z AI’s new GLM-5.3 scored a 60 on Artificial Analysis’ Intelligence Index, moving into fourth place overall and tying Kimi K3 for the top open model. U.S. AI chipmaker Cerebras introduced CS-4, its fourth-gen AI computer, which it says delivers up to 30x the speed of GPU-based rivals, even on the largest models.OpenAI debuted Private Safety Processing, a system to scan for misuse across API sessions without staff seeing the content—keeping its zero-data-retention promise.*Sponsored Listing
Highlights: News, Guides & Events- Read our last AI newsletter: Pacing comes to the AI frontier
- Read our last Tech newsletter: The $1.4T case against Meta
- Read our last Robotics newsletter: Robot vacuums finally learn gestures
- Today’s AI tool guide: Use the Loop Method for better ChatGPT results
- RSVP to next workshop today @ 2 PM EST: Land your first AI consulting gig
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