Today on This Week in Startups, we're joined by @bryantchou, Founder of @ployai. He spent 12 years as Co-founder and CTO of Webflow. Now he's the founder (Chief Ployee) of Ploy, an AI platform that builds your site, writes your copy, and runs your campaigns while you sleep. They just emerged from stealth with a $27M seed round led by First Round Capital and Y Combinator. Come tune in at 11PM CT.

Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out. It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend. The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans). More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains. In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries. Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology. I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.

Looking for three up and coming AI companies to interview on @ThisWeeknAI — please reply below or DM @ThisWeeknAI your ideas!

Fun question to start the week: Which suite of acquired companies would make the best line-up for Apple? @Lons said Sony. Apple TV (and other electronics), PStation becomes Apple Gaming, Apple Pictures Entertainment, even Crunchyroll becomes Apple Anime 10

Today on TWiST, we're joined by Stacy Salvi, Co-Founder & CEO of The90. She spent 8 years building wearables at Fitbit (through Google's $2.1B acquisition) and is now betting on a new stat: UV exposure. Her answer is The90 Gem, a piece of smart jewelry that tracks your real UV exposure and tells you exactly when to reapply. See you at 11 AM central! Live details in comments. Company: the90.com/the90-gem LinkedIn: linkedin.com/in/stacysalvi/

EXCLUSIVE: AI actress Tilly Norwood glitches and starts speaking CHINESE during her interview with Piers Morgan and real-life actor Tom Conti... Watch the full interview at 7pm (BST)👇 📺 piped.video/piersmorganuncen… @piersmorgan | @TillyNorwoodX

It used to take five days and two people to assess a website’s security, according to Armadin co-founder/CEO Kevin Mandia. Now it costs $5 and takes about 10 minutes. As the leaders of the top frontier labs call for more regulation, Mandia argues that essential AI development for tasks like cybersecurity will continue regardless. He’s joined on TWiAI Ep 31 by another panelist working on critical AI we have to get right: detecting financial fraud. Soups Ranjan of Sardine AI joins the panel. @lons, @alex, @soupsranjan, @sardine, @ArmadinSecurity, @Jason 0:00 Dario Amodei's "We Must Pace the Frontier" essay 1:51 Kevin Mandia: how scared should we be of agentic attack swarms? 6:53 Rogue agents vs. humans pointing AI at a target 9:52 250,000 fraudulent account signups in two days 16:59 Sam Altman's two ways AI fails 19:41 Open-weight models are catching up 21:39 Why proprietary data is the new moat 27:51 Mixing frontier models with open models 35:37 Bloomberg: Chinese hackers lean on DeepSeek because it's cheap 37:05 How much in-house expertise it takes to use AI well 42:56 Armadin's Palo Alto office and the Palantir playbook 1:02:54 AI and jobs: normal churn or something bigger? 1:07:19 What founders are actually saying in the group chats 1:08:49 Every meeting recorded, every meeting summarized 🎥 Watch the full episode here 👇