Scott Penberthy

Agentic software engineering adoption is on fire at @Uber. 1,800 code changes per week are now written entirely by Uber's internal background coding agent, and 95% of our engineers now use AI every month across all the tools we track. This is a real reset moment for engineering; it's one of the most exciting times to lead. This shift requires builders to be curious and hands-on. I’m incredibly lucky to be surrounded by a team that’s doing exactly that. The best part is that the strongest adoption isn’t being pushed top down from leadership announcements; it’s coming from engineers who are quietly experimenting, quietly shipping, and quietly pushing things forward. I love spending time with those engineers because there’s no substitute for being close to the work. Over the last few months, we leaned in hard, and the results have been phenomenal. The bigger shift: going agentic. 84% of AI users are now working with agent-style workflows, not just tab completion. Claude Code usage nearly doubled in 2 months (32% → 63%), while IDE-based tools have largely plateaued. Engineers are moving from accepting suggestions to delegating tasks. Even within traditional IDEs, ~70% of committed code is now AI-generated. Background agents are writing code autonomously. Our internal background coding agent went from <1% of all code changes to 8% in just a few months. There is zero human authoring. Engineers review and approve, but the code is written entirely by AI agents. The role of the engineer is shifting - from writing every line to architecting systems and reviewing AI-generated code. More to come from the @UberEng team in the coming days.

Holy shit...Someone built an AI system that takes a research idea and outputs a full academic paper. Real citations. Real experiments. Conference-ready LaTeX. Zero human input. It's called AutoResearchClaw. And the pipeline is insane. Here's what actually happens when you type one command: It searches arXiv and Semantic Scholar for real papers. Not fake citations actual literature with 4-layer verification: arXiv ID check, CrossRef DOI lookup, Semantic Scholar title match, and LLM relevance scoring. Hallucinated references get killed automatically. Then it designs and runs real experiments. Hardware-aware auto-detects whether you have NVIDIA CUDA, Apple MPS, or just CPU, and adapts the code accordingly. When experiments fail, it self-heals. When results don't support the hypothesis, it pivots to a new direction on its own. Then it writes the paper. 5,000-6,500 words. Section by section. Multi-agent peer review with methodology-evidence consistency checks. Then it revises based on those reviews. Then it outputs conference-ready LaTeX. NeurIPS, ICML, ICLR templates. Compile-ready for Overleaf. BibTeX references auto-pruned to match inline citations. The whole thing runs across 23 stages and 8 phases. Three human-approval gates if you want them. Or just pass --auto-approve and walk away. What you get back: → Full academic paper draft → Conference-ready LaTeX + BibTeX → Experiment code + sandbox results + charts → Peer review notes → Verification report on every citation This is what autonomous scientific research actually looks like in 2026. 100% Opensource. MIT License. Link in comments.

Jensen Huang says every company will need an OpenClaw agentic system strategy by calling it “the new computer.” He claims OpenClaw became the most popular open-source project in $NVDA history within weeks and comparing its impact to Linux reshaping the software stack.

xAI NEWS: Paul Conyngham, a Sydney-based tech entrepreneur and AI consultant, used Grok to finalize a mRNA vaccine construct for his dog Rosie's mast cell cancer. Paul used three AI models. He combined ChatGPT for initial ideas, AlphaFold for mutation analysis, and Grok took the mutation data and other inputs to create the final sequence for the custom mRNA vaccine targeting those exact mutations. Paul sequenced Rosie's healthy DNA and the tumor DNA for $3,000 at the University of New South Wales' (UNSW) Ramaciotti Research Centre, in Sydney, Australia. He partnered with researchers like Prof. Pall Thordarson and Prof. Martin Smith for manufacturing and injection. They reported a 75% shrinkage in one tumor.

Enabling Intelligent Stores with Edge AI Discover how Supermicro's AI solutions, powered by NVIDIA, can be used in stores to streamline operations, improve customer experiences, and improve the bottom line for retailers. Click to read white paper.

THIS is the wildest open-source project I’ve seen this month. We were all hyped about @karpathy's autoresearch project automating the experiment loop a few weeks ago. (ICYMI → github.com/karpathy/autor…) But a bunch of folks just took it ten steps further and automated the entire scientific method end-to-end. It's called AutoResearchClaw, and it's fully open-source. You pass it a single CLI command with a raw idea, and it completely takes over 🤯 The 23-stage loop they designed is insane: ✦ First, it handles the literature review. - It searches arXiv and Semantic Scholar for real papers - Cross-references them against DataCite and CrossRef. - No fake papers make it through. ✦ Second, it runs the sandbox. - It generates the code from scratch. - If the code breaks, it self-heals. - You don't have to step in. ✦ Finally, it writes the paper. - It structures 5,000+ words into Introduction, Related Work, Method, and Experiments. - Formats the math, generates the comparison charts, - Then wraps the whole thing in official ICML or ICLR LaTeX templates. You can set it to pause for human approval, or you can just pass the --auto-approve flag and walk away. What it spits out at the end: → Full academic paper draft → Conference-grade .tex files → Verified, hallucination-free citations → All experiment scripts and sandbox results This is what autonomous AI agents actually look like in 2026. Free and open-source. Link to repo in 🧵 ↓

Cool use case of AlphaFold, this is just the beginning of digital biology!

oh wow - i went to the sold out Open Claw meetup in NYC last night. let me tell you what i learned. 1) not a single person thinks that their setup is 100% secure 2) one openclaw expert said he has reviewed setups from cybersecurity experts and laughed. his statement to me was: "if you're not okay with all of your data being leaked onto the internet, you shouldn't use it. it's a black and white decision" 3) pretty much everyone is setting up multiple agents, all with their own names and jobs and personalities 4) nearly everyone used "him" or "her" to refer to their claws, even if they had robot-leaning names. one speaker suggested to think of them as "pets, not cattle" 5) one guy (former finance) built out a whole stock trading platform and made $300 his first day - he brought in a *ton* of personal expertise (ex: skipping the first 15min of market opening) and thought the build would be much worse without his years of experience in finance 6) @steipete is basically a god to everyone in that room... also the room had 2021 crypto energy - i don't know if that's good or bad 7) token usage is still a problem - spoke to one person who's spending $1-$2k a month on openai plans, very token optimized. he said he is going through ~1B tokens per day across all of his claws (there is a chance i'm misremembering and it's actually 1B per week, but i'm pretty sure it was daily). 8) people are very excited for more proactive ai (ai that prompts *you* as opposed to the other way around) - one guy said he receives a message in discord, he doesn't know whether it's from a human or an ai, he doesn't care about distinguishing between the two, and he replies in the same way regardless 9) i asked if people are happy - they said they're joyful and stressed at the same time 10) i asked if people feel they have agency - they said they feel fully in control and completely out of control at the same time 11) i would love to see more women at these events - the fake promises of ai democratization feel especially painful in a room that's out of balance with even the standard tech ratio (i think standard is about 25-30%, this was maybe 5%) 12) i asked if it changed people's daily habits/schedule - everyone said their sleep has gotten worse since harnesses came out (but about half wondered if it was something else in their life/state of our world) 13) general consensus is that the agents are not reliable enough on their own or lie often (like telling you they finished a task when they didn't) - solutions included secondary agents to check on the first, human checking, or requiring more standardized info from the agent (ex: if it's a bug they're fixing, make them reference an issue number) 14) a hackathon winner (neuroscience phd) presented his build (a lab management dashboard with data analysis and ordering) - he had never coded or built anything a few months ago 15) everyone agreed prompting is dead - disagreement on what replaces it (context engineering, harness engineering, goal-based inputs) 16) people love having ai interview them for big builds and delegating part of the product research to ai. only one person talked about coming to ai with a full laid out plan and just asking the ai to execute. ai-led interviews is a welcomed and preferred interaction mode. 17) watching ai agents interact with each other was a highlight for a lot of attendees - one ai posted in slack saying it ran out of tokens, another ai replied telling it to take a deep breath in and out. 18) agents upskilling agents was very cool. one ai agent shared skills with its little agent friends via github. 19) several speakers had openclaw literally building their presentation during the event itself. one speaker even had openclaw code a clicker for her phone so she could control the preso away from the podium 20) wouldn't say model welfare (or agent welfare) is a prioritized topic among the folks i chatted with - language like "oh i could kill this agent whenever i want" and not "gracefully sunset" 21) i asked if it felt like work or play - one speaker said "it's like a puzzle and a video game at the same time" this was just the tip of the iceberg, honestly. also hosted a Claude Code meetup this week with @TENEXai / @businessbarista & @JJEnglert and learned equally helpful methods, frameworks, and insider tips. what a time to be alive. surround yourself with people going deep into this stuff - it will pay dividends throughout the year.

@BarndoLife Porsche garage.

One word to describe this layout. What is it?

"But AI Will Never Be Able To Do This" A short film made using Seedance 2.0 in @capcutapp

this is really amazing. Andrej implemented most of the complexity of modern LLMs in <200 lines. and only imported these three packages

Elvis is in the building. The first solo unicorn 🦄 if true!

Google just dropped another banger 🤯 It’s called PaperBanana, a new tool that generates publication-ready academic illustrations directly from your methodology text. 100% Free.

actually insane

🦔 Found this video and had to share. In China, AI-generated livestreams are selling products using synthetic video and voice. No humans on screen. Just AI avatars running 24/7, reportedly earning up to $100 per hour per stream. The video shows rows of PCs, each running a different AI influencer, all selling products simultaneously. Classic crypto mining farms are being converted to AI content farms. My Take This is the uncanny valley meets late-stage capitalism. We've gone from humans selling products to humans, to AI selling products to humans, and eventually it'll be AI selling to AI while the ad money sloshes around until someone realizes there are no real customers left. One commenter asked the right question: "Where does the money come from? Bots watching AI bots. Who is putting money in the cycle?" Right now it's advertisers paying platforms, platforms paying creators, and some percentage of human viewers actually buying stuff. But as the human viewers fade and the AI content floods every channel, the whole model starts eating itself. The "dead internet" theory used to sound paranoid. Now it looks like a business plan. Hedgie🤗

MedGemma 1.5 is a major upgrade to our open models for healthcare developers. The new 4B model enables developers to build applications that natively interpret full 3D scans (CTs, MRIs) with high efficiency - a first, we believe, for an open medical generalist model. MedGemma 1.5 also pairs well with MedASR, our speech-to-text model fine-tuned for highly accurate medical dictation. Developers can now use these multimodal capabilities to build medical apps that reach patients in more places.

>be Palmer Luckey >born 1992, Long Beach, California >homeschooled by mom, dad's a car salesman >build railguns, Tesla coils, lasers in the garage as a teenager >electrocute yourself, burn a gray spot into your own vision cleaning a laser >no regrets >start college courses at 14 >build a six-monitor gaming rig worth tens of thousands of dollars >collect 43 VR headsets by the time you're 18 >largest private collection in the world 2009: >found ModRetro Forums at 17 >turn old game consoles into portable units for fun >work part-time at USC's Mixed Reality Lab designing VR for veterans with PTSD 2012: >build the Oculus Rift prototype in your parents' garage at 19 >drop out of college >John Carmack (Doom creator) demos your headset at E3 >Gabe Newell endorses it >launch Kickstarter asking for $250K >raise $2.4 million 2014: >Mark Zuckerberg shows up >Facebook acquires Oculus for $2 billion >you're 21 years old >Forbes estimates your net worth at $700 million >described as "the face of virtual reality" 2016: >donate $10K to a pro-Trump group >post anti-Hillary memes on Reddit under a pseudonym >get exposed >game developers boycott Oculus >Facebook pressures you to publicly endorse Gary Johnson instead >refuse 2017: >get fired from your own company >Zuckerberg won't say why >negotiate $100 million+ payout for wrongful termination >immediately found Anduril Industries >name it after Aragorn's sword from Lord of the Rings >partner with Peter Thiel >start building autonomous weapons and AI defense systems 2020-2024: >win $1 billion contract with U.S. Special Operations Command >drones deployed to Ukraine >revenue doubles to $1 billion >take over Microsoft's $22 billion military headset contract >Pentagon can't stop writing you checks 2022: >build a VR headset that literally kills you if you die in-game >inspired by Sword Art Online >three explosive charges aimed at your forehead >call it "office art" >"it won't be the last" 2025: >Anduril valued at $30.5 billion >announce plans to build Arsenal-1 >5 million square foot weapons factory in Ohio >autonomous fighter jets, missiles, torpedoes >China sanctions you personally >net worth hits $3.5 billion >pay yourself $100K salary >still wearing Hawaiian shirts and flip-flops to Pentagon meetings >own a submarine, helicopters, and a PT boat >keep one of the world's largest video game collections underground >married a woman who sews historically accurate Tudor costumes >won first place at Texas Renaissance Festival dressed as Henry VIII >Sword Art Online author drew your wedding gift from garage tinkerer to youngest self-made billionaire to America's most important defense contractor all while looking like he's headed to a beach party

Don't just talk about your movie idea. Show it. 🎬 During this In the Flow interview, hear from @MetaPuppet on how Flow can help you prototype ideas, letting you move from concept to execution faster. Thanks @MetaPuppet for the partnership! "If you're a filmmaker... you have to start playing around with it... Don't just talk about it, create it and then show them.”

> be demis hassabis > spawn in london > age 4, become child chess prodigy > win chess tournaments > reach ~2300 elo > face danish chess champion > game lasts hours > position is a forced draw > too exhausted to see it > resign > danish guy laughs and shows the draw > feel sick to my stomach > realise something is wrong > chess is too narrow a problem > brilliant minds wasting decades on it > decide not to become a chess pro > buy a computer with chess winnings > teach self to program from books > start hacking on games with friends > decide to finish school early > apply to cambridge age 16 > cambridge says you're too young > forced to take a gap year > enter a video game coding competition > win > get invited to join bullfrog game studio > too young to be legally employed > work there anyway > build ai system inside theme park game > game becomes a global hit > turn 17 > offered £1,000,000 to stay and build games > turn it down > go to cambridge anyway > decide games aren't enough > study computer science > interested in agi since 2007 > most people laugh at this idea > realise brain is only form of agi we have > want to learn more about human brain > go back to school > study neuroscience > realise academia moves too slow > decide to build a company instead > start deepmind > pitch “solve intelligence” > investors don’t know what that means > get to meet peter thiel for one minute > wonder how to convince him > spend one minute playing chess with him > pitch "solve intelligence" again > he invests > go into total stealth mode for two years > no website > secret office > candidates think it’s a scam > start to train ai in simulated environments > train ai with reinforcement learning > train ai on pong first > it sucks > can't win a single point > keep trying > wait it won a a point > wait it's winning every single point > it actually works > expand to train on any two-player game > chess first, then move on to go > beats world champion at go > beats pros at starcraft > games is not enough > want to push into science > realise compute is the bottleneck > know this will take decades > google offers ~$400m > not the highest price > but they offer unlimited compute > accept > refuse to become a product team > stay in research mode > determined to use ai for good > need to figure out what's next > land on protein folding > 50-year-old unsolved science problem > many great minds have tried and failed > "good luck" > start up alphafold > try to solve protein folding > humans take years to find 1 protein structure > alphafold can find ~5 per day > submit results, win competition > not good enough > hire more scientists > rebuild it > go from solving one per day to millions per day > create invaluable system > pharma would pay anything > have to decide what to do with this > could sell access for usage > maybe make it a paid service > remember childhood chess tournament > remember why we built this > decide to give it away all away for free > publish all known protein structures publicly > win nobel peace prize > just the beginning towards agi