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The Final Countdown for TechCrunch Disrupt 2026 Savings This is it. The countdown is almost over. You now have until tonight at 11:59 p.m. PT to lock in Early Bird savings of up to $410 for TechCrunch Disrupt 2026 before prices increase. Event Overview: A Gathering of Tech's Elite If Disrupt has been on your must-attend list, this is your final chance to secure the lowest available rates before the next price jump hits. Once the deadline passes, so do the savings. Join 10,000+ founders, investors, operators, and innovators at Moscone West in San Francisco from October 13–15 for three days packed with networking, startup discovery, and conversations shaping the future of tech. Group Benefits: Bring Your Team at Reduced Rates Bring a plus-one at 50%, or bring a group to get an up to 30% discount. These options make it more affordable to attend with colleagues or team members. Why TechCrunch Disrupt Matters for the Industry TechCrunch Disrupt is where startup momentum accelerates. The event brings together the people actively building, funding, and scaling what's next across AI, fintech, SaaS, climate, cybersecurity, consumer tech, and beyond. What to Expect at the Conference With 300+ exhibiting startups, Startup Battlefield 200, curated networking experiences, and multiple stages of programming, Disrupt is built to help attendees make meaningful connections and real business progress. Who Should Attend Disrupt 2026 Disrupt is designed for founders raising capital, investors sourcing opportunities, operators scaling companies, and innovators looking for an edge. Whether you're launching your next startup, growing your network, or tracking the future of technology, Disrupt puts you in the room with the people driving the industry forward. High-Caliber Speakers and Sessions Every year, Disrupt brings together hundreds of influential voices across startups and venture capital. Past speakers have included leaders from the companies and firms shaping the future of AI, enterprise software, fintech, consumer tech, and more. This year will deliver the same high-caliber experience, with 200+ sessions across six industry-focused stages, plus roundtables and breakouts covering scaling, AI, fintech, infrastructure, robotics, and emerging technologies. Don't Miss the Early Bird Deadline Early Bird savings of up to $410 end tonight at 11:59 p.m. PT. After that, ticket prices increase. Register now to secure your TechCrunch Disrupt 2026 pass at a low rate before the deadline expires. Bringing more than just you? Save 50% on a second ticket, or up to 30% on community passes.

The Rise of Recursive Self-Improvement in AIThe word "recursion" is the latest buzzword in AI circles. Two separate startups have taken on the name, and many more have started referencing recursive self-improvement (RSI) in their roadmaps. Like AGI before it, RSI has become a three-letter byword for a cataclysmic AI takeoff – even if there's still a little disagreement about what it exactly means.In basic terms, RSI refers to an AI system that can continuously upgrade itself. Once AI systems can manage the upgrade cycle better than humans, the process can become a closed loop, limited only by the compute power they can access, and humans are no longer necessary or even helpful.Scary or not, that's a vision that a lot of AI labs are eager to chase.Key Players Pursuing Recursive SystemsEarlier this month, well-known AI researcher Richard Socher launched the aptly named Recursive Superintelligence with RSI as an explicit goal. "Our main focus is to build truly recursive, self-improving superintelligence at scale," Socher told TechCrunch at launch, "which means that the entire process of ideation, implementation, and validation of research ideas would be automatic."A number of other prominent researchers are already chasing that same goal, hoping for a breakthrough that will make recursive self-improvement possible.One of the most prominent is Andrej Karpathy, a legendary figure from Tesla and OpenAI, who is using agent swarms to train LLMs on simple tasks for a project he calls Auto-Research. Karpathy has been unusually open about the project, tweeting about milestones regularly and making the building blocks available through a public GitHub repo. So far, the work has mostly been confined to making minor improvements on a GPT-2 scale model — as Karpathy noted in March, "It's not novel, ground-breaking 'research' (yet)" — but it's been enough to convince lots of other researchers to follow the RSI dream. And with Karpathy now working on pre-training at Anthropic, he will have plenty of opportunity to apply the idea at a larger scale.Adaption — founded by Cohere and Google alum Sara Hooker — recently launched a similar tool called AutoScientist in an effort to automate frontier training. Like Karpathy's auto-researchers, the system trains agents to make incremental improvements — but for Adaption, the goal is to make it easier to train a full-scale frontier model. If those same researchers start to push the frontier forward, the system could quickly spiral into something very much like RSI.Disarray founder Doris Xin drew more specific RSI interest when her self-trained machine learning agent took home 28 medals in a recent Kaggle competition, beating out many human-trained agents. As she sees it, the major challenge is reliability."I would argue, given infinite compute and infinite time horizon, we are already there," Xin told me. "I want to make an argument that this is not a creative endeavor, really. It's just a lot of meat-and-potatoes engineering."The Current State of Self-Improving AIThere's also plenty of evidence that the AI industry isn't very close to recursive systems in any meaningful way — and is still grappling with talking to a wary public about its progress. So Google CEO Sundar Pichai basically admitted in a recent podcast interview."It's a continuum, and we are all definitely making progress," Pichai said. "But in the way people describe RSI, that would represent a next level of acceleration and would have a lot of implications, but we aren't quite there yet."But the continuum includes an awful lot of self-improving AI systems.In January, one of Anthropic's lead programmers for Claude Code estimated that "close to 100%" of his team's code was written by the tool — a frank admission that Claude Code was literally writing itself.Just because engineers are using an AI tool doesn't mean the tool can replace them — but Anthropic seems to be getting close to replacing engineers too. In a recent survey tied to the Mythos preview, five out of 18 Anthropic engineers believed that, with harness improvements, this version of Mythos could soon substitute for an L4 engineer — a midlevel programmer who can take on involved projects without supervision.Still, there were some of the same weaknesses you might expect."Some of Claude's major reported weaknesses compared to an L4 include: self-managing week-long ambiguous tasks, understanding org priorities, taste, verification, instruction-following, and epistemics," the report reads.In other words, its weaknesses are everything involved with self-direction, which is the cornerstone for RSI. But sure, for everything else, Claude is ready to step right in.Expert Perspectives on RSI TimelinesJust like the AGI term before it, the AI industry also can't tell us how far away it is from showcasing a meaningful recursive system. When Georgetown's Center for Security and Emerging Technology assembled a group of experts to study RSI last year, the group found a major split in assessments — some expecting an imminent "superintelligence" style explosion while others expected slower progress and an eventual plateau. But all agreed that recursion made the future especially difficult to predict.Helen Toner, director of CSET and a former board member at OpenAI, told TechCrunch that simply using AI tools to do AI research isn't enough to qualify as RSI. "They're just using AI for as much as they can," Toner told TechCrunch. "And I think that is different from the classic definition of RSI, which is really that there are no humans needed."Toner pointed to a recent post by METR's Ajeya Cotra, which distinguishes different milestones on the path to the AI research takeover. One step, which Cotra calls "adequacy," would come when the system can still perform research after all humans are removed — even if the resulting research isn't as valuable or efficient. "Parity" comes when an AI-only system is as good at research as a human-only system. "Supremacy," the final stage, comes when an AI-only system outperforms a collaborative system between humans and AI.Ultimately, Cotra concludes that AI is very close to the adequacy threshold of being able to produce some work on its own — similar to the incremental changes made by Karpathy's Auto-Research system. "I wouldn't be totally shocked if you told me this milestone had already passed, and I expect it to happen in the next couple years," Cotra wrote.She was less clear on when parity will come, but once it does, she thinks it would "massively accelerate the pace of AI progress, leading to AI research supremacy within another year."The Challenges Ahead for Recursive AIWith so much of AI built on scaling laws, there's a strong tendency to think RSI will follow the same curve. Toner thinks that many of those pursuing AI research and development via RSI "think of it as a pretty smooth ladder, where you can just keep scaling up."But even if AI researchers are able to make incremental improvements like Karpathy's auto-researchers, there will be larger challenges in handing off the whole process of research. Toner put it in terms of the history of computing, which has seen human beings handing off more and more of the process while still directing things from the top."We went from machine languages to assembly language and compiled languages; you're getting further and further from the guts of the computer," Toner said. "But the human is still, in some intuitive sense, running the show."Moving beyond that paradigm will take significant challenges, both in engineering and alignment. But even with the massive investments happening, there's no infinite compute available — and the basic trade-off between human labor and machine intelligence will be hard to overcome.The Future of Recursive Self-ImprovementAs for a total recursive AI system of apocalyptic visions? The only thing researchers essentially agree on is that, like AGI, it's not here yet.

The Lead Enterprise organizations are not rejecting AI. They are rejecting operational instability. This shift is becoming a defining reality for enterprise AI companies that scale versus those that stall after early momentum. The Event Details At TechCrunch Disrupt 2026, taking place October 13–15 at Moscone West in San Francisco, Arsalan Tavakoli-Shiraji, co-founder and SVP of field engineering at Databricks, will discuss this shift during his AI Stage session, “The Enterprise Isn’t Broken. Your Assumptions About It Are.” The Data Analysis The enterprise AI market is full of successful pilots that never became real deployments. Not because the technology failed, but because the organization could not absorb the operational consequences of adopting it. Databricks and other AI startups gaining traction inside large organizations increasingly share one thing in common: They reduce uncertainty. The Impact Analysis Enterprise buyers are asking different questions now. Concerns are no longer secondary; in many organizations, they have become core to the buying decision itself. For AI founders selling into the enterprise, understanding how technical systems interact with organizational behavior, infrastructure realities, procurement processes, governance concerns, and operational risk is crucial. The Prediction The startups that succeed in enterprise AI over the next several years may not necessarily be the ones with the most advanced models. They may be the ones that best understand how enterprises actually absorb change. The market is maturing, and enterprise AI success increasingly depends on more than strong engineering alone.

The Final Days of Early Bird Pricing Time is running out to secure discounted tickets to TechCrunch Disrupt 2026. Early Bird pricing ends tomorrow, May 29, at 11:59 p.m. PT. After that, prices for the highly anticipated tech conference will increase. Unlock Savings of Up to $410 By registering now, you can lock in savings of up to $410 on your pass or up to 30% on group passes of 4+. Why Attend TechCrunch Disrupt 2026? TechCrunch Disrupt 2026, taking place from October 13–15 at San Francisco’s Moscone West, is a premier event for startups, investors, and tech enthusiasts. Here’s what you’ll gain by attending: Founder Pass: Accelerate growth with the right insights, tools, and connections. Meet investors aligned with your startup. Investor Pass: Discover standout startups and expand your portfolio with curated access. Use matchmaking tools to make every conversation count. Don’t Miss Out The window to the lowest ticket rates of the year is closing at 11:59 p.m. PT tomorrow, May 29. Register now to secure your ticket with up to a $410 discount.

Google’s AI Overview Stumbles on Simple Letter Counting Google’s newly rolled‑out AI Overview feature in Search incorrectly counted letters in everyday words – claiming there are two “P”s in “Google”, one “r” in “poop”, and even misspelling “journalism”. The blunders highlight a long‑standing weakness of large language models (LLMs) when it comes to exact spelling. The Miscounted Letters Behind the New Search AI “Google” – AI said 2 Ps (actual: 0) “poop” – AI said 1 r (actual: 0) “journalism” – AI said 2 d’s (actual: 0) U.S. President’s last name – AI reported 1 P but rendered “t‑r‑p‑u‑m” Quantifying the Miscounts: Numbers Behind the Errors Beyond the anecdotal examples, the AI also produced a faulty definition for the word “disregard”, responding with “Understood. Let me know whenever you have a new prompt or question!” This illustrates that token‑based encoding can produce nonsensical outputs even when the input is a single word. Implications for Search Trust and AI Adoption Google’s AI‑driven overhaul aims to make generative responses the centerpiece of its 29‑year‑old search product. Repeated factual and spelling errors risk eroding user confidence, especially after earlier AI Overviews cited satirical sources and gave absurd advice such as “eat rocks”. Trust in AI‑generated answers remains a critical hurdle. What’s Next for Google’s Generative Search? Google told TechCrunch it is “working to fix this particular issue” and will likely refine its tokenizer and post‑processing pipelines. Industry observers expect incremental improvements rather than a complete architectural shift, meaning users may continue to see occasional glitches while the broader AI‑search strategy matures.

The Seismic Shift in Search Google's recent I/O event has officially marked a new era in search technology, with AI-generated answers now taking precedence. This fundamental change renders traditional SEO strategies, built around the '10 blue links' model, largely obsolete. Implications for Brands and Marketers The new AI-driven search paradigm significantly reduces brand visibility. Most brands currently have limited insight into how AI systems describe them to users. This development calls for an urgent reevaluation of SEO and digital marketing strategies. Scrunch's Strategic Positioning Scrunch, a startup, is positioning itself at the forefront of this AI search shift. Matt Thompson, VP of partnerships at Scrunch, discusses the implications of Google's changes. Adapting to the New Landscape Marketers and founders must adapt quickly to these changes. Key considerations include: Understanding how AI describes their brand. Revising SEO strategies to align with AI-driven search results. Staying Informed For deeper insights, listeners can tune into the full episode of TechCrunch's Equity podcast, available on YouTube, Apple Podcasts, Overcast, Spotify, X, and Threads.

The Final Hour: Apply for Startup Battlefield 200 Today The application window for Startup Battlefield 200 closes today at 11:59 p.m. PT. This is the last chance for founders to apply or nominate a startup for a chance to compete for $100,000 in equity-free funding, gain global visibility, and connect directly with investors on the TechCrunch Disrupt stage. What Startup Battlefield 200 Offers Selected companies will showcase at TechCrunch Disrupt in front of 10,000+ attendees, leading venture capital firms, global media, and the broader TechCrunch audience. Founders gain direct investor access, live exposure, and the opportunity to prove they belong among the next generation of category-defining companies. Every selected company pitches live, whether on the Disrupt Stage or the Pitch Showcase Stage. Founders get direct investor access, live exposure, and the opportunity to prove they belong among the next generation of category-defining companies. The Impact of Startup Battlefield 200 More than 1,700 startups have participated in Startup Battlefield over the years. Together, they've raised over $32 billion and produced more than 250 exits, including acquisitions by Microsoft, Google, Salesforce, Uber, and Amazon. Eligibility and Application Applications are open globally across industries. Most selected startups are pre-Series A, though select Series A companies may qualify. To apply, startups should: Be building innovative, potentially category-defining products. Have a strong founding team. The Stakes Thousands apply every year. Only 200 are selected. Just 20 finalists pitch on the main Disrupt Stage. One startup wins $100,000 in equity-free funding. The Prediction If you're building something category-defining — or know a startup that deserves the spotlight — submit your nomination and complete your application before time runs out. The deadline closes tonight, 11:59 p.m. PT.

The Final Countdown for Early Bird Tickets There are only 3 days left to save up to $410 on your ticket to TechCrunch Disrupt 2026. Early Bird pricing ends May 29 at 11:59 p.m. PT, and once the deadline passes, ticket prices increase. What to Expect at TechCrunch Disrupt 2026 From October 13–15 at Moscone West in San Francisco, TechCrunch Disrupt brings together 10,000+ founders, investors, operators, and innovators driving the future of technology. Founder Pass: Connect with investors, gain practical insights, and access the tools and relationships that help startups grow faster. Investor Pass: Meet emerging startups, discover new investment opportunities, and maximize every conversation with curated networking tools. The Importance of Securing Your Ticket Now Whether you’re raising capital, scouting investments, hiring talent, launching a startup, or building strategic partnerships, Disrupt is designed to put you in the middle of the conversations shaping what’s next. The countdown is on. Early Bird pricing disappears May 29 at 11:59 p.m. PT. Secure your ticket now and save up to $410 before rates increase.

Rapid Growth Trajectory Database provider ClickHouse has crossed $250 million in annualized revenue run rate, tripling its business from last year, Yury Izrailevsky, co-founder and president of product and technology, told TechCrunch. Izrailevsky expects the revenue figure to reach the high-nine digits by the end of the year. Valuation and Funding ClickHouse was valued at $15 billion in January following a $400 million Series D funding round led by Dragoneer Investment Group. The latest valuation implies a steep multiple of over 60x annualized revenue. IPO Ambitions The fast revenue growth and premium valuation position the less-than-five-year-old company for an IPO within the next few years, according to Izrailevsky. ClickHouse joins a small but growing list of tech startups signaling plans to go public as the IPO window is expected to be flung wide open by SpaceX’s historic June debut, followed by highly anticipated listings from OpenAI and Anthropic later this year. Strategic Moves Last fall, the startup hired Jimmy Sexton, who previously ran investor relations at Snowflake, one of ClickHouse’s main competitors, as chief financial officer. Bringing on a CFO is often viewed as a signal that a company is preparing for public markets. Acquisition Strategy The company has already acquired six startups, including Langfuse, which helps developers track and evaluate AI agent performance. Izrailevsky indicated that ClickHouse plans to remain acquisitive, looking to scoop up “relatively young, but showing very promising technology” startups, typically open source, that complement its core product suite. Product and Customer Base The technology behind ClickHouse was originally developed inside Russian search giant Yandex 17 years ago, but spun out as an independent startup in 2021. ClickHouse has over 4,000 customers, including Anthropic, Meta, Capital One, and Decagon. Business Model The startup’s open source database is designed to process the massive datasets required by AI agents. ClickHouse generates revenue by selling managed cloud services. Izrailevsky claimed that this commercial offering ultimately costs clients less than self-managing the open source version. It “is something that’s a little counterintuitive, but it also has been a big tailwind for us,” he said.