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Gartner Warns $3.5 Trillion of AI Infra Spending Vulnerable to Diminishing by 2030-End

The research firm warns AI infrastructure spending could outpace revenue, which exposes trillions in assets to write-down risk and consolidates the neocloud market.

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US-Based Reflect Orbital Books 2 Skyroot Launches for Its Spacecraft

The agreement expands Skyroot Aerospace’s commercial launch pipeline as Reflect Orbital develops satellite-based lighting services.

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Figma Research Finds AI Speeds up Product Building, Raises Quality Concerns

A survey of more than 500 Indian respondents found growing adoption of design AI, faster workflows, and rising concerns about generic AI output.

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The 20 Cypher 2026 Talks That Got People Talking

From Vijay Shekhar Sharma’s call to make India the LLM capital of the world to Sarvam AI’s land records breakthrough, 1,540 LinkedIn posts reveal the Cypher 2026 talks and ideas that resonated long after the event ended.

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Figma announces new features to define how agents work on its platform

Design platform Figma announced a new Markdown-based editor to help define a company’s design, bring in design and code libraries, and integrate with the Payload headless content management system during the company’s first Config event in India. Through some of these features, the company aims to provide a definition for its own and third-party agents to adhere to a brand’s design rules better while creating with AI. The company debuted a new feature called Figma Specs, which is a markdown editor that lets users define their design language in a simple way. The document can serve as a reference for teams and agents while designing in Figma. Specs can exist as a standalone file in Figma or can co-exist within the canvas. Apart from acting as a text editor, users can reference other Figma elements, such as elements on the canvas and embed FigJam diagrams, code layers, and designs. What’s more, teams can bring in more context about design, including design libraries, code libraries, and guidelines to manage context for the design system. Agents can also refer to this centralized system to adhere to rules. In the past week, the company made its agent on canvas available to a wider user base. However, given the non-deterministic nature of AI, the company is providing tools to steer it towards more predictable outcomes. Figma also made its code layers feature, which adds coding to designs on canvas for more interactive prototypes. The companyannounced this featurein private beta back in June. At its India event this week, the company is making the function available in public beta to let more users test it out. Users can also ask the agent to turn a design into code or change a part of the code to iterate on a prototype. “We see Figma as the place where software teams come to decide what they build and ship. And so for that, I think one of the key things to keep in mind about what AI has changed and what it made available is the ability to build,” Figma’s chief design officer Loredana Crisan told TechCrunch. “There are 17-times more lines of code being produced today than in the past. But when you’re looking at releases, only 1.3-times more releases. A lot of that code actually is not necessarily built to ship, but really built to discover what the product is. It’s built to design.” The company said it is also supporting over 20 new tools with its MCP, including Open Code, Dia, Grok Bot, and Indian AI startup Sarvam. Last year, Figma acquiredopen-source headless CMS Payload. Now, the company is integrating it with its Figma Make product for generating dynamic websites and directly managing content. The company said that Payload’s downloads have increased sixfold in the last 12 months. The company opened itsfirst office in India late last year with sales, partnership, go-to-market, and product support functions. Figma said that the country is its biggest market in terms of users outside the United States. The company noted that the platform works with 40% of India’s top 100 companies listed on the Bombay Stock Exchange.

Figma Expands Into Coding, Hosting as CEO Rules Out Covering High-Traffic Bills

Figma said its new AI-powered tools will expand designers’ capabilities, while hosting costs could vary with traffic.

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Gudea leverages AI to help organizations prevent social media crises before they erupt

Every day, conversations unfold across social media and websites around the world. A seemingly insignificant post—whether it involves AI-generated misinformation, hate speech, or a damaging rumor—can quickly snowball into a much larger public controversy. Gudea, a company that tracks how stories and rumors spread online that describes itself as the “storm tracker for the internet,” is using AI to help organizations spot trouble brewing online before it turns into a crisis. Unlike traditional social listening platforms, which only track metrics such as mentions, hashtags, and impressions, Gudea aims to show organizations who is driving a conversation, how information is moving, how quickly a story is gaining traction, and where it could be headed. Rather than simply tallying posts, its AI analyzes behavior, relationships, and the pathways through which information travels across more than 500 mainstream and fringe websites and platforms, including X, Reddit, and TikTok. Instead of simply telling a company that mentions are rising, Gudea aims to provide the context behind that growth so decision-makers can determine how and whether to respond. Gudea pitched its mission Wednesday afternoon on theStartup Battlefield stage at TechCrunch Disrupt 2026, where the company made the case that companies need to take a more proactive approach to protecting their reputations. “These big industries don’t understand that there are things they can do proactively to defend their reputation and their brand,” CEO and founder Keith Presley said. “A lot of the chief communications officers and chief media or marketing officers, they’re using legacy tools to try to figure out what’s happening. Those tools were only ever designed to tell you the number of hashtags or number of impressions.” Gudea was founded in 2023 by Presley, Jonathan Sperber, and James Thomin. Presley brings more than 15 years of experience spanning political campaigns and defense, including building the infrastructure for Andrew Yang’s presidential campaign. Sperber, the company’s chief strategy officer, has a background in disinformation research. Thomin, Gudea’s CTO, holds a Ph.D. in chemical engineering and has spent roughly two decades working in AI and machine learning. Presley called the company’s path to becoming a startup unusual. “We’re one of those weird startups where I never wanted to do a company,” he said. The team began with the George Washington Initiative, a nonprofit established after the 2020 election. The organization adapted strategies and tactics that the intelligence community has used overseas to disrupt online networks tied to groups such as Al Qaeda and ISIS. It applied them to domestic information campaigns. The goal was to identify the online environments where information campaigns were taking shape and disrupt the pathways that allowed those narratives to reach wider audiences. However, the team found that existing tools didn’t show how information was actually moving across people, groups and platforms. That gap became the opening for Gudea. Three years after its founding, Gudea has nearly 40 clients. According to Presley, its customer base includes a Fortune 50 telecommunications company, a Fortune 50 retailer, “one of the world’s largest AI labs, one of the world’s largest bands,” public relations and crisis communications agencies, and government agencies. With the rise of generative AI, Presley believes that the need for Gudea’s technology has only grown, as the company looks to expand its customer base. AI tools have dramatically lowered the cost and effort required to generate content and coordinate online campaigns. What once required a larger organization can increasingly be carried out by a single person with a laptop and access to the right software. “When we first started in 2021, and then as a company in 2023, we maybe saw one out of four things we looked at have inauthentic activity around it,” Presley said. “Now it’s probably nine out of ten things that we look at have this inauthentic activity.” Looking further ahead, Gudea plans to expand its ability to understand where narratives originate and how they spread. One major upcoming initiative is geolocation for narratives. Slated for next year, the technology is intended to allow users to identify where conversations are happening with far greater precision, down to the city-block level, Presley explains. The company also wants to give customers greater access to the tools behind its analysis. For example, a company could eventually run an advertising campaign through Gudea’s AI model before launching it and get a better idea of whether the strategy is likely to produce a negative outcome or not. Last week, Gudea announced that it had raised $7 million in seed funding in a round co-led by Mudita Venture Partners and Silicon Road Ventures. The investment brings the startup’s total funding to approximately $15 million.

Ricursive Intelligence is betting on AI-designed chips to help solve the compute crisis

Ricursive Intelligencefounders Anna Goldie and Azalia Mirhoseini believe more efficient AI chip design could help solve the compute crisis. The founders took the stage at TechCrunch Disrupt on Wednesday to detail how their startup is developing AI that can design chips, learn from each iteration, and improve subsequent designs, all with the goal of automating and accelerating the chip design process. “There is this understanding that in the next five years we are going to have at least 10,000x more demand for compute, and that’s somewhat potentially conservative,” Goldie said on stage. “So we don’t want to build 10,000 times more data centers. We think that we need to help by making chips that are more efficient, that use the bandwidth in those data centers more efficiently, that use the wafers and fabs more efficiently, because even if we make [data centers] in space or something, I don’t know, you won’t see the sun anymore.” While some may be scared by the thought of AI designing its own chips, Goldie argues that letting AI handle chip design will allow humans can focus on developing applications and exploring new possibilities that can expand what they can accomplish with computing. “I think the way everything is shifting is that humans come bring their great ideas and creative thoughts, and execution is handled by AI,” Goldie said. “And this is happening in chip design, software development, and other places. And that’s something that recursive does for chip design.” The founders say AI is challenging traditional chip design methods by discovering unconventional layouts that can outperform traditional ones. For example, AlphaChip, the AI system the founders previously developed, produced a circular, “donut-shaped” arrangement of chip components that initially surprised engineers but ultimately proved to be successful. They explained that they are optimizing entire chips rather than following the traditional approach of partitioning them into dozens of smaller blocks. This approach allows AI to create intricate patterns, including wave-like designs, which the pair said they plan to share more about in the future. The founders also argued that AI-designed chips will make it possible to create all sorts of chips that might not have been possible before. “If it takes six months or a year or two years to design a new chip, then you really have to be extremely selective about the chips that you design,” Goldie said. “But if you can design a chip in like a week, and then say for manufacturing, you can design custom chips for all sorts of different types of applications in like space and AR, VR, and you biological computing, and it makes sense financially to do that, and we can be more energy efficient.”

Apate sends AI agents undercover to get scammed so they can gather fraud intelligence

Most companies use AI agents to ship products faster or to speed up workflows.Apate.aisends them undercover to get scammed. Founded in 2024 on the basis of research done in Macquarie University in Sydney, the Australian startup deploys thousands of AI agents that masquerade as innocent victims. The agents can answer scam calls, respond to shady messages and emails, follow phishing links, and join social media groups to bait fraudsters. They pretend to be people of all stripes, sporting different ages, genders, and accents, and speak various languages as they try to keep scammers engaged long enough to learn something useful. The company says its fleet of agents has so far wasted 17 years of scammers’ time across 2.5 million conversations. More importantly for Apate’s customer base of banks, telecom companies, government agencies, and utilities, the undercover agents try to get scammers to reveal things about themselves that are usually learned onlyaftera victim has been scammed: bank accounts, crypto wallets, phone numbers, malicious websites, the brands they’re impersonating, and other details about the scams they’re running. Apate, one of the finalists at this year’s Startup Battlefield 200 at TechCrunch Disrupt, then feeds that information to its customers, who use it to inform their anti-fraud measures and initiatives. (The companywill pitch a panel of VC judges at Disrupt, which is taking place this week at Moscone West in San Francisco through Thursday, October 15.) It’s a curious evolution of scam-baiting, but it’s not so surprising given how much AI has empowered scammers and hackers. The FBIreceivedmore than 22,000 complaints of AI-related crimes in 2025, which resulted in about $893 million in losses. More than $632 million of that came from investment scams, in which the FBI says fraudsters use AI to run conversations, and deepfake the voices and appearances of celebrities, executives, and trusted figures. For a long time, people have made a hobby out of deliberately stringing scammers along — sometimes hilariously, like getting scammers toread aloud entire books, or even toget ridiculous tattoos. Now, with AI growing increasingly capable, the tables are turning. Curiously, the idea behind Apate was sparked by a real scam call. Several years ago, Apate’s founder and CEO Dali Kaafar was at a family picnic when he got a call from an unknown number. Realizing it was a scammer on the line, he decided to play dumb for the benefit of his kids and managed to keep the call going for 44 minutes. Everyone had a laugh, but Kaafar noticed that those were 44 minutes the scammer had not spent calling a real victim. It was also 44 minutes of his wasted time, which led him to wonder: Could he automate it, and in the process, learn something useful? That idea eventually led to research work at his job at Macquarie University, where Kaafar and his colleagues used machine learning and natural language processing to uncover the content of scam calls, and develop better ways to detect and prevent scams. “Most of the industry works after the fact. Telcos block numbers, but scammers just get new ones. Banks watch transactions, but by then the scammer has already reached the customer. We go to the scammer directly and get the information before anyone gets hurt,” Brad Joffe, co-founder and chief commercial officer, told TechCrunch. “Our AI agents talk to tens of thousands of scammers every day across calls, messages, email, and the web. What we offer our customers is what comes out of those conversations, and what they can do with it.” Joffe said Apate uses both frontier models and its own fine-tuned models to power its agents and analysis. The company trains its models on conversations its agents have had with scammers, as well as the research Kaafar did at Macquarie. In addition to access to Apate’s fleet of agents, customers get access to an insights portal that offers intelligence and analytics on scams targeting their end users or employees, brands, products, and more. Customers can even assign these agents particular missions, such as obtaining a bank account number or crypto-wallet address. Its text agents can search forums, investment groups, and social platforms for potential scam activity, and can then enter conversations with a fabricated identity to surface scammers’ details. The startup’s customers include Commonwealth Bank of Australia, TPG Telecom, as well as other utilities, telcos, and government agencies. Joffe said TPG has diverted nearly 590,000 calls to Apate’s agents, Commonwealth has seen a 76% drop in publicly reported scam losses, and an unnamed Australian bank the startup works with has used its outbound agents to disrupt 22 scam campaigns. Investors are betting there is money to be made from fooling scammers, too. Apate raised $8.15 million in seed funding in August from Lobby Capital, OIF Ventures, Investible, Concept Ventures, and Baobab Ventures. Joffe said the 20-person company has raised just under $10 million in total and plans to spend the latest round on its product and international expansion, including opening an office in London and building a larger presence in the U.S. “Apate is named after the Greek goddess of deception, which felt appropriate given what our agents do,” Joffe said, adding that the startup even features scammers swearing at the bots in its pitch material. “We track that as a sign of frustration and every swear word gets celebrated by us at Apate. We are probably one of the only businesses in the world that celebrates when people swear at our product.”

YouTube Music launches new labels as AI-generated music floods streaming platforms

YouTube MusicannouncedWednesday the rollout of a new labeling system aimed at improving transparency around songs created with the help of generative AI. Now listeners will be able to easily identify tracks created using AI, including those involved in composition and vocals. The label will appear on the player page. Clicking on this label provides additional information about the specific role of AI in the track’s creation. Notably, these labels will also extend to the main YouTube app. YouTube said it collaborated with various music partners and deployed its own detection tools to identify AI-generated music. According to itshelp page, partners using YouTube can declare their work’s use of generative AI through one of three designations: Fully Gen AI, Partly Gen AI, or No Gen AI. “Fully Gen AI” applies to tracks that are entirely generated by AI, while “Partly Gen AI” refers to works where artists may have incorporated AI-generated components but added their own live elements. Tracks edited using pitch-correction tools such as Auto-Tune fall under the “No Gen AI” category. The move comes as AI-generated music rapidly expands across streaming services, and many platforms are adopting their own approaches. For instance,Apple Musichas plans to introduce “Made With AI” labels as part of its AI Transparency Tags later this year.Spotifyalso has AI labels, as well as a music spam filter. Deezer has taken one of the stricter stances, reporting in July that it was receiving nearly90,000fully AI-generated tracks daily. The platformlabels detected AI-generated musicand excludes it from algorithmic recommendations and editorial playlists, while also withholding royalties from fraudulent streams. The company is also working on an option to let usersfilter out AI-generated music. TIDALalso labels recordings it identifies as entirely AI-generated, allows listeners to disable them, and excludes these recordings from royalty attribution. YouTube, by contrast, is focusing on disclosure rather than blanket restrictions. Its new labels are intended to inform listeners about AI’s role in music creation, but AI involvement alone doesn’t make a track ineligible for monetization. YouTube even experiments with AI-powered music creation, including its toolDream Track, which lets select creators generate soundtracks featuring AI-generated versions of participating artists’ voices.

Flock CEO says its microphones detect ‘just gunshots’ — its website says different

Flock CEO Garrett Langley said the company’s gunshot-detection microphones detect “just gunshots,” but Flock’swebsitepaints a far broader picture of what other ambient audio also gets picked up. Speaking onstage atTechCrunch Disrupt, the co-founder of the surveillance company defended Flock’s audio-collection product calledGunshot Detection, which listens for gunshots and other ambient audio across nearby neighborhoods to provide “earlier awareness” to potential public safety events. Flock’s website says that the company’s audio systems can pinpoint gunfire instantly, while also being able to “detect street takeovers early to stop chaos before it escalates,” and “identify severe crashes in real time so help arrives faster.” It also says they can “expand awareness beyond gunfire with alerts for car crashes, fireworks, and sideshows.” The company’s Gunshot Detection feature, announced last year, faced immediate pushback. In announcing the feature, Flock said the technology would listen out for sounds of “screaming.”Privacy groups condemned the companyfor listening for human voices, prompting the company to amend its website to instead say “sounds of human distress.” Flock later said itpulled the ability to detect “distress”altogether from its customers who tried it. During the interview, Langley pushed back against what he described as misinformation about his product, arguing that many of its critics misunderstand how its products work. The comments come as public opinioncontinues to shiftagainst Flock and other license plate reading companies amid growing unease about mass surveillance — sentiments that were visible in San Francisco, whereprotesters gathered to voice their oppositionoutside the venue as Langley took the stage. “Most people don’t call 911 when they hear a gunshot, and so that’s why we built the product,” Langley told TechCrunch editor-in-chief Connie Loizos onstage. “And then some of our customers said, ‘Oh, we have these in parking lots. It would be great if we could get alerted if someone was being abducted, if someone was being harmed.’” Langley said that the idea seemed logical, so the company prototyped it and rolled it out to a couple of customers, but said that some people then had a lot of concerns. Langley conceded to making mistakes but that he was listening to his customers. “There’s only a couple customers that were prototyping it with us, and we said, ‘OK, great, it’s just going to do gunshots, plain and simple.’ If a gun goes off, we’ll notify, and if not, that’s all it’s going to listen to,” said Langley. When asked about the contradiction between his remarks and the company’s marketing materials that say the audio systems can detect more than gunshots, he responded, “It’s just gunshots.” When reached by TechCrunch, Flock spokesperson Paris Lewbel said: “Flock’s gunshot detection technology is primarily used to detect gunfire but is also capable of detecting fireworks, sideshows, and potential car crashes. CEO Garrett Langley’s remarks were intended to emphasize that Flock’s Audio Detection technology is not designed to monitor conversations or analyze speech and does not currently detect human screaming or distress.” An FAQ section of the website notes that “in addition to gunshots, Flock Gunshot and Audio Detection can detect fireworks, sideshows, and other disruptive community events.” It goes on to state that the company’s “detection library is continually expanding to include emerging threats that are relevant” to customers’ specific needs. Langley stated that the number of Flock’s microphones is comparable to ShotSpotter, which as of 2024 had about 25,000 microphones, per reporting byWired. Langley’s comments come amid mounting scrutiny of Flock from privacy advocates, including the ACLU, and members of the public who are concerned about the misuse of its technology, with some going so far asdestroying the surveillance cameras. The remarks also come asTexas and Floridahave moved to end their relationships with Flock, andAmazon’s Ringhas ended its partnership with the company.

TechCrunch Disrupt 2026: Day 2

Day 2 ofTechCrunch Disrupt 2026is here at San Francisco’s Moscone West. Explore innovative startups and solution providers in the Expo Hall, discover emerging technologies through live startup pitches, and use AI-powered matchmaking to connect with a community of 10,000+ founders, investors, startup teams, and technology leaders. Whether you’re looking for your next investment, discovering solutions for your business, or gathering ideas to take back to your team, there’s plenty to explore today. Today’s focus spans AI, with speakers from Nvidia, Waabi, Flock Safety, and Ricursive Intelligence, alongside Benchmark’s full partnership. Conversations will cover robotics, AI hardware, public safety, and venture investment. Still deciding whether to come?Get your passand join us at 50% off the original walk-up rate. Make discovery and networking your focus with an Expo+ Pass, or choose an eligible conference pass to add stage sessions, interactive roundtables, and Q&A breakouts. Registration: 8 a.m. to 5 p.m.Badge pickup and in-person registration is in the Level 1 lobby. All times below are Pacific Time. Open8 a.m. to 5 p.m.on Level 2. Explore 300+ startups alongside tech partners and solution providers across the Expo Hall. See products in action, discover tools that could help your business grow, and speak directly with the teams behind them. Meet potential customers and partners, scout investment opportunities, or compare solutions to the challenges your team is facing. Give yourself time to explore companies beyond your usual area of interest. Catch today’s enterprise fast pitches to discover emerging startups and see how founders make their case. Whether you’re building a company, scouting investments, or working in a startup team, find inspiration in how others explain their products, demonstrate value, and capture attention. Note the companies and approaches that stand out, take fresh ideas back to your team, and meet the founders afterward to explore potential opportunities. With an eligible conference pass, explore the ideas, business strategies, and technologies shaping the startup ecosystem.Check the full agendafor session times and the complete Day 2 lineup. Hear perspectives that could inform your next business decision, investment thesis, or product strategy. Today’s highlights include: AI, Surveillance, and the Future of Public Safety: Garrett Langley, Flock Safety What We Believe Now: Benchmark’s Jack Altman, Peter Fenton, Chetan Puttagunta, Everett Randle, and Eric Vishria When AI Starts Designing Its Own Hardware: Anna Goldie and Azalia Mirhoseini, Ricursive Intelligence Startup Battlefieldcontinues with health tech and life sciences, plus enterprise and security, as contenders pursue a place in the final and $100,000 in equity-free funding. Discover companies to follow, see how teams respond to investor scrutiny, and gather ideas for presenting your own products or evaluating new opportunities. Explore what it takes to fund and grow a startup. Founders can sharpen their plans, investors can compare perspectives on what makes a business fundable, and startup teams can better understand the priorities shaping their next stage of growth. Consider what the discussion means for your business, portfolio, or team, and compare perspectives with other attendees afterward. The Series A in 2027: Jahanvi Sardana, Index Ventures; Shailendra Singh, Peak XV; and Janelle Teng Wade, Bessemer Venture Partners How to Win When You’re Not Building AI: Mark Crane, General Catalyst; Shan Shan, Baillie Gifford; and Chris Yu, ALSO Build Mode Live: Building From Zero to One:Juliana Di Simone, Forela; Arul Nigam, Circuit Breaker Labs; and Courtney Young, MyoGene Bio Revealing AI Disruptors 60: What Can AI Do Next?: Parag Agrawal, Parallel Web Systems; Shay Grinfeld, Greenfield Partners; Anand Kannappan, Patronus; Alberto Taiuti, Reactor The Real Tokenmaxxing: How the Best AI Companies Navigate a Multi-Model World: Mo Jomaa, Capital G; Vipul Ved Prakash, Together AI; and Zuzanna Stamirowska, Pathway Building the Next Generation of AI Giants:Jas Khaira, Blackstone N1 The Zero-to-1K Playbook: How to Get Your First 1,000 Customers Without a Marketing Budget:Crystal Huang, GV (Google Ventures); Grant Lee, Gamma; and Elia Wallen, Engine So You’ve Got a Hit Product. How Does Your Company Do It Again?: Maddi Holman, Daring Ventures; Filip Kaliszan, Verkada; Tamar Yehoshua, Atlassian Discover how AI is moving into physical products and environments, with opportunities to explore practical applications, emerging markets, and the challenges of deployment. Plus, witness a live robot demonstration. Building AI Systems When Failure Is Not an Option: Nathan Michael, Shield AI; Mikell Taylor, General Motors; and Raquel Urtasun, Waabi Come, Meet Stretch. The Robot Built for Real Life, Not a Demo Reel: Aaron Edsinger, Hello Robot Robots Are Waiting for Their ChatGPT Moment. Here Is What Is Standing in the Way: Les Karpas, Nvidia Operating at the Edge: How AI Works When the Cloud Doesn’t: Ali Agha, FieldAI; Michelle Lee, Medra; and Aidan Madigan-Curtis, Eclipse Ventures Launching AI’s Orbital Infrastructure: Devin Coldewey and Blake Bullock, The Aerospace Corporation; Jeff Thornburg, Portal Space Systems; Jonny Dyer, Muon Space Humanoid Robots Have Arrived: Live and On Stage: Jonathan Hurst, Agility Robotics, and Digit, Humanoid Robot From Prototype to Production: Can It Scale in Reality: Kevin Peterson, Bedrock Robotics; Adrian Macneil, Foxglove The Race to General-Purpose Robots with Skild AI: When AI Meets the Physical World:Varun Jain, SE Ventures; Deepak Pathak, Skild AI Can We Engineer Nature’s Comeback?: Ben Lamm, Colossal Biosciences Why and How Every Company Will Build Its Own AI: Manos Koukoumidis, Oumi; Matt Burns, Insight Media Group The Agent Security Problem Nobody Is Talking About:Gavriel Cohen, NanoCo; Ric Smith, Okta Rewriting SaaS: Why AI Breaks the Old Business Model: Cathy Gao, Sapphire Ventures; Aaron Jacobson, NEA; and Barr Moses, Monte Carlo Before You Let AI Do the Job, How Do You Know It Actually Can:Irene Solaiman, Hugging Face The $63 Billion Case for Storagemaxxing Your AI Stack: Pinaki Mukherjee, Wasabi Technologies; Stephanie Walter, HyperFRAME Research; Kevin Cochrane, Vultr; Jake Lee, L2 Point Management What Comes After the Chatbot: Alexander Embiricos, OpenAI The GTM Engineer: How AI Created Tech’s Next Big Job Category: Kareem Amin, Clay Model Behavior: How Top Startups Get Real Value From AI Adoption:Cat de Jong, Anthropic; Grant Lee, Gamma; Kareem Amin, Clay Proxy, Host, Operator: Who Can Read Your Agent’s Prompts?:Richard Rizk, Blackbox AI Securing the AI Enterprise: Why the Cloud Just Got a Lot More Complicated:Katie Moussouris, Luta Security; Wendy Nather, Cybersecurity Veteran; Rudy Mitra, AWS The Enterprise Isn’t Broken. Your Assumptions About It Are:Arsalan Tavakoli-Shiraji, Databricks Use the audience Q&A to explore a decision you’re facing, ask how an idea could apply to your business, or better understand the implications for companies you’re evaluating. Building Then vs Now:Payal Kadakia, ClassPass; Dr. Rumman Chowdhury, Humane Intelligence; Cassie Kozyrkov, Kozyr; and Holly Ransom, Emergent Infrastructure at the Speed of Demand: Power and Freight Without the Wait:Kofi Asante (Bluecore Energy), Kevin Damoa (Glīd) Best Practices for Running a Successful Fundraise: From Preparation to Investor Engagement:Maggie Sin (Fidelity Private Shares), Bill Tai (HUT 8 Corp), Robin Uata (Fidelity Private Shares) From Founder to Investor: The Next Act – What Happens After You Win?:Bruce Lee (Keebeck Wealth Management), Abhi Tiwari (Blank Ventures) Breaking Into Space: The AI Builder’s Opportunity:Dr. Brian Cameron (The Aerospace Corporation), Timothy Graves (The Aerospace Corporation), Bosco Lai (Little Place Labs), Col. Aaron Stevenson (United States Space Force) Sovereign AI: Who Will Build the Infrastructure and Intelligence of the Next AI Economy?:Özgür Altun (Turkcell), Suresh Babu (Hewlett Packard Enterprise), Bekir Polat (Office of the Presidency of the Republic of Türkiye) Fundraising Mistakes That Will Kill Your Round, and How to Avoid Them:Dr. Irena King (Surgicure Technologies), Dr. Richard Munassi (Tampa Bay Wave), Ashley Paston (General Catalyst), Emily Zhen (HealthQuest Capital) Take part in these popular small-group discussions. Bring a business challenge, an investment question, or a perspective from your own work. Hear how others approach similar issues and leave with ideas to explore further. What Comes After ChatGPT? AI for the Physical World:Jack Hidary (SandboxAQ), Stacie Calad-Thomson (NVIDIA) How Does Agentic AI Change Decision-Making?:Cassie Kozyrkov (Kozyr) When Frontier Models Are Not Enough: How to Make AI Capable of Breakthrough Scientific Discoveries:Piotr Byrski (Molecule.one), Shane Lewin (Clockwork Bio) Grow Like a Founder, Think Like a CFO: Balancing Growth and the P&L:Marshall Egger (Spacemilk) Agentic AI in the Enterprise: Separating Signal from Noise for GTM and Ops Leaders:Ankita Mehta (Databricks) The $100 Billion Entry Fee: Can Anyone Still Compete in AI?:Harrison Rolfes (PitchBook) FDE: The Best Commercial Motion in Enterprise Software You’ve Never Heard Of:Kevin Bai (Anthropic) The Rise of SoCal Hard Tech: Why VCs and Founders Are Gravitating to Gundo:Drew Boyles (City of El Segundo), Kevin Hawkins (New York Stock Exchange) “My Company Is a Rocket Ship.” What Comes After the Landing?:Vishal Kumar (Twin Peaks Wealth Advisors), Tushar Kumar (Twin Peaks Wealth Advisors) How to Land Your First Institutional Check (From the Person Who Writes Them):Aditi Maliwal (Upfront Ventures) Relationship-Led GTM: Founder + Operator Perspective:Connie Koh (Vectors Capital), George Mitri (2DaLoop) Open-Weight Models and the New AI Stack:Mercedes Bent (Premise), Vanessa Larco (Premise) VC Insights for Founders: How to Raise Your First VC Round:Itamar Novick (Recursive Ventures), Brian Sparkes (Silicon Valley Venture, Corp.) Doing More with Less: Raising Venture Capital in an AI-first World “Helping Entrepreneurs Avoid the Pitfalls of Overcapitalization”:Neil Sequeira (Defy.vc) TheNetworking Loungepowered by Signify Business Cash World Elite Mastercard® by Wells Fargois open 9 a.m. to 5 p.m.Use the TechCrunch Events app and itsAI-powered matchmakingto schedule meetings. Connect with people relevant to your goals, from potential customers and solution providers to investors, collaborators, and industry peers. Follow up on an introduction, continue a conversation over coffee, and agree on a next step before you part ways. The Deal Flow Cafe is available only to Founder Pass and Investor Pass holders for dedicated networking.Explore pass access here. For Investor Pass holders only,StrictlyVCoffers conversations on IPOs, family offices, and limited partner priorities. Use the afternoon to compare investment perspectives and build relationships with fellow investors. Check the agenda for the latest program times. The New Rules of Going Public:Ryan Flanagan, ICR The New Power Players: How Family Offices Are Reshaping Venture Investing:Bruce K Lee, Keebeck Capital Management and Dave Sachse, Family VC What Limited Partners Want Now:Amit Bhatti, Truebridge Capital and Beezer Clarkson, LGT Capital Partners Keep the conversations going after you leave Moscone West. Some of tonight’sSide Eventsinclude: Ecosystem Mixer, hosted by Peak XV Liquid Assets, hosted by Augment and Mintz The Afterburn, hosted by Backblaze and Flamethrower Explore opportunities to meet people beyond your existing network in a more informal setting. Check the individual listings for entry requirements and RSVP before heading over. Discover a company worth watching, a solution worth exploring or a connection worth following up. Whether you’re building, investing, or helping a startup grow, make Day 2 work for your goals. Get your Disrupt passat 50% off the Walk-Up rate and join 10,000+ tech leaders for the next two days of our annual flagship conference.

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TechCrunch Disrupt 2026: Day 2