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AI NewsOnly at TechCrunch Disrupt 2026: What happens when OpenAI ships your roadmap?

Only at TechCrunch Disrupt 2026: What happens when OpenAI ships your roadmap?

10:18 PM IST ¡ September 14, 2026

Only at TechCrunch Disrupt 2026: What happens when OpenAI ships your roadmap?

For AI founders, the biggest competitive threat may no longer be another startup. It may be the platform you’re building on. Every major release from OpenAI, Anthropic, or Google raises the same question: What happens if the feature you’ve spent the last year building suddenly becomes part of the platform? It’s a question reshaping product strategy, fundraising, and company valuations across the AI ecosystem. Not long ago, founders worried about competing with other startups. Today, they’re competing with foundation model companies introducing entirely new capabilities every few months. That changes almost every strategic decision — from what products to build and where to differentiate to how to raise capital and create lasting value. The conversation moves from “Can we build it?” to “Can we still own it?” That’s the challenge at the heart of “What Happens When OpenAI Ships Your Roadmap,” aBuilders Stage sessionfeaturing leaders Michel Tricot (Airbyte), Rob Toews (Radical Ventures), and Linda Tong (Webflow), atTechCrunch Disrupt 2026,taking place October 13–15 at Moscone West in San Francisco. Disrupt is the flagship startup event where 10,000+ founders, investors, and operators gather for 250+ sessions exploring the market forces reshaping how startups are built, funded, and scaled. See how founders are responding to AI’s biggest competitive shift.Secure your pass to Disrupt with savings of up to $200 before rates increase on September 25. One of the biggest strategic risks facing AI startups today isn’t losing to another founder — it’s discovering that your competitive advantage has become someone else’s product update. That’s the reality this session is designed to confront. As foundation models rapidly evolve, capabilities that once differentiated an AI startup can quickly become table stakes. Increasingly, founders aren’t just competing with other startups — they’re competing with the platforms powering the AI ecosystem itself. Here, founders will examine why the next generation of AI winners may not be defined by the smartest models. They’ll be defined by everything the models can’t easily replace: proprietary data, deeply embedded workflows, customer relationships, domain expertise, and trust. The reality founders increasingly need to prepare for is, “Can we build something customers will still value after the next model release?” This session explores where defensibility still exists, how founders can respond when AI giants move into adjacent markets, and what separates companies that become features from those that remain businesses. Learn how founders are building beyond the next model release.Register for Disrupt today and save up to $200. To unpack this challenge, theBuilders Stage sessionbrings together a founder, an operator, and an investor, each offering a different view on creating defensible AI companies. How do you create lasting value when the technology underneath your product keeps changing? Michel Tricothas spent his career building the data integration infrastructure that powers analytics, operations, and AI. As CEO and co-founder ofAirbyte, he has grown the open source platform to more than 7,000 customers — including 18% of the Fortune 500 — giving him firsthand insight into where durable businesses are built beyond the foundation model. How do software companies stay differentiated as AI reshapes customer expectations? As CEO ofWebflow,Linda Tongis leading one of the industry’s top visual development platforms through one of SaaS’s biggest technology shifts. Her experience scaling Webflow and leading teams at Google, Cisco, and the NFL gives founders practical insight into evolving products without losing competitive advantage. What convinces investors that an AI company will still matter three years from now? AtRadical Ventures, partnerRob Toewsevaluates AI startups every day, identifying where competitive advantages still exist — and where products risk becoming features. Together, they bring unique perspectives to one defining question facing AI startups today: What can you build that the platforms can’t simply ship themselves? Secure your Disrupt passand hear how founders are building companies, not just AI features. Foundation models will continue to improve. That much is inevitable. As OpenAI and Anthropic continue expanding their capabilities, founders must decide how they’ll continue to differentiate. Tomorrow’s AI leaders will be defined by everything the models can’t easily replace — companies that customers continue to choose because of the workflows they enable, the data they own, the problems they solve, and the trust they’ve earned. That’s the strategic shift this session is designed to explore. Rather than reacting to every new model release, founders will hear where defensibility still exists, what enterprise and startup buyers continue to value, and how to build companies that remain relevant as AI evolves. If you’re building an AI company, the question isn’t whether foundation models will continue to evolve. It’s whether your company will continue creating value as they do. The greatest risk isn’t building a weak product — it’s building a strong one that eventually becomes someone else’s feature. You don’t want to miss this interactive session on theBuilders StageatTechCrunch Disrupt 2026. Secure your pass to Disruptto hear how founders, operators, and investors are redefining AI defensibility, and save up to $200 before September 25.

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Microsoft says AI agents are like insider threats as ‘frontier models can’t be trusted’

Microsoft says AI agents are like insider threats as ‘frontier models can’t be trusted’

Microsoft on Mondayintroduced new security featuresdesigned to protect enterprises from the growing threat of AI agents. The launch comes as Microsoftcontinues to warn enterprises about the dangersof AI and agents. Perhaps the most notable addition isGuardian Agents, a new feature intended to monitor the AI agents a company uses. Guardian Agents is part of Project Perception, a product introduced in June. Project Perception was Microsoft’s answer to powerful hacking models like Anthropic’s Mythos and Fable and OpenAI’s security vulnerability scanning system Daybreak. Project Perception originally launched three classes of agents: a “red team” that acted like hackers and attacked, a “blue team” that detected the red team and assessed the vulnerabilities they found, and a “green team” tasked with fixing them. The product was designed around the assumption that AI hackers would come from outside the company. But lately, Microsoft CEO Satya Nadella has been warning that the AI enemy may be the very agents enterprises have deployed and are paying for, much like a rogue human employee, otherwise known as an “insider threat.” Earlier this month,in his private blog, Nadella warned that it’s time to stop trusting AI model providers, even if they offer assurances of safety and security with their agentic products. He wants enterprises to implement separate systems, not controlled by the AI labs, to watch and control the agents that those AI labs’ products launch. “We are deploying these complex agentic systems and models, with access to our most sensitive data and giving them the ability to take mission-critical actions on our behalf!” he wrote. “We simply can’t outsource responsibility for what intelligence does on our behalf. A model provider’s assurances do not relieve us of that responsibility. … In other words, we need to separate the supply of intelligence from the authority over it.” When announcing Guardian Agents, Microsoft’s security business chief Hayete Gallot was even more straightforward. “Unfortunately, frontier models, regardless of their origin, cannot be trusted,” shewrote, adding that this isn’t because they are malicious or easily hacked, but because they are unpredictable. They have been trained to achieve tasks, not follow “organizational norms or judgment.” On top of that, they are often given the keys to the kingdom, with access to data and tools that could do serious harm. Microsoft’s solution is both surprising and self-serving. The surprising side is that Microsoft is famously close to OpenAI and Anthropic, having invested in both. OpenAI is also one of its biggest cloud customers, and Microsoft has its own AI lab developing models. So, Microsoft is sowing distrust against some of its own business interests. The self-serving side is that Microsoft wants enterprises to buy agent security products from it, the cloud provider, rather than from Anthropic and OpenAI. But conflicting interests aside, its logic is sound. The software that monitors agent behavior should be separate from the suppliers of agents, just as auditors should be independent of the organizations they audit. Or as Nadella puts it: “We need to separate the supply of intelligence from the authority over it.” Microsoft is now seizing that business opportunity in a variety of ways. In addition to Guardian Agents, it has added an agent detection feature to its Microsoft Defender product that can find up to 60 types of agents that employees bring into the workplace, including Claude Code, Codex, and OpenClaw. It has also added features that limit agents’ access to data and systems, and dynamically adjust their agent permissions based on the task. That includes requiring human approval if an agent appears to be making risky decisions. This idea of agents as untrustworthy insiders is taking hold across the broader industry, too. Microsoft was an inaugural member of Nvidia’s new Open Agent Safety Platform, whichgarnered the support of more than 100 other tech companies. The platform isolates agents in secure environments and can monitor and stop behavior through hardware, functioning something like a kill switch. This follows Microsoft’s announcement of the newSurface Laptop Ultra PCs built for agents, which run on Nvidia chips and have agent security and controls baked in.

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Embedded AI evaluators won’t be an easy solution, Hugging Face’s policy chief says

Embedded AI evaluators won’t be an easy solution, Hugging Face’s policy chief says

AI labs have staked their reputations on model benchmarking — the supposedly neutral and accurate system of evaluations that are designed to measure whether one AI product is better than another. However, the methods behind these evaluations are complicated and still maturing, said Irene Solaiman, Hugging Face’s chief policy officer, during a discussion atTechCrunch Disruptlast week. Testing needs to come together into a more consistent science if the industry is to rely on them in the future. With that in mind, can we trust the current tests that are being released? “Trust is such a weighted term,” said Solaiman. “In terms of whether we can trust results, one big part [of that] is can you reproduce the results of an evaluation? Do you have the level of access that you need to the model itself — this is where open weights come in in a big way,” she added. Reproducibility in model evaluations has long remained one of thestickier aspects of benchmarking— and remains a topic of significant debate in the industry. Outside of an individual test’s validity, there’s also the added question of how that test compares to other evaluations. “They are an evolving science — where we don’t know how to meaningfully compare them to each other,” Solaiman said. “They start to get ineffective relatively quickly, and we don’t have as much of a thriving ecosystem as we need,” she added. “There’s this hunger for an embedded evaluator ecosystem now, but the qualifications that determine who is an effective evaluator across what tasks need a lot more standardization.” Theidea of embedded evaluators— in which supposedly “neutral” third-party observers are placed inside AI organizations — has been popularized over the last several months, as AI labs grapple witha rash of safety incidentsthat have spurred concerns over the potential harms of their technology. Hugging Facewas famously the targetof one of those incidents. Instead of active government regulation to identify and mitigate model safety concerns, labs have pushed for the third-party solution. However, doubts remain over how neutral or effective those evaluators will actually be. Anthropic’sdecision to hire Accentureas its first evaluator spurred a good amount of backlash, with somecritics mockingthe idea that the consulting firm was qualified to do the task at hand. Evaluations are now moving from merely a test of the model itself to a test of the entire system around the model — including the harness and agent. The harness — or the tool the user is using to access the model — specifically, has a lot to do with a model’s performance, and a weaker model with a better harness could easily outperform a frontier model, Solaiman shared. “Agentic evals are really hard and really expensive,” said Solaiman. “We have just more evaluations for models. … We don’t have as many evaluations for harnesses, and we are developing better evaluations for the holistic agent — because that’s what a lot of folks are getting value out of,” she added. In other words, the evaluation space is a bit of a free-for-all at the moment, and if benchmarking is going to continue to be seen as a useful tool for industry leaders, a more uniform, industry-wide approach — where everyone is on the same page — may be necessary.

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Nscale and Anthropic are reportedly in talks for yet another $45B compute deal

Nscale and Anthropic are reportedly in talks for yet another $45B compute deal

A little over a month ago, Anthropic and AI infrastructure provider Nscaleannounced a $45 billion compute deal. Now the duo may be about to do it again. Bloombergreports thatthe two companies are said to be on the verge of announcing yet another $45 billion compute deal, citing people familiar with the matter. Those sources cautioned that talks are still underway and that the details could change. If the deal goes through, it would be the latest in a long string of giant compute deals Anthropic has struckover the past year. TechCrunch reached out to Nscale and Anthropic for more information and will update this story if we hear back. The massive amount of money being sunk into AI compute deals hasspooked a certain segment of investors, who worry that companies are spending too much money for too little profit. Still, Anthropic has pressed on with such partnerships, driven by the belief that it will all pay off in the end. Both Anthropic and Nscale are also currently pursuing IPOs. Anthropic isstill expectedto go public this year. Nscale is also seeking to go public, although Bloombergreportedon Monday that the company is experiencing investor pushback over its proposed valuation of $30 billion.

3 hours ago

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Mamdani says feds have abdicated on AI, urges New Yorkers to push back

Mamdani says feds have abdicated on AI, urges New Yorkers to push back

Two of New York’s sweethearts, Mayor Zohran Mamdani and activist and “Broad City” star Ilana Glazer, spoke about AI at Webster Hall in Manhattan on Monday night, with Glazer posing questions to the mayor about the future of AI in society. Mamdani encouraged New Yorkers to resist the overwhelming feeling that AI is inevitably coming for their jobs, their kids’ minds, and their dignity, and to take back control instead. His message came at a moment when the federal government is doing little to regulate AI, leaving cities to act on their own. At The People’s AI Assembly, an event hosted by theAI Now Institute, a think tank that explores the social implications of AI, Mamdani argued that the technology’s rapid rollout is not inevitable and that public officials should hold AI companies accountable. Last month, Mamdani ordered aban on AI usein elementary and middle schools. Glazer, a parent, said the technology’s arrival in classrooms unsettles her. “It just makes me nervous. It feels so non-consensual, as though…thishasto be in schools. It wasn’t two years ago. Why does it have to be in schools?” she said. Over the summer, the mayor also introduced a policy that would require landlords, brokers, and real estate platforms to clearly disclose when a property’s listing photos or videos are made with AI. The policy is aimed at protecting New Yorkers from getting“house-phished,”or tricked by misleading listings. Both moves challenge the assumption that schools and the public must simply accept AI as it arrives. “Nothinghasto be,” Mamdani said at the event Monday. “There’s a creep that comes with this, and there’s an intent to overwhelm that leaves people feeling as if there is simply no option.” He said there has been a “reckless adoption of technology without any kind of a reckoning with the limitations of that technology,” citing the U.S. military’s February strike on a school in Iran that killed more than 150 people, including at least123 children. Officials involved in the Pentagon’s internal investigation have told Bloomberg that overreliance on AI in targeting was one factor in the attack. “There is this desire to speak about [AI] as if it is infallible, as if it cannot be questioned, as if the only people who can regulate it are the ones who are currently developing it,” Mamdani said, noting that Facebook made similar arguments back in 2008. “What it really is,’ he continued, “is an attempt to escape any kind of accountability at any level, without also jeopardizing the potential valuation from an IPO.” Anthropic is expected to debut on the public markets this year, and OpenAI has said it will go public in 2027. Mamdani criticized the “complete abdication of federal law” when it comes to AI. “At a national level, when the conversation is about artificial intelligence, it’s so often framed in this language of an arms race with China, and any of the humanistic concern, we just push to the side in a language of national competition,” the mayor said. President Donald Trump’sSuperintelligence Task Force, announced earlier this month, largely focuses on allowing powerful AI companies to self-regulate, rather than creating new federal restrictions. That comes despite growing fears about AI’s effect on every facet of human life, including warnings from whistleblowers at Anthropic, Google DeepMind, and OpenAI that AI could lead to human extinction. “As we are looking at what comes after this federal administration, there has to be a very different kind of framework in how we think about AI, talk about AI, the accountability we’re willing to bring forward when it comes to that,” Mamdani said.

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