AI evaluation startup Braintrust has urged customers to revoke and replace their API keys after an earlier breach of customer secrets.

According to an email sent to customers Monday and seen by TechCrunch, the startup confirmed “unauthorized access” in one of its Amazon Web Services (AWS) cloud accounts, which contained API keys used by customers for accessing cloud-based AI models.

“We’ve communicated with one impacted customer and to date have not found evidence of broader exposure,” read the email.

The email asked “every customer to rotate” any of the API keys that they store with Braintrust.

Braintrust disclosed the security incident on its website on Tuesday. “The incident has been contained, and in the meantime, we’ve locked down the compromised account, audited and restricted access across related systems, and rotated internal secrets.”

The company said the cause of the breach is under investigation.

Braintrust spokesperson Martin Bergman told TechCrunch that the company sent the email to customers “out of an abundance of caution” and that it “confirmed a security incident, but there is no evidence of a breach at this time.”

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Braintrust provides a platform designed for companies to monitor AI models and products. Founder and CEO Ankur Goyal previously told TechCrunch that Braintrust is like an “operating system for engineers building AI software.” The startup raised $80 million in a Series B funding round in February, which valued the company at $800 million.

Jaime Blasco, the co-founder of cybersecurity startup Nudge Security who received a breach email alert from Braintrust, told TechCrunch that the incident could have “downstream implications for affected customers,” like AI companies that rely on Braintrust.

Contact Us Do you have more information about this breach? Or other data breaches? From a non-work device, you can contact Lorenzo Franceschi-Bicchierai securely on Signal at +1 917 257 1382, or via Telegram and Keybase @lorenzofb, or Do you have more information about this breach? Or other data breaches? From a non-work device, you can contact Lorenzo Franceschi-Bicchierai securely on Signal at +1 917 257 1382, or via Telegram and Keybase @lorenzofb, or email .

Hackers frequently target corporate accounts on cloud services or third-party platforms as an effective way of stealing secrets, like API keys. Once hackers get their hands on API keys, they can log into the company or customers’ systems appearing as if they are legitimate users, without needing to break into the target company’s systems.

CircleCI, a company that provides development products for software engineers, was hit with a similar cloud data breach in 2023, and similarly asked its customers to rotate “any and all secrets” they stored with the company.

More recently, an EU cybersecurity agency said hackers were able to steal 92 gigabytes of data from a compromised AWS account used by the European Commission. The breach affected 29 other EU entities and the data of dozens of internal European Commission clients.

Lachy Groom, one of Silicon Valley’s most closely watched solo investors, decided to back Indian startup Pronto just 20 minutes into his first meeting with its 24-year-old founder.

The meeting, which took place in February through a mutual connection, led to Groom investing $20 million in Pronto as an extension of its Series B round, valuing the startup at $200 million after the investment — double its valuation just over two months earlier, as TechCrunch had previously reported. The deal came together within weeks, bringing the solo investor on board as the Bengaluru-based startup expands to meet growing demand for on-demand home services in India.

Groom said he was drawn to Pronto’s ambition to build what he called the world’s largest platform for organizing domestic labor, starting with India’s vast and largely unstructured workforce. “The work underneath that is genuinely hard, and most attempts in adjacent categories have struggled with the operational discipline,” he said, adding that Pronto founder Anjali Sardana (pictured above) and her team were operating “at a level I haven’t seen elsewhere in this space.”

Before founding Pronto in 2025, Sardana worked at Bain Capital and venture firm 8VC, where she gained early exposure to investing and high-growth startups. The startup connects households with workers for everyday tasks such as cleaning and basic home services.

The introduction was arranged through Paul Hudson, founder of Glade Brook Capital, who connected Groom and Sardana during her trip to San Francisco earlier this year. Glade Brook has backed startups founded by both: Pronto, which Sardana leads, and Physical Intelligence, where Groom is a co-founder. Hudson and Groom have also backed Indian quick-commerce startup Zepto.

Sardana said Groom’s investment approach is heavily founder-driven. “He indexes two things. One is the founder, and that’s 95% of it. If he loves the founder, then he will invest,” she told TechCrunch, adding that the rest comes down to the scale and potential of the business.

Groom’s bet comes as a clutch of startups in India race to build instant home services platforms, a category that is seeing rapid adoption among urban households as more consumers turn to on-demand help for everyday tasks.

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The opportunity is significant. A recent Bank of America note, reviewed by TechCrunch, estimates the instant home services market in India could grow into a $15 billion to $18 billion industry by the end of the decade, as companies including Pronto, Snabbit, and Urban Company’s InstaHelp compete for share in the fast-growing category.

Competition is intensifying, with heavy capital inflows and aggressive pricing, particularly to attract first-time users. Bank of America estimates that Snabbit and Urban Company’s InstaHelp each account for about 40% of the market, while Pronto has around a 20% share, even as it scales rapidly. The category is expected to remain “burn-heavy” over the next two to three years.

Despite trailing larger rivals, Pronto has been scaling rapidly, growing from around 18,000 bookings a day to 26,000 in just over a month. The startup is focused on driving repeat usage, betting that turning occasional demand into frequent, habit-driven usage will be key to winning the category, with its top 10% of users accounting for about 40% of bookings.

This growth has also brought challenges, particularly in building out supply. Pronto has expanded its network of service workers to 6,500, up from 1,440 in January. But Sardana said demand continues to outpace supply, making forecasting and capacity management key challenges as the startup grows.

Billionaire media mogul Barry Diller doesn’t think OpenAI CEO Sam Altman is untrustworthy, despite recent reporting to the contrary. Onstage at The Wall Street Journal’s “Future of Everything” conference this week, Diller vouched for the AI exec, who has been accused by some former colleagues and board members of being manipulative and deceptive at times.

Diller, who is friendly with Altman, was responding to a question about whether or not people should put their faith in Altman to ensure that artificial intelligence benefits humanity.

In particular, he was asked about the theoretical form of AI known as artificial general intelligence, or AGI, which could one day outperform humans on any task.

The media exec, a co-founder of Fox Broadcasting and chairman of IAC and Expedia Group, said that while he believes Altman is sincere in his pursuits, that’s not really the area of concern people should be focused on. Rather, it’s the unknown consequences that will result from AI.

“One of the big issues with AI is it goes way beyond trust,” Diller said. “It may be that trust is irrelevant because the things that are happening are a surprise to the people who are making those things happen. And I’ve spent a lot of time with various people who’ve been in the creation mode of AI, and they have a sense of wonder themselves. So…it’s the great unknown. We don’t know. They don’t know,” he explained.

“We have embarked on something that is going to change almost everything. It is not under-reported. Now, whether these huge investments are going to come through — I couldn’t care less. I’m not invested in it, but progress is going to be made,” Diller added.

Still, the media mogul said he believes that most of the people leading the charge are good stewards, saying he believes that Altman is sincere and “a decent person with good values.” (Diller wouldn’t say which of the AI leaders he thinks is insincere, we should note.)

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“But the issue is not their stewardship. The issue is … it’s dealing truly with the unknown. They don’t know what can happen once you get AGI, and we’re close to it. We’re not there yet, but we’re getting closer and closer, quicker and quicker. And we must think about guardrails,” Diller noted.

Plus, he warned, if humans don’t think about guardrails, then the alternative is that “another force, an AGI force, will do it themselves. And once that happens, once you unleash that, there’s no going back,” Diller said.

Snap no longer has a deal with Perplexity, the company revealed on Wednesday as part of its quarterly earnings report. The deal, announced last November, would have seen Perplexity’s AI search engine integrated directly into Snapchat. Perplexity was set to pay Snap $400 million in cash and equity over one year as part of the deal.

Snap said that the companies “amicably ended the relationship in Q1″ and that its sales guidance “assumes no contribution from Perplexity.” When Snap announced the deal as part of its third-quarter earnings last year, it said it expected revenue from the partnership to begin contributing to its financials in 2026.

The deal would have seen Perplexity integrated into Snapchat’s “Chat” interface, allowing users to ask questions and receive conversational answers directly within the app. Although the integration was being tested with select users, Snap said in February that the companies had “yet to mutually agree on a path to a broader roll out.”

Snap CEO Evan Spiegel said at the time of the initial announcement that the deal reflected the company’s vision to use AI to enhance discovery on Snapchat, and that Snap was looking forward to “collaborating with more innovative partners in the future.”

Perplexity did not immediately respond to TechCrunch’s request for comment.

Snap revealed on Wednesday that Snapchat’s global daily active users (DAU) rose 5% year-over-year to 483 million, while monthly active users (MAU) also grew 5% to reach 965 million. The company attributed the growth to new features across the app, including Snap Map and its Lenses AR filters.

“In Q1, we returned to growth in daily active users, accelerated revenue growth, expanded margins, and generated strong free cash flow,” Spiegel said in a press release. “We remain focused on disciplined execution as we invest in Specs and our long-term opportunity in intelligent eyewear and look forward to sharing more at AWE on June 16th.”

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Snap said in April that it was laying off roughly 16% of its global workforce, impacting around 1,000 full-time employees, citing advancements in AI for the cuts.

On Wednesday, xAI and Anthropic announced a surprise partnership that has the Claude-maker buying out “all of the compute capacity at [xAI’s] Colossus 1 data center,” roughly 300MW that allowed Anthropic to immediately raise its usage limits. It’s a huge deal for xAI, likely worth billions of dollars. More importantly, it immediately monetized one of the company’s most impressive accomplishments, turning xAI from a consumer to a provider of compute.

It’s tempting to see the arrangement as a shot at OpenAI amid the ongoing lawsuit. But Musk’s explanation on X was that xAI had already moved training to a newer data center, Colossus 2, and xAI simply didn’t need them both.

In the short term, there’s an obvious logic at work. xAI’s existing products are mostly focused on Grok, which has seen plummeting usage since the image generation debacles earlier this year. If xAI’s data center buildout is that much more than what Grok needs to operate, partnering with Anthropic adds a lot of green to the balance sheet. This is especially useful as the company, now combined with SpaceX, speeds toward an IPO. More broadly, having Anthropic lined up as a customer makes it easier to believe that SpaceX’s orbital data center play might actually work.

But beyond the short-term benefit, the Anthropic partnership sends an unusual message about where Elon Musk’s priorities really lie. It suggests the company’s real business may be more about building data centers than training AI models.

It’s rare to see a major tech company treat compute resources this way when companies like Google and Meta, who are also training models, are building more data centers. It’s an easy point to miss, because so many of these companies are working as enterprise AI vendors, online services, and cloud providers all at once. But when forced to make a choice between selling more available compute to customers and preserving some to build their own tools, they reliably choose door No. 2.

Just last month, Sundar Pichai admitted on a call that Google Cloud revenue was lower than it could have been because the company was “capacity constrained” — and when given the choice of renting out their GPUs or using them to develop AI products, Google chose the AI products.

Facebook has faced a more extreme version of the same constraint, spinning up an entirely new cloud apparatus just to ensure they would have enough GPU power to chase Mark Zuckerberg’s AI ambition. As he put it when announcing Meta Compute in January, “How we engineer, invest, and partner to build this infrastructure will become a strategic advantage.”

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The key word there is “strategic.” Both Zuckerberg and Pichai are looking toward a future where AI is powering the most popular and lucrative systems in the world. Computing power isn’t just a way to satisfy today’s inference demand, but to build tomorrow’s products — and running short on compute means missing out on that chance.

By focusing on data centers (earthbound and otherwise), xAI is positioning itself more like a neocloud business: buying GPUs from Nvidia and renting them out to model developers like Anthropic. It’s a far more difficult business, squeezed by both chip suppliers and the shifting cycles of demand. The valuations for most active neoclouds reflect that reality: xAI was valued at $230 billion in its January funding round; CoreWeave, which oversees a comparable quantity of computing power, is worth less than a third of that.

Musk’s version of a neocloud is more ambitious, as you might expect. Some of the data centers might be in space — at least by 2035, if things go according to plan. xAI will be making its own chips at the Terafab, which will take away some but not all of Nvidia’s pricing power. But none of it changes the basic economics of the neocloud business.

As recently as the February all-hands, xAI had real ambitions in software. That was the presentation that unveiled the orbital data center project, but it also teased significant ambitions in coding (since bolstered by the Cursor partnership) and interesting ideas like leveraging computer use into full-scale digital twins (in the unfortunately named Macrohard project). These are the kind of long-horizon projects that need committed computing resources to succeed. As long as xAI is selling large quantities of compute to its competitors, it’s hard to think such new ambitions have much of a future.

In Brief

Business insurance startup Corgi announced on Wednesday a $160 million Series B, led by TCV, valuing the startup at $1.3 billion, the startup’s co-founder Nico Laqua said on LinkedIn.

This comes just four months after the company announced a $108 million Series A. The company has now raised $268 million in funding to date, Laqua said, and has become Y Combinator’s latest unicorn.

Laqua started the company with Emily Yuan in 2024 and was part of YC’s Spring 2024 batch. Corgi, which names Deel and Artisan as customers, offers coverage for general liability, cyber liability, and tech and AI liability. Other investors in the round include Kindred Ventures, Leblon Capital, and First Order Fund.

Corgi did not immediately respond to our request for comment.

Microsoft is weighing whether to delay or scale back one of its most ambitious clean energy goals as its rapid buildout of AI data centers puts pressure on its ability to meet those targets. Microsoft has yet to make any public announcements, but according to Bloomberg the company is having internal discussions over its hourly clean energy matching goal.

The tech company has said that by 2030 it intends to match 100% of its hourly energy use with clean power on the same grid. But Microsoft’s rush to build AI data centers has apparently sparked debate within the company about whether the pledge has become an impediment to its ambitions.

Microsoft declined to comment on the internal debate over the hourly matching goal. Instead, a spokesperson told TechCrunch the company continues “to look for opportunities to maintain our annual matching goal.”

Hourly targets like the kind Microsoft has set for itself are more rigorous than annual targets. Because the grid is a balanced system — the supply and demand of electrons needs to be matched on a near-instantaneous basis — hourly matching helps develop clean energy sources that more closely align with a company’s usage patterns.

Annual targets are more lenient. They are effectively accounting tricks that could, for example, let a company buy more solar power than it might use at midday. Other customers on the grid use that energy, but the company that paid for the solar panels gets to claim the renewable power they make. It’s a tidy arrangement that has sped the deployment of wind, solar, and batteries. But on its own, annual targets won’t eliminate fossil fuels entirely. Hourly targets help foster renewable development that more closely mimics how a true net-zero world would be powered.

Big tech companies like Microsoft, Meta, Google, and Apple have generally led on emissions reductions, setting aggressive net-zero targets. Many have eliminated their carbon emissions on an annual basis. Microsoft, for instance, said it met that goal last year.

But as data centers grow in size and number, those same companies are turning to natural gas. Microsoft is included in that list; last month, the company said it was working with Chevron and Engine No. 1 to build a massive natural gas power plant in West Texas that could eventually generate up to 5 gigawatts.

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Despite the West Texas project, Microsoft is widely viewed as a leader among tech companies pursuing net zero emissions. By 2030, Microsoft intends to remove more carbon from the atmosphere than its operations produce.

Part of the company’s renewable push has been driven by an internal carbon tax. The Microsoft spokesperson did not reply to questions about the company’s carbon tax. If it remains in place, some of the internal debate surrounding hourly matching might revolve around a cost-benefit analysis of the shift.

If Microsoft were to abandon its hourly-matching target, the company would also lose some leverage in efforts to sell the public on its data centers.

As data centers have proliferated, the general public has begun to push back against them, citing concerns over pollution, power prices, and water use. When Microsoft brings its own clean power to a project, it can plausibly say it has addressed two of those concerns. Without it, new data centers might be harder to sell to the public.

Robinhood CEO Vlad Tenev is touting the success of the fintech’s new Ventures Fund I, which allows retail investors to invest in private tech companies like Stripe, Oura, Databricks, OpenAI, and others, through a publicly traded fund listed on the NYSE. “We had something like over 150,000 retail investors participate in the IPO, so it’s quite democratized,” noted Tenev in an interview at The Wall Street Journal’s Future of Everything conference this week.

The fund, which launched in March, arrives at a time when the term “unicorn,” which once referred to the rare billion-dollar startup, has become outdated. When AI model providers like OpenAI and Anthropic are raising capital at valuations of $850+ billion to $900 billion, another word besides “unicorn” is needed.

“We call them frontier companies,” said Tenev, explaining how Robinhood differentiates these larger, private companies from other startups.

“There are private companies that are raising capital at valuations in the high hundreds of billions. You’re going to see, perhaps, multiple private companies getting into the trillions [in valuation] before the IPO — before retail investors can participate,” he said.

Robinhood’s initial fund has exposure to many tech companies that have yet to go public, including most recently OpenAI, which joins Mercor, Ramp, Airwallex, Boom, and others.

Tenev believes the new fund makes sense as part of Robinhood’s broader mission to democratize access to markets for retail investors.

Initially, the company did this through its zero-commission trades, which significantly increased retail participation in the public markets. Now it sees investing in large, private companies as the next step.

“You can think of [the new fund] as a publicly traded venture capital firm with daily liquidity. No accreditation requirements and no carry,” Tenev said in the interview. “So just a competitive management fee, no carry — which, for those of you familiar with venture capital, typically, when you invest in a fund as an LP, you pay a management fee, but there’s also a carry of typically around 20%, which means 20% of your profits go to the fund manager.”

Tenev believes that, due to the size of these companies, retail investors should be able to get in earlier than the IPO — especially given how many companies are choosing to wait to go public.

“The aspiration is, if you’re a company raising a seed round and a Series A round — so, just first capital — retail should be a big chunk of that round, much like it now is in the public markets,” Tenev said. “And we should let those people in at the ground floor, so that they can actually benefit from this potential appreciation that’s increasingly happening in the private markets,” he added.

In late August 2017, key figures at OpenAI (then a small nonprofit research lab) gathered to discuss how they would create a for-profit to commercialize its technology and raise the funds needed to realize AGI.

Elon Musk was demanding full control of the company and had just given each of his co-founders a Tesla Model 3. CTO Greg Brockman said he saw that as way of buttering them up at a time when Musk and Sam Altman were vying to win support for their respective visions of the company’s future. OpenAI’s head of research, Ilya Sutskever, had commissioned a painting of a Tesla to give Musk during the meeting as a friendly gesture.

The conversation didn’t follow that mood: When Musk was told the others would not accede to his demand for control of the company, Brockman said he got angry and upset. He sat for several minutes thinking quietly.

Then, in Brockman’s telling, Musk said, “I decline.” The SpaceX and Tesla founder “stood up and stormed around the table…I thought he was going to hit me. He grabbed the painting and started to storm out of the room. And then he turned around and said, ‘When will you be departing OpenAI?’”

Brockman and Sutskever didn’t leave or commit to Musk’s vision. Musk stopped his regular donations to the company’s operating budget, and within six months, he would leave the board, though he paid for office space the company shared with Neuralink until 2020.

As today’s legal battle over the future of OpenAI proceeds, scrutiny has settled on a key period in 2017 when the organization’s original co-founders disagreed about who would control its future, eventually bringing us Musk’s lawsuit against his co-founders.

We have yet to hear from Sam Altman, but OpenAI president Greg Brockman testified for two days, often referencing a personal journal that offers a rare insight into what it’s like to be a 30-year-old tech executive in a pitched battle with Elon Musk.

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“It’s very painful,” Brockman said of the publicity around the journal, which he called “deeply personal writings that were never meant for the world to see. [But] there’s nothing in there I’m ashamed of.”

Cutthroat negotiations between startup founders are rarely shared so publicly, especially when a company becomes as world-changing as OpenAI.

We saw a recent taste of this rancor when OpenAI’s lawyers shared a text message Musk sent to Brockman two days before the trial began: “By the end of this week, you and Sam will be the most hated men in America. If you insist, so it will be.”

The jury won’t see that note, but Musk’s lawyers have done their best to realize its spirit. They are trying to show the court that Altman and Brockman “stole a charity,” while OpenAI’s legal team tries to show that Musk had the exact same plan in mind.

The inciting incident for all of this was when an OpenAI model defeated the top human player in the video game DOTA II. Brockman said that convinced everyone in the organization that compute was the key resource to create powerful AI tools, but that fundraising purely as a nonprofit would be insufficient.

That led to talks about a for-profit subsidiary, of which Musk wanted “unequivocal” control, at least at the start. The other founders proposed equal shares, and perhaps more equity commensurate with a cash investment. Another idea on the table was somehow connecting OpenAI to Tesla’s AI work. Shivon Zilis, an OpenAI advisor who acted as a go-between for Musk and the team there, said there were more than 20 variations on the plan.

But when the other founders wouldn’t give Musk control, their partnership unraveled.

“It should not be the case that there exists one person with full and absolute control over OpenAI,” Brockman testified. Brockman and Sutskever discussed a plan to kick Elon off OpenAI’s board in order to move forward, resulting in November 2017 journal entries that Musk’s lawyers have focused on.

‘[C]an’t see us turning this into a for-profit without a very nasty fight,” Brockman wrote. “[I’m] just thinking about the office and we’re in the office. and his story will correctly be that we weren’t honest with him in the end about still wanting to do the for profit just without him….btw another realization from this is that it’d be wrong to steal the non-profit from him. to convert to a b-corp without him. that’d be pretty morally bankrupt. and he’s really not an idiot.”

That “steal the non-profit” line may seem damning, but the context, according to Brockman, was whether or not to try and toss Musk off the board. They ultimately did not do that. Musk left the board voluntarily in February 2018, concluding that “OpenAI is on a path of certain failure,” saying he planned to focus more on AI at Tesla.

Brockman described his reflections as an effort to determine whether he would be satisfied with his work life.

“This is the only chance we have to get out from Elon,” he wrote during the talks. “Is he the ‘glorious leader’ that I would pick? We truly have a chance to make this happen. Financially what will take me to $1B?”

That last reflection was also seized on by Musk’s lawyers as a sign that Brockman was thinking more about his personal wealth than the nonprofit’s mission. Brockman said his current stake in the company is worth almost $30 billion, which became an opportunity for Steve Molo, the main trial attorney for Musk, to berate him.

“Why you didn’t take the $29 billion more than the billion you said you would be good with, and donate that to the charity?” Molo demanded.



“Look at what we accomplished,” Brockman replied. “The OpenAI nonprofit has over $150 billion of OpenAI equity value. That is something we have built through hard work, blood, sweat, and tears, all this time since Elon has left.”

Molo also dwelt on emails from where Brockman said he will donate $100,000 to OpenAI, something he never did. Ironically, Brockman might be best known to the public for making the largest donation of the 2025 political cycle, $25 million given to MAGA Inc., a SuperPAC supporting President Donald Trump, but that didn’t come up in the trial.

Molo did mock Brockman’s description of the charged meeting around his control of the company as Musk being “mean” to Brockman, and suggested that Brockman didn’t understand the governance issues the way Musk, a serial founder, did.

Brockman, though, said Musk didn’t understand AI. “He did not and does not know AI,” he testified, describing Musk dismissing an early demonstration of the software that would become ChatGPT. “We did not think he was going to spend the time required to actually get good at it.”

“The fact that Elon saw this very early version of the research, that really set all these things in motion, [and] didn’t recognize that spark — that was exactly the kind of thing that was critical to avoid happening in this environment,” Brockman said.

In 2019, OpenAI would create a for-profit and use it to raise $1 billion from Microsoft. The company would raise a further $13 billion from the software giant over the next four years, fueling its rise as the leading AI frontier lab. It also fueled the net worth of the company’s executives and employees, as well as the assets held by OpenAI the nonprofit.

And ultimately, those deals fueled Musk’s suspicions that Altman and Brockman got one over on him, leading him to file his suit in 2024. The trial is expected to continue through next week.

A U.S. court has sentenced Latvian hacker Deniss Zolotarjovs to more than eight years in prison following his conviction for carrying out ransomware attacks.

The Justice Department accused the hacker of working for a notorious Russian ransomware gang called Karakurt, which was led by former leaders of the Akira and Conti ransomware gangs, who were sanctioned by the U.S. Treasury for their alleged links to Russian intelligence.

Prosecutors said members of Karakurt targeted U.S. government entities with attacks that disrupted 911 emergency dispatch systems, and also stole children’s health information. Zolotarjovs was responsible for “escalating pressure” on victims who resisted the gang’s ransom demands, the DOJ said.

While Zolotarjovs’ conviction is notable in itself, U.S. prosecutors said in their press release that the ransomware gang relied on access to Russian government databases and law enforcement connections to intimidate its victims, further underscoring the links between the activities of cybercriminals and the Russian state.

Security researchers have long accused the Russian government of shielding ransomware gangs and malicious hackers from Western law enforcement, including by refusing to extradite its citizens accused of damaging hacks. U.S. officials in recent years have said Russia has become a “safe haven” for cybercriminals, citing the threat from ransomware as one of the top national security challenges facing the United States.

According to the DOJ, the Karakurt ransomware gang “fueled corruption” in the Russian government; these ties to officials allowed the gang’s leaders to avoid paying taxes to the state, and the gang regularly paid bribes to officials who exempted members from compulsory Russian military service.

The Russian Foreign Ministry did not respond to TechCrunch’s request for comment.

Per the DOJ, the Karakurt gang targeted more than 54 companies, with at least $15 million in ransoms paid by the victims. Karakurt does not appear to be an active ransomware gang; some operations change owners and names, sometimes to evade sanctions.

Zolotarjovs was arrested in the country of Georgia in 2023 and extradited to the United States in August 2024. He later pleaded guilty.

(h/t @realhackhistory.org)

In Brief

SpaceX, Elon Musk’s space company that also houses his AI company, xAI, is considering spending $55 billion, at least initially, to build a semiconductor factory in Grimes County, Texas, according to a proposal on the county website.

The company estimates it may spend a total of $119 billion on the project, which would be a “multi-phase, next-generation, vertically integrated semiconductor manufacturing and advanced computing fabrication facility,” according to the filing.

Musk has previously outlined plans for the project, dubbed “Terafab,” that will also see Tesla contributing resources. The companies have roped chipmaking giant Intel into the effort, aiming to develop chips for AI servers, satellites, SpaceX’s proposed data center in space, as well as autonomous Tesla vehicles and robots.

The billionaire has said the manufacturing facility will, sometime in the future, manufacture enough chips to provide 1 terawatt of power per year, arguing that semiconductor manufacturers aren’t making chips quickly enough for his companies’ artificial intelligence and robotics needs. “We either build the Terafab or we don’t have the chips, and we need the chips, so we build the Terafab,” he wrote.

However, Musk wrote in a tweet on Tuesday that Grimes County, Texas, was only one of several locations under consideration for the factory.

The filing comes as Musk has doubled down on ensuring xAI has enough computing power available to train and power its Grok series of AI models. He’s also intent on capitalizing on the demand for AI compute by building data centers in space, which he has cited as a big reason for combining xAI with SpaceX. The combined entity is said to have a valuation of $1.25 trillion and is expected to go public in June.

In Brief

DeepSeek is in talks to raise its first round of venture capital, and in just a few weeks, its potential valuation has soared from $20 billion to $45 billion, the Financial Times and Bloomberg reported.

The Chinese AI lab came to prominence in early 2025 after launching a large language model that trained on a fraction of the compute power and at a fraction of the cost of the big U.S. models like those from OpenAI and Anthropic. It has since kept reasonable pace with the top models in the world in areas like reasoning and coding while remaining open weight (versions are freely available on Hugging Face).

Founded by Chinese hedge fund billionaire Liang Wenfeng, who controls nearly 90% of the company, the lab has not previously sought out investors, the FT reports. However, faced with competitors poaching DeepSeek’s researchers, Liang opted to raise funds in order to offer employees shares in the company, sources tell the FT.

The round is said to be led by the state investment vehicle China Integrated Circuit Industry Investment Fund, Bloomberg reports. China is seeking to fund homegrown AI technology to sidestep the difficulty of obtaining U.S. technology, particularly chips. DeepSeek has been optimized to run on chips made by China’s hardware giant Huawei Technologies. That combo is considered a powerful duo for the nation to develop its own AI to rival the United States. The country’s cloud giants Tencent and Alibaba are also reportedly in talks to participate, per Bloomberg.

DeepSeek could not be immediately reached for comment.

In Brief

Chrome on Android now lets users share their approximate location with websites rather than their precise location, Google announced this week. The tech giant says that while some cases require precise location, such as when you’re placing a delivery order or trying to find the closest ATM, there are instances when your approximate location is enough, like when you’re getting access to local weather and news.

“By letting you share your approximate location, we’re giving you more control over your location data,” Google explained in a blog post. “And you can still share your precise location when it’s needed — e.g., for navigation — so you won’t lose functionality.”

Image Credits:Google

Google plans to bring this feature to the desktop in the coming months. The company did not share a timeline for when, or if, the feature will launch for Chrome on iOS.

The company will also be introducing new APIs that let web developers request either an approximate location or specify when a precise location is necessary. The tech giant says it encourages developers to review their location needs and only request precise location when it’s essential for the site’s functionality.

The new feature is a small win for Android users, as it gives them more control over how much location data they share with websites.

Google is updating search to refine its AI experience by adding additional context to links, like excerpts from web forums and blogs, as well as a feature that highlights links from a user’s news subscriptions.

While citing web forums and discussion boards can help users find answers to more niche queries, this design choice could also prove chaotic.

Two years ago, Google overhauled its search experience to put AI front and center — when you search for something, Google will often summon an “AI Overview,” which has spurred mixed reception from users. People quickly pointed out how the feature could be exploited, since it failed to recognize sarcasm or information that comes from dubious sources. (It cited The Onion when telling someone to eat “one small rock per day,” and used Reddit to advise someone to put glue on their pizza to make the cheese stick better.)

Though Google’s AI Overviews have improved significantly, they still — like anything powered by an LLM — are prone to hallucination. A recent New York Times analysis found that the AI Overviews were correct about nine times out of 10. But for a company that processes trillions of queries a year, that success rate would mean that hundreds of thousands of searches turn up inaccurate results every minute.

Of course, not every search has an objective yes-or-no answer, which is why Google might want to pull in voices from web forums where people discuss such questions — there’s a reason why people often add “Reddit” to the end of their Google searches.

“For many searches, people are increasingly seeking out advice from others,” Google explains. “To help you find the most helpful insights to explore further, AI responses will now include a preview of perspectives from public online discussions, social media, and other firsthand sources. We’re also adding more context to these links, like a creator’s name, handle, or community name, to help you decide which discussions you might want to read or participate in.”

But now Google is complicating the role of its AI Overviews. Is the AI Overview supposed to answer a question, or is it supposed to serve you a variety of sources that might have the information you’re looking for? Isn’t that basically just a normal Google search?

Google will, at least, add more context to where its AI Overview commentary comes from, which might help users decipher if they’re getting information from a trustworthy source. It’s similar to how ChatGPT or Claude will sometimes provide links that are supposed to back up its claims.

Still, we’d recommend double-checking that the AI is not hallucinating the validity of these citations.

Genesis AI, a startup that raised a $105 million seed round to build foundational AI for robotics, has unveiled its first model, GENE-26.5, and it comes with surprise hands. In a demo video, the company showcased various advanced tasks performed by a set of robotic hands it has designed in-house.

“The model has always been the goal, because a better model means better intelligence,” Genesis co-founder and CEO Zhou Xian told TechCrunch. But the company soon realized that it needed control over the hardware. “So we decided to go full stack,” he said.

Other well-funded companies operate at the intersection of AI and robotics — such as Physical Intelligence and Skild AI. Zhou also acknowledged that “there’s probably 50 or 100 robotic hand companies out there.” But he and his co-founder Théophile Gervet hope that building their own will give them the upper hand.

The key difference is that Genesis’ hand has the same size and shape as a human hand — rather than the two-finger grippers many robotics companies have been using — reducing the gap with real-world conditions.

“That lets us collect a lot more data than was previously possible, to train a model that can do many more tasks,” said Gervet, a former research scientist at Mistral AI who is now Genesis’ president.

Of all the physical manipulation tasks showcased in the video below, Gervet’s personal favorite is cooking, because it proves that the robot has been able to complete a long series of difficult tasks, such as cracking an egg and slicing a tomato. But Genesis has also tasked its robots with preparing smoothies, playing the piano, and solving Rubik’s cube — a robotics gimmick.

Other tasks, such as lab work, are closer to what could be the commercial applications of Genesis’ technology. But what happens behind the scenes is just as important: The startup has also developed a sensor-loaded glove that works as a real-life double of its robotic hand, collecting data that can more readily be used.

“Our idea was that if we could design a robotic hand that tries to mimic a human hand as much as possible, we can instantly unlock huge amounts of human data without having to worry about what people call the ‘embodiment gap’ in robotics research,” Zhou said.

Others have tried their hand at that problem; the main novelty is how Genesis combines this with its model. The current version is named GENE-26.5 for May 2026, but Zhou expects there will be many iterations, thanks to the simulation it has developed. “The real bottleneck for the iteration speed of the model is evaluation. So this helps us speed up model training a lot,” he said.

Beyond simulation, though, data will be key to training models that can help robots perform more tasks. That’s also where Genesis’ glove could come in handy. Gervet said that, unlike clunky data collection devices that get in the way, it is just as light and easy to wear as the security gloves already used in many industries, while relatively cheap to make.

“We’re in talks with a lot of customers right now, and a lot of the value of a glove would be that, for the first time, you can wear the data collection device when you’re doing your daily job, whether it’s a lab technician for pharma or for manufacturing,” Gervet said. This would also be complemented by “egocentric video data” — people filming themselves doing the task.

Still, it remains to be seen whether workers would be happy to wear the very gloves and cameras that could train robots to replace them, and whether they will get extra pay for that training. That will be between Genesis’ customers and their employees, Gervet suggested. “We haven’t nailed the details yet,” he said.

Either way, they may decide not to share that data with the startup, the founders acknowledged. But the startup also has avenues of its own to build its “human skill library” — it could also pay third-party partners to collect data. Its model is already trained on “massive amounts of human-based internet videos,” according to a press release that didn’t mention compensation.

Combined with its simulation system, this could help Genesis lower the costs of its technology for real-world applications like the one it has demonstrated. “This marks an important milestone for their team and the robotics industry more broadly,” said Google’s former CEO, Eric Schmidt, who invested in the startup.

In July 2025, just a few months after its creation, the startup had emerged from stealth with a $105 million seed round co-led by Eclipse and Khosla Ventures, with additional backers including Bpifrance, HSG, and individuals like Schmidt, but also Xavier Niel, Daniela Rus, and Vladlen Koltun.

This funding helped Genesis increase its headcount. With offices in Paris and California, it has also expanded to London. “One big reason we decided to be in Europe is there is a huge talent density across the whole continent,” Gervet said. Its team of 60 people is split around “40-45% in Europe and 50-55% in the U.S.,” and the startup is currently hiring in all three locations.

Aside from hiring, the company also plans to reveal its first general-purpose robot shortly, which Zhou told TechCrunch will be a full-body robot, not just hands. But he insisted that the roadmap is still the same.

“Our goal is to build the most capable robotic system,” he said.

You might think the big story out of Match Group’s first-quarter earnings is Tinder’s turnaround. The dating app’s revenue is slightly up again after quarter-after-quarter of declines.

But we’d like to point to a comment the chief financial officer made about how the company is slowing its hiring right now because it needs more money to pay for AI tools for its employees.

Ah, yes, the good ol’ “let’s blame AI” strategy!

While speaking to analysts on the first-quarter earnings call, Match Group CFO Steven Bailey talked about how the dating app giant was investing in AI technology for internal use at the company — as well as how Match was paying for it.

“We’re making a big push around AI enablement. We’re giving every employee in the company access to all the cutting-edge tools. We’re giving them the training they need to succeed. We’re setting expectations. We really want to become an AI-native company,” Bailey said.

“We think it’s a huge opportunity. But these tools cost a lot of money, as I’m sure you know, and so the way we’re helping to pay for that is by slowing our hiring plans for the rest of the year,” he added.

The company assured investors that the impact would be cost-neutral, as the slowed hiring and lower headcount would make up for the increased software expenses. Plus, Match Group is betting that the increased productivity from employees’ use of AI will ultimately increase revenue growth, the number-cruncher explained.

While on the surface this looks like another example of AI taking people’s jobs — in this case, forcing a company to lower its number of open positions — there’s likely more nuance to this story.

Let’s keep in mind that Match Group’s flagship app, Tinder, has been struggling in recent years. This quarter may be the start of a turnaround, as monthly active users declined by 7% in March compared with the far-steeper 10% drop a year ago. Tinder registrations also grew for the first time since 2024, but by a mere 1%, as Bloomberg pointed out.

This is perhaps a positive sign for Tinder. Or it might be a brief blip driven by users’ curiosity around various product improvements and new features, like IRL events. Time will tell.

Dating meets a generational shift

Match Group remains a company that has to work to squeeze more money out of an oft-dwindling, less-active user base — which, to the company’s credit, it did exactly that. Match’s revenue was $864 million in the first quarter, up 4% year-over-year. However, its next-quarter estimates are coming in lower — around $850-$860 million, down 2% to flat year-over-year.

All these struggles come after many months of what appears to be a growing disinterest in the use of dating apps by younger people. This generational shift sees people opting to meet up in real life, perhaps by pursuing an interest, like running, book clubs, or a hobby that connects them with other people, which then, in turn, expands their network, increasing their chance of meeting someone new.

The trend coincides with a resurgence of nostalgic tech, like digital cameras, flip phones, boomboxes, and even landlines, signaling a generation that’s feeling burned out by always-on connectivity and looking for analog pleasures.

Match Group is aware of this significant shift and says it’s pivoting to address the challenge by increasing the number of its own IRL events.

“Gen Z desperately wants to connect. They know they want to meet new people. They just want to do it in a low-pressure, low-stakes way that doesn’t feel like a job interview,” Match’s CFO Spencer Rascoff told investors on the call. “Traditional dating apps are very highly structured and can be intimidating to a user under 30. So, I think the growth of these alternative ways to meet new people speaks to how Gen Z is trying to find lower-pressure ways to connect.”

“We’ve obviously adapted our roadmap to this reality,” he said.

Apple has agreed to pay $250 million to settle a class action lawsuit over how it marketed its AI features ahead of the launch of the iPhone 16. The Financial Times was the first to report the news.

The lawsuit alleged that Apple exaggerated the breadth of features Apple Intelligence would bring, which included a significantly upgraded version of its assistant, Siri. The complaint alleges that the company created the impression that advanced AI capabilities would be available to users sooner than they actually were. In particular, the plaintiffs allege that Apple overstated both the readiness and functionality of these features, particularly the promised improvements to Siri, which have yet to fully materialize.

As a result, the complaint claims, people who bought the iPhone 15 or iPhone 16 believed they were paying for cutting-edge AI tools that were not actually available at the time of purchase. The lawsuit framed this as false advertising, and says Apple’s marketing influenced buying decisions based on features that were incomplete or delayed.

Apple did not admit to wrongdoing in court, but has chosen to settle the case rather than continue with litigation. Under the proposed agreement, eligible U.S. customers who purchased the iPhone 15 or iPhone 16 between June 10, 2024 and March 29, 2025 could receive up to $95 per device.

Apple has been touting a more advanced version of Siri ever since it unveiled Apple Intelligence in 2024 during WWDC. The anticipated updates are expected to help Siri function more like modern AI chatbots such as ChatGPT or Claude. The upgraded experience is rumored to be powered by Google Gemini, though newer reports state the company’s next iPhone operating system may let users choose from a number of third-party large language models.

The settlement arrives ahead of Apple’s annual developer conference on June 8, when the company is expected to preview a version of its AI-enhanced Siri.

When companies are looking for opinions or advice on a project, they tend to go to LinkedIn or use expert networks such as GLG, Third Bridge, or AlphaSights. But they often don’t find quality inputs, despite their searches.

Today, these sites ask experts to fill in a form based on their job title, which is then used to match them with companies in need of their help.

London-based Ethos thinks that AI can improve both sides of this experience. For experts, it offers voice-powered onboarding to ask a broader set of questions and get more data about their knowledge in various domains that their job titles don’t cover. For companies, Ethos can better match natural language queries posed by these organizations for their project, thanks to the wider range of data it has collected.

Ethos said that its voice-based onboarding and data allows it to answer complex client questions like, “Find me people who worked at a funded startup by A-grade investors solving for finance automation.”

Another example the startup gave was how a pharma company using its platform could search for doctors who specialize in a certain area, but who have also written papers on the subject or have an understanding of drug development.

Image Credits:Ethos

Today, Ethos announced a $22.75 million Series A round led by a16z with participation from General Catalyst, XTX Markets, Evantic Capital, and Common Magic.

a16z’s Anish Acharya thinks that legacy platforms like LinkedIn and GLG only show shallow signals with job titles. He believes that Ethos captures different sub-specializations through its voice interview process with curated questions.

“I think voice is the original form of human communication. Most people, you know, most people don’t know how to write their story down in a very succinct, compelling, and accurate way. Voice is a big unlock for Ethos,” Acharya told TechCrunch over a call.

How Ethos is scaling its network

Ethos was founded by James Lo and Daniel Mankowitz in 2024. Lo previously worked at McKinsey and later at SoftBank, where he worked on the transformation of companies like WeWork and Arm. Mankowitz worked as an AI researcher at DeepMind, where he worked on YouTube’s video compression algorithm, Gemini, and the AlphaDev sorting algorithm.

James Lo and Daniel Mankowitz Image Credits:Ethos AI by ivan weiss

Both founders arrived at tackling the problems of building an expert network from different angles. Lo always wanted to work on providing the right economic and employment opportunities to people. Mankowitz thought that the economy is a knowledge graph of people, companies, and products, and using the right algorithms, you can match these entities with each other.

“Traditional expert platforms almost purely focus on a mixture of job titles and job descriptions. What we observe is that most clients and most employers are not looking for a job title company. They’re looking for a specific skill and a specific capability. We also observed that, over time, looking for a skill and capability is going to gradually merge between the human economy and the agent economy,” Lo said.

Beyond the data provided by experts, Ethos also looks at other public sources like blogs and academic papers, along with social links to match companies with the right people.

The company also conducts interviews through its own platform using voice agents and extracts insights. Startups like Listen Labs and Outset already provide a way for companies to use conversational AI for interviews, offering some competition on this front. But Ethos thinks that its network of experts is better suited for certain clients than its competitors.

Ethos doesn’t name its client base, but said that top hedge funds, private equity firms, leading foundational AI labs, and enterprise consulting were already using its product. It’s taking 30% or more as a per-project fee from businesses, depending on the nature of the project. The company noted that it’s on track for “an eight-figure annualized revenue” but didn’t provide specific numbers.

Image Credits:Ethos

It also didn’t say how many experts are on the platform, but said that roughly 35,000 people are joining each week. (Ethos sends invites to people whom they think can benefit from it.)

One challenge for the startup is growing an expert user base that’s relevant to its clients. The company said that AI labs spending money to map human talent has been helping its cause.

“Our perspective here is the AI labs have — are pointing a giant capital gun at every economically valuable occupation in the world. They’re trying to map out every profession. And so that’s an amazing tailwind for us,” Lo said.

He noted that these labs are building professional services in areas of law, health, finance, and management, so they would want all kinds of experts in these networks to build out their models and get feedback about their products and strategy.

The company has eight people on its team now, and its goal is to keep the team compact while scaling up.

Aurora Innovation will start hauling loads in driverless trucks for distribution giant McLane, the latest company to adopt the startup’s autonomous vehicle technology following a multi-year pilot program.

Under the commercial agreement announced Wednesday, trucks outfitted with Aurora’s self-driving system will be used to transport goods between Dallas and Houston. These trucks will operate autonomously and will not have a human safety driver on board who can take over. However, Aurora will still have what it describes as a “human observer” sitting in the cab — who does not operate the vehicle — per an agreement it has with truck manufacturer Paccar.

Aurora said it plans to expand to new routes between McLane distribution centers across the U.S. Sun Belt by the end of the year.

The companies launched a pilot program in 2023 using autonomous trucks with a human safety operator. The pilot eventually expanded to two round-trips daily between Dallas and Houston.

McLane recently approved moving to driverless operations, which now run seven days a week between the two Texas cities.

The companies are taking a novel approach to this route, using Aurora’s driverless tech for the long-haul portion of the trip before handing it over to a McLane truck driver who makes local deliveries to customers like fast food restaurants. Aurora said this handoff occurs at the company’s Dallas and Houston terminals located right off the freeway.

The commercial contract is the latest win for Aurora as it tries to transition from a developer of autonomous trucks to a commercial operator earning money on its driverless routes. And it comes a year after the company launched its commercial self-driving truck service in Texas. Since then, Aurora has landed a commercial agreement to haul frac sand for Detmar Logistics. Last month, Hirschbach Motor Lines agreed to buy 500 Aurora-powered trucks; that agreement, which is outlined in a memorandum of understanding, is expected to close later this year.

Today, the company operates driverless trucks — some with a human observer still in the cab — on routes between Dallas and Houston, Fort Worth and El Paso, El Paso and Phoenix, Fort Worth and Phoenix, and Laredo and Dallas.

Aurora reports its first-quarter earnings Wednesday after the markets close.

The year keeps moving swiftly, and so is all of our planning for TechCrunch Disrupt 2026! We have an exciting new panel in store for founders in need of merger and acquisition advice … but first, we have a limited-time ticket offer to share.

Disrupt will once again be held in San Francisco’s Moscone West from October 13–15, and for a limited time, attendees can also bring a colleague, co-founder, investor, or teammate for less! You can buy one Disrupt 2026 pass here, and get 50% off a second pass of the same ticket type with a limited-time offer that ends May 8 at 11:59 p.m. PT.

As for the kind of programming that’ll keep you locked in during Disrupt’s three days, let’s dive into our newest panel that will be on the Builders Stage.

Image Credits:TechCrunch

Hear at Disrupt how M&A is now an early-stage strategy

If you’ve been following our recent coverage, acquisitions and acqui-hires remain in vogue, especially within the AI scene. Whether it’s OpenAI buying Hiro, Anthropic acquiring Vercept, Google taking the team behind Hume AI, or Databricks pulling in two startups just for its security product, it’s been a busy year!

And being acquired is far from being the end of a long road for founders; it can be part of their early-stage journey. And with those, and many other acquisitions in mind, we’ve gathered an expert panel to help equip founders with what they need to know about all the M&A options that lie before them.

Their perspectives will equip you with a playbook for creating optionality for potentially selling, ways to make your startup more enticing to buyers, and the realities of going through the acquisition process. And for some background on our panel, let’s learn more about our industry leaders.

Aklil Ibssa, Head of Corporate Development and M&A, Coinbase

Image Credits:Coinbase

Aklil Ibssa brings a buyer-side perspective from one of the biggest companies in crypto, as he leads the company’s acquisition strategy and execution, helping identify where Coinbase should buy, invest, partner, or build. He’s overseen more than 14 acquisitions and nearly 50 early- and later-stage investments, and as one of the first hires on Coinbase’s corporate development team, he contributed to an M&A program that’s become among the most active in crypto, with more than 40 total completed acquisitions.

Techcrunch event This Week Only: Buy one pass, get the second at 50% off

Your next round. Your next hire. Your next breakout opportunity. Find it at TechCrunch Disrupt 2026, where 10,000+ founders, investors, and tech leaders gather for three days of 250+ tactical sessions, powerful introductions, and market-defining innovation. Register before May 8 to bring a +1 at half the cost. This Week Only: Buy one pass, get the second at 50% off

Your next round. Your next hire. Your next breakout opportunity. Find it at TechCrunch Disrupt 2026, where 10,000+ founders, investors, and tech leaders gather for three days of 250+ tactical sessions, powerful introductions, and market-defining innovation. Register before May 8 to bring a +1 at half the cost. San Francisco, CA | REGISTER NOW

Most importantly for founders, he’s seen firsthand how strategic buyers evaluate young companies: whether for technology, talent, licenses, product velocity, and beyond. And he’ll be able to speak to acquisitions, including Deribit, Liquifi, and Echo, and prominent investments in startups like Kalshi.

Lindsey Mignano, Founder, Mignano Law Group

Image Credits:S72 Business Portraits

Lindsey Mignano brings the legal and structural expertise that often determines whether an early-stage M&A deal can actually get to the finish line. As founder of Mignano Law Group, she represents emerging technology companies, SMEs, venture-backed startups, and venture firms as outside general counsel. Her practice spans everything from SAFE notes, priced rounds, and bridge financings to buy-side and sell-side acquisitions, acqui-hires, and everything else you can bring to mind.

That uniquely equips her to educate founders without insight into how early M&A readiness can begin. Many of her clients are seed through Series B companies, including enterprise SaaS, PaaS, and AI startups — exactly the kinds of companies now facing strategic interest, and she’ll be able to ground the conversation in the realities of cap tables, contracts, asset sales, and the necessary work for acquisitions to happen.

Karl Alomar, Managing Partner, M13

Image Credits:Tanya Gillogley

Now it’s time for an investor and operator to join the conversation. As managing partner at M13, Karl Alomar backs seed and Series A software founders across infrastructure, fintech, developer productivity, and other categories, feeling the brunt of the AI revolution. He has intimate knowledge of the earliest strategic decisions founders make: when to raise, when to partner, when to accelerate growth, and when an acquisition path may create the best outcome for the company, team, and investors.

As COO of DigitalOcean, Alomar helped build the cloud infrastructure company from its first product to roughly $250 million in ARR and an eventual NYSE IPO, with its valuation peaking around $15 billion. But as a founder, he’s been a part of the acquisition cycle too. China Export Finance grew to approximately $140 million in revenue before being acquired in 2010, and Clearview Networks was acquired in 2000. That combination gives Karl a nuanced perspective on the core question facing founders in the audience: When should they keep building with their team, and when is M&A the right path forward?

Get your second pass at 50% off by May 8

And remember: If you register for Disrupt 2026 by May 8 at 11:59 p.m. PT, you can take advantage of that offer to get your pass with savings of up to $410, and get 50% off a second pass of the same ticket type. All the insights Disrupt offers are best shared with a partner or colleague, so don’t miss this opportunity!