• Anthropic platform engineering head Katelyn Lesse said that Claude now writes all her team's code.
• Lesse shared ways that Claude Code has helped the company become more efficient.
• Anthropic nears an initial public offering at a potential $2 trillion valuation.

A top Anthropic engineer says that Claude Code has already wiped out all human coding at one of the AI lab's central teams.

Katelyn Lesse leads the AI startup's platform engineering group, which handles the company's core services, developer tools, and product infrastructure — it's essentially the engine room of Anthropic. Lesse said at Grafana Labs' ObservabilityCON event on Tuesday that among her staff, which tallied 200 as of this summer, the era of human-written code is fully over.

"When it comes to our team and how we're actually building and maintaining our systems, all of our code is written by Claude," Lesse said. "Like, literally all of it."

Anthropic's heavy reliance on Claude Code has helped it remain relatively small, as it approaches an initial public offering that could value it at nearly $2 trillion. The company's revenue growth slowed in the third quarter of this year. Maintaining its lofty valuation may depend on selling more companies on the AI-first approach espoused by Lesse and other Anthropic leaders.

Lesse said that people on her teams are still designing systems and verifications, and then offloading the actual coding to Claude. She said that when the company changed the programming language of a major codebase from Python to Rust, workers developed a way to verify the final product.

"But the grunt work of building the pieces and actually monitoring the pieces and actually making sure that we felt good about it, that was agents all the way down," Lesse said.

Lesse said Anthropic already lets agents fix tests autonomously, with no human interaction, and it's thinking about how staff can get comfortable with agents autonomously making changes to the actual codebase, given the improvements in AI models over the last year.

"As engineering leaders, we're like terrified, and we're like, let's be really careful about this, but I think the line is starting to push," Lesse said.

Anthropic has also embraced Claude Code companywide. It released a report last week saying that as AI agents have worked more inside the company, it has hired for a smaller share of junior technical positions. And in May, Anthropic said that Claude then wrote more than 80% of the entire company's production code.

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• One of Meta's AI researchers left the company this month to start a legal tech company.
• Ethem Coban worked on teaching Meta's language models to reason through legal questions.
• Since then, he's had talks to raise $6 million in funding for a startup, according to a person familiar.

The legal industry's artificial intelligence gold rush is luring talent from Silicon Valley's biggest labs.

Ethem Coban, a researcher at Meta, left the company earlier this month to launch a legal tech startup, according to a person familiar with the matter. Coban, who worked on teaching Meta's language models to reason through legal questions, has been in talks to raise $6 million at a $25 million valuation.

Talks are still early, and the terms of the deal could change.

The startup is the latest entrant in an increasingly crowded legal tech market. Long seen as laggards, lawyers have spent the past two years experimenting with tools built on large language models. Early movers like Harvey and Legora saw a crush of demand, setting off a wave of investment in startups promising to transform how lawyers work.

Now, that opportunity is attracting researchers from the companies building the underlying models.

Coban spent almost two years at Meta, most recently at its Superintelligence Labs, where he helped train models to give better answers to legal questions and reduce hallucinations, the person said. He previously studied law at American University and Goethe University in Frankfurt.

A spokesperson for Meta didn't respond to a request for comment.

Coban has told investors that his new company aims to help law firms and corporate legal teams build and customize models around their expertise. The bet is that companies will increasingly want to own their AI rather than license it from outside companies, because it gives them more control over their data.

Law firms also see a chance to turn mountains of case files into a competitive advantage that other firms can't simply buy off the shelf. Kirkland & Ellis, the industry's revenue leader, has committed $500 million to building proprietary software. Latham & Watkins has been buying its own Nvidia servers to customize models in-house.

For Coban, the challenge won't be convincing law firms that they need artificial intelligence. It will be persuading them that someone who knows how the models work from the inside is best suited to build them.

• Newcomers like Kevin O'Leary face skepticism due to a lack of experience in data center development.
• Bernstein analysts dubbed O'Leary and others "bragawatts."
• Most announced projects will never happen. "Press releases are cheap…concrete is not."

The AI industry has a problem with bragging.

Companies are announcing enormous new data centers to power the AI boom. Some promise facilities bigger than anything the industry has built before.

There's just one problem: Most of these projects may never happen.

Bernstein Research analyzed thousands of planned US data centers and concluded that only about 35% of the announced capacity is likely to get built. That's roughly 170 gigawatts of data center capacity out of a total of almost 500 gigawatts.

The rest? A significant chunk of it belongs to a category the industry has a wonderfully dismissive name for: "Bragawatts." These are ambitious announcements, often from newcomers with little experience building data centers, that have a slim chance of becoming reality.

"Press releases are cheap…concrete is not," Bernstein analysts wrote in a research note.

Bernstein began its analysis with more than 7,000 data center projects across North America, drawing on information from Aterio, a company that tracks construction through satellite imagery, permits, and other records. The analysts narrowed that to more than 5,000 projects (partly by excluding those already canceled).

Then they assessed the chances of these remaining projects being completed. The analysts considered factors such as whether construction had started, whether electricity was available, and whether the companies involved had successfully built data centers before.

The results revealed a striking divide.

The 'bragawatt brigade'

Experienced operators including Amazon, Google, Microsoft, and Meta landed at the top. Bernstein gave these companies perfect scores of 5 out of 5 for their development credentials. Other data center specialists, such as Digital Realty, Equinix, and CoreSite, got top marks, too.

O'Leary Digital, associated with celebrity investor Kevin O'Leary, ended up at the bottom, with a credibility score of 0.35 out of 5, according to Bernstein. His company has announced 15 gigawatts of data center projects, and Bernstein estimates that only 489 megawatts, or about 3%, will actually materialize.

"Sorry, Kevin," the analysts wrote.

Although the term "bragawatts" has been doing the rounds in the data center industry lately, it's unclear who coined it, Bernstein analyst Madison Rezaei told me.

"I wish I could take credit for that," she said. "I believe I originally heard it from an Equinix executive, but I don't think he owned it either."

She said that while some ambitious newcomers could succeed, they haven't yet demonstrated they can deliver.

"It's not that all of these guys are sort of terrible and not going to deliver, but we just have lower confidence because we don't know them," Rezaei said.

O'Leary Digital responds

O'Leary Digital disputed Bernstein's assessment, saying the research doesn't account for substantial work that occurs before construction begins.

While acknowledging that O'Leary Digital is a young company, CEO Paul Palandjian said the team has decades of experience building major infrastructure projects and that its proposed 15 gigawatts of capacity would be built in stages over several years.

The company said it has secured binding agreements covering about 11,000 acres in Utah and 13,000 acres in Alberta, obtained a 30-year development agreement in Utah, and made progress on planning, engineering, and permits at both sites. It also said the projects would generate their own electricity.

The company said its early development work is funded, additional capital is committed to reaching key milestones, and experienced engineering and construction partners are involved.

"We would rather be judged on milestones than on a model," Palandjian said.

'An announcement in search of a project'

Other low scorers in the "bragawatt" brigade included Vermaland and Joule Capital Partners, according to Bernstein analysis based on Aterio data.

Joule has announced 50 data center projects with a combined capacity of 11.7 gigawatts. Bernstein estimates that only about 11% of that capacity will actually get built. Almost all of Joule's planned capacity remains at the announcement stage, with little evidence of construction progress or of major customers committing to use the facilities, Bernstein wrote in a July note to investors.

The analysts gave Joule a credibility score of 2.05 out of 5, placing it among the lowest-ranked developers in its database.

"An announcement in search of a project," the analysts wrote.

Vermaland has announced plans for a massive data center project in Arizona. Bernstein estimates that only 4% of its proposed 2.2 gigawatts of capacity will get built. The company is primarily a landowner, not a data center developer. Its proposed $33 billion La Osa project near Eloy had already been sharply scaled back amid local opposition and without construction approval. In late August, regulators formally rejected the project. Even before that, the analysts gave Vermaland a credibility score of 0.75 out of 5.

Joule and Vermaland didn't respond to emails seeking comment this week.

A yawning gap for data centers

Sergio Toro, CEO of Aterio, sees similar patterns in his firm's voluminous, detailed data.

Aterio's tracking shows that roughly 30 to 40 gigawatts of new data center capacity get announced each month. Yet only about 7 gigawatts begin construction each month, while 2 to 3 gigawatts actually start operating.

This leaves a yawning gap.

Many announced projects get withdrawn before construction begins — and before real money has been spent.

"They just make the announcement, but they didn't get their approvals. Or they make multiple filings in multiple locations to see which one gets selected," Toro told me. "That's why we track with satellite if there's real movement on the ground or not."

Indeed, Bernstein analysts wrote recently that the amount of "stranded" data center capacity has surged. These are projects that are either canceled, delayed, or not approved.

The AI boom's three tiers

Toro sees three broad groups competing to build AI infrastructure.

At the top are the established technology giants, including Amazon, Microsoft, and Google. They've built data centers for decades and generally deliver on their commitments. Most of their projects will get done, he said.

In the middle are "neoclouds," newer companies such as CoreWeave that rent out computing power specifically for AI. Although they're more vulnerable to financing problems and delays, many are making solid progress, especially because some of these players already have access to electricity.

"We see them advancing quite well," Toro said. "Sometimes we see some delays, but it's not something significant or any kind of big capacity that is at risk."

Then come the newcomers making extraordinary promises. That's where most delays and cancellations happen, Toro said.

Even Amazon needs a backup plan

Not every project that disappears was a fantasy, though. Even a top player like Amazon struggles sometimes to secure electricity and other supplies on time for these huge projects.

Business Insider's Eugene Kim reported exclusively this week on the challenges Amazon faces with its record AI buildout.

The biggest, most experienced tech companies deliberately pursue more potential data center capacity than they need because they know some developments will fail or get delayed.

Major AI companies were committing to three or four times the space and electricity they needed over the following two years, Jeffrey Moerdler, a data center lawyer, estimated during an interview with Bernstein analysts.

His reasoning: Of data center projects that haven't started construction, roughly a third will arrive on schedule, another third will be delayed, and the remainder won't happen.

Rezaei and Toro estimate that the top players don't over-commit that much — more like double the capacity they need at most.

The strategy provides a "Plan B," as Toro put it, in case of delays involving electricity, equipment, permits, local opposition, or other factors.

Texas has a ghost problem

This helps explain another extraordinary number.

Data center companies have requested connections for roughly 450 gigawatts of electricity demand on Texas' main power grid, more than five times the grid's roughly 85 gigawatts of existing capacity, according to Toro and others. 

Many of those requests are placeholders rather than firm construction plans. Toro calls them "ghost projects."

These speculative projects clog the waiting lists for electricity connections, making the electricity shortage look a lot worse than it actually is.

"Developers routinely spam projects across several sites, and many are speculative builds with no customer yet," Ryan McEntush, a partner at venture capital firm Andreessen Horowitz, wrote in a recent blog. "Often these new developers have never even plugged in a GPU, let alone a power plant."

Texas has paused applications to review and weed out projects that aren't serious. Toro, from Aterio, expects this to favor the established players at the expense of the bragawatts.

The real AI boom

None of this means the AI infrastructure boom is imaginary.

Aterio tracks thousands of buildings, including major projects already under construction. Bernstein estimates that nearly 80% of the capacity the largest technology companies are directly developing is credible.

And when speculative projects disappear, Rezaei doesn't expect a wave of unpaid debt. Many will fail before building begins, the stage when developers borrow serious money through project financing.

Some of those missing data centers were never really coming in the first place.

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• Meta CEO Mark Zuckerberg considered moving out of California because of a proposed billionaire tax.
• Zuckerberg would get $20 billion in "immediate liquidity" if the billionaire tax passes.
• Meta made the offer to Zuckerberg to help keep him in California after he considered leaving.

Meta CEO Mark Zuckerberg considered moving out of California because of its proposed billionaire tax, Meta disclosed in a new SEC filing on Wednesday.

Next month, Californians will vote on Proposition 40, a one-time tax on the assets of the state's billionaires.

The filing said that Zuckerberg told a special committee formed by Meta that he was considering moving.

In response, the committee concluded that it was "critically important" for Zuckerberg to keep running Meta close to its Silicon Valley headquarters — particularly to its AI division, Meta Superintelligence Labs.

The filing said the committee got Zuckerberg to agree to remain in California or any other jurisdiction where Meta has its corporate headquarters for eight years, barring unforeseen circumstances.

As part of its efforts to ensure he can remain in charge as it raises more cash for its AI initiatives, the company is granting the Meta CEO a new stock class.

The shares would give Zuckerberg $20 billion in "immediate liquidity" to cover the tax by selling stock without losing control of Meta, if the tax passes. The new shares wouldn't add to Zuckerberg's net worth or increase his percentage ownership of Meta.

"The goal is to keep Mr. Zuckerberg continuing to lead the Company from California," the filing says.

Meta declined to comment. A person familiar with the matter said that the new class of shares, which totals $150 billion, is also intended to raise capital, compensate employees, and keep Meta's stock price on the right track.

Meta's filing showcases how tech billionaires are responding to the tax proposal. Some, including Google cofounder Sergey Brin and former CEO Eric Schmidt, poured hundreds of millions of dollars into attack ads against the proposal.

While Zuckerberg has taken a lower-key approach, it's clear he's been taking the proposed tax seriously.

The Meta CEO, who is worth about $240 billion according to Forbes, has multiple residences in California, including in Palo Alto and Lake Tahoe.

He also has a sprawling property portfolio outside the state, including a doomsday bunker in Hawaii, a waterfront mansion in Miami, and a castle in Ireland.

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• Meta's AI agent, Muse, is unprofitable due to "very high compute costs," CEO Mark Zuckerberg says.
• Meanwhile, Meta expects Reality Labs, its AI glasses division, to lose $15 billion next year.
• The social media giant has a plan to fix that.

Meta says some of its biggest cash incinerators could finally start turning profits.

The social media giant, which generated over 97% of its quarterly revenue from ads, has faced persistent questions from investors about the lack of profitability in its AI and hardware initiatives.

Meta CEO Mark Zuckerberg addressed those concerns head-on during its third-quarter earnings call on Wednesday.

Zuckerberg said that Muse, the AI assistant it launched last month, is unprofitable since it's "very compute intensive to run." Meta expects to start turning that around next year by massively improving Muse's efficiency.

"If compute efficiency continues improving quickly for another few years, which we think is highly likely, then Muse will be highly profitable over multiple years," he said.

Meta plans to make money from Muse by taking a small transaction fee off of purchases it drives, Zuckerberg said at Meta's Connect conference last month.

Zuckerberg added that Muse, which launched only in the US and Canada, wasn't launched globally due in part to the amount of compute it requires. (Meta's North American users are generally its most lucrative.)

Zuckerberg also struck a positive note about its cash-hemorrhaging Reality Labs division, which makes products like Meta Ray-Bans and virtual reality glasses.

Meta expects Reality Labs to narrow its losses to about $15 billion in 2027, down from the $18 to $19 billion it expects to lose this year. The division should start trending toward profitability next year, as Meta's AI systems make it more useful, Zuckerberg said.

"I continue to believe that the path to delivering holographic experience, of bringing together the physical and digital worlds and everyday glasses, will come through VR first," Zuckerberg said.

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• Anthropic has its answer to AI agents like Meta's Muse and OpenAI's Dots.
• Claude Duet, built on Anthropic's flagship model, has entered the personal agent frenzy.
• Karan Ahuja, a recent departee from Meta, led Claude Duet's development.

Anthropic is joining the personal AI agent craze.

The company announced the new app Claude Duet on Wednesday, billed as a "proactive agent" that can run in the background, surface tasks to a user, and handle a variety of work. The tool is in research preview for now with a waitlist, meaning it won't immediately compete for the larger market with other new agents like Meta's Muse and OpenAI's Dots.

Still, the announcement ramps up the pressure on those companies — Anthropic says it built Duet around its flagship Opus 5.5 model, which was released in late September and has already become one of the industry's most popular. Recent model breakthroughs have made AI better at handling work on its own, spurring a rush to build these "always-on" personal agents.

"It can have the discernment and judgment around when to be proactive, when to act on your behalf," said Mike Krieger, a co-lead of Anthropic's Labs team, said in a Duet launch video.

The tool, Anthropic says, will send users a brief each morning about what's happening on their connected apps, and message them when something needs attention. Like other companies' offerings, it runs outside a user's computer, sends notifications, and asks for approval on certain tasks.

Anthropic announced Duet on the day of Meta's earnings report and used the opportunity to mention a new poach from Mark Zuckerberg's company. Karan Ahuja led product management for Meta Superintelligence Labs until July, according to his LinkedIn, before starting at Anthropic in August and leading Duet's development.

He wrote on X that he's been using Duet to build Duet, and said the team "built it for professionals and small business owners juggling a lot at work and at home."

Ahuja also wrote that Anthropic is letting people into Duet from the waitlist "as quickly as possible."

The news didn't go unnoticed at Meta. Alexandr Wang, who heads Meta Superintelligence Labs, posted a meme about Duet's similarity to Muse.

Anthropic is fast approaching a giant initial public offering, which could value the company at as much as $2 trillion. Like other AI players, the company navigates a high-wire competition to win over users, secure computing power, build state-of-the-art models, and deliver AI-native products.

The data firm Apptopia estimates that Muse had more than 14 million installations as of Wednesday. It found that Claude users who installed the Muse app were using Claude more than before, though still for fewer minutes per day than they spent on the Meta product.

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• Nvidia vice president Laura Fay has retired after a decade at the company.
• Fay grew Nvidia's enterprise marketing team from roughly 60 to 600 employees.
• Nvidia brought in Google Cloud's Alison Wagonfeld as its first chief marketing officer this year.

Laura Fay, a longtime Nvidia marketing executive who reported to CEO Jensen Huang, retired in July after roughly a decade at the AI chip giant.

Fay formerly served as Nvidia's vice president of global enterprise marketing, overseeing campaigns, events, analyst relations, and partner marketing. She said her team grew from roughly 60 to 600 people by the time she left.

Fay was among 36 employees on an internal list obtained by Business Insider last year of company leaders reporting directly to Huang. Prior to joining Nvidia, she spent 22 years at Cisco, concluding her tenure there as VP of global marketing.

Fay said Huang recruited her to build Nvidia's enterprise marketing organization as the company looked to expand beyond gaming.

"I want to change the world, and I want you to change it with me," she recalled him telling her on their first call.

Fay said she began considering retirement around her 10th anniversary in January, though a call from Huang congratulating her and expressing hope that she'd stick around for another decade persuaded her to stay a little longer.

Nvidia declined to comment.

Fay's retirement came as Nvidia also brought in new marketing leadership. In February, the company hired Google Cloud executive Alison Wagonfeld as its first chief marketing officer.

The Wall Street Journal reported at the time that Wagonfeld would oversee all marketing and communications teams and assume responsibilities previously divided among several leaders.

Those changes follow another longtime marketing departure. Greg Estes, Nvidia's former vice president of corporate marketing and developer programs, retired in 2025 after roughly 15 years at the company.

Several other longtime Nvidians have retired this year, including sales chief Jay Puri, chief accounting officer Donald Robertson, and VP of hardware engineering Robert Huang. Some retirees told Business Insider that Nvidia's exponential stock run helped precipitate their decisions.

Nvidia's communications organization has also undergone a shake-up as scrutiny around the company has intensified, with roughly 15 employees departing since 2025 amid a reorganization under new leadership.

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• Joel Kaplan, Meta's chief global affairs officer, is leaving, Meta confirmed to Business Insider.
• Kaplan, a Republican who once worked for the Bush administration, spent 15 years at Meta.
• Kaplan helped bridge ties between Meta CEO Mark Zuckerberg and President Donald Trump.

A longtime political operative at Meta who played a key role in bridging ties between the company and President Donald Trump's administration is leaving.

Joel Kaplan, Meta's chief global affairs officer, will leave after the midterm elections and a transition period, Axios first reported. Meta confirmed the report to Business Insider.

A veteran Marine Corps artillery officer, Kaplan is a Republican who served as an advisor and deputy chief of staff to former president George W. Bush.

Kaplan joined Meta in 2011. At Meta, he oversaw the company's response to policy issues ranging from the Cambridge Analytica scandal to the end of its fact-checking program.

Kaplan helped repair a once-fraught relationship between Meta CEO Mark Zuckerberg and Trump after Meta temporarily suspended Trump's account following the January 6 riot.

Kaplan posted on X on Tuesday that he plans to spend time with his family and figure out what to do next.

Kaplan didn't respond to a request for comment from Business Insider.

Kaplan has served as Meta's chief global affairs officer since 2025, succeeding former UK politician Nick Clegg. Other Meta executives will share his responsibilities, Axios reported.

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• Abdulrahman Alfozan will stay jailed pre-trial, a San Francisco judge decided Monday.
• The engineer is accused of bugging a conference room at OpenAI, and he has been fired.
• Alfozan posed a risk of non-appearance, the judge said, after discussing his ties to Saudi Arabia.

A former OpenAI engineer accused of bugging the AI startup's office was denied release by a San Francisco judge on Monday, meaning he'll have to mount his defense from jail.

The Justice Department arrested Abdulrahman Alfozan on October 9 and charged him with using or attempting to use a device to intercept oral communications. He's accused of placing a recording device behind a television in an OpenAI conference room — an FBI affidavit includes photos of the device wrapped in toilet paper, and a man they say is Alfozan peering behind the TV.

On Monday, the engineer wore a yellow surgical mask and a jail-issued orange sweatshirt to the San Francisco courthouse. Magistrate Judge Alex G. Tse prodded Alfozan's legal team about the risk that he might not appear for a future court hearing.

Tse said that Alfozan's wife and son had traveled to Saudi Arabia with no plans to return, and went back and forth with Yasin about a one-way ticket that Alfozan had previously booked to the country. Tse said that Saudi Arabia and the US do not have an extradition agreement, and expressed skepticism that he had sufficient ties to the Bay Area to prevent his departure.

William Pernik, Alfozan's attorney, argued that, rather than being detained, Alfozan should be fitted with an ankle monitor, ordered to stay home, and have limits placed on his use of technology. The lawyer also said Alfozan is willing to put up "essentially all the money his family has" as bond, including a roughly $1 million investment account.

"Everything this man has, he's willing to surrender, and say, 'I'm not going anywhere,'" Pernik said.

Pernik and Nas Yasin, another of Alfozan's attorneys, cited his coming naturalization interview as evidence of his local ties.

"He was weeks away from achieving every immigrant's dream in this country," Pernik said.

Yasin told Tse that she learned Alfozan's wife had obtained a short-term visitor visa to return to the US, to help improve her husband's case for ties to the Bay Area.

Tse also asked Alfozan's legal team a slew of questions about his relationship with Saudi Arabia, including a commitment by the Saudi consulate to pay his bond and support his legal effort.

Nick Parker, an assistant US attorney, appeared for the prosecution. He argued that the threat of forfeiting a $1 million bond wouldn't be enough to convince Alfozan to return if he made it out of the US, because he might be able to earn more money in Saudi Arabia.

"There is a real threat here that once he leaves, the case is over," Tse responded.

The judge scheduled the case's next hearing for early November.

OpenAI called the recording device "sophisticated" when the arrest went public, though it said it hadn't found signs that he'd taken AI model weights, source code, or customer information. OpenAI fired Alfozan.

Alfozan's charge carries a maximum penalty of 5 years. Pernik said in a statement last week that the allegations "appear wholly out of character for him."

Alfozan, 35, has a green card that makes him a lawful permanent resident of the United States. He attended MIT, then worked at Facebook (now Meta) from 2017 to 2023. After a stint at the engineering startup Nash Technologies, Alfozan joined OpenAI in 2025.

FBI agents have already taken Alfozan's Saudi passport.

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Cooley has made billions doing what law firms do: hire great lawyers, bill for their time, and keep clients happy. Artificial intelligence is scrambling that formula. If machines can do in minutes what once took an associate hours, what exactly should clients be paying for?

Rachel Proffitt thinks she has the answer.

On a toasty October afternoon in San Francisco, I met Proffitt for lunch to talk about the future of the global law firm she now leads. When the check arrived, neither of us knew how much the restaurant paid the dishwasher or how many minutes the chef spent preparing our meal. We were paying for the experience, not the labor behind it.

Why, she wondered, should legal services be so different?

"Clients have never been excited about the fact that it took us 82 hours to do something. They don't care," she says. "They just want the outcome. They want the results."

The billable hour is only the beginning. AI is forcing law firms to rethink how many associates they really need and how those young lawyers learn their craft. Client relationships are changing as companies use software to get a head start on the work they send to outside counsel. Some of that work may never reach a lawyer at all.

If tech is about to reinvent law firms, Cooley should be one of the firms with the clearest view of what's coming. From its early days on San Francisco's Market Street, it worked with semiconductor manufacturers and venture capitalists when the valley was still covered in fruit trees and canneries. Cooley grew up alongside the tech industry, and today it is as comfortable defending Meta in court as it is helping Andreessen Horowitz round up billion-dollar funds.

That evolution has been lucrative. Cooley says its gross revenue jumped from $912 million in 2015 to $2.4 billion last fiscal year. Its crosstown rival, Wilson Sonsini, brought in $1.7 billion in 2025, according to The American Lawyer. Still, the gulf between Cooley and Big Law's largest firms remains enormous. Kirkland & Ellis, the industry's revenue leader, cracked $10 billion last year. Latham & Watkins, another go-to firm for Silicon Valley, hit $8.3 billion.

The next wave of tech public listings promises a fortune in legal fees for the chosen few. Gibson Dunn landed SpaceX's IPO. Anthropic tapped Wilson Sonsini for its coming listing. And Cooley is reportedly sharing OpenAI's IPO work with Wachtell Lipton, one of Wall Street's most formidable law firms.

The irony is hard to miss. Big Law is fighting for a piece of the biggest technology companies in the world, even as those companies build the tools that could upend the business of law itself.

Proffitt came up as a lawyer under the old rules. Her next task is to figure out what it will take to build a great law firm under the new ones.

'The winner's circle'

Profitt didn't grow up wanting to be a lawyer but liked how law school taught her to think. Litigation was out of the question: Public speaking during mock trials made her stomach turn. "It was transactional law or bust," she says.

She started her career as a summer associate at Wilson Sonsini and worked her way up to partner. She fell in love with the intensity of the work, pulling all-nighters at the financial printers where she marked up securities filings by hand. She recalls the Christmas Eve when her father marveled that she had made it through the day without taking a work call. After 15 years at the firm, she left for Cooley in 2017.

Three years ago, Proffitt got a call at home that she didn't see coming. Joe Conroy, then Cooley's chief executive, wanted to know whether she would consider succeeding him.

She was flattered, but also "a bit terrified," she says. She spent two decades helping startups, including Unity Software, Procore, and Instacart, raise money and go public. Running a firm with 3,000 employees was another matter. She talked to her family, then put herself forward for the job. She started in 2024.

Proffitt couldn't have guessed how quickly AI would jolt her industry from its steady state. It wasn't too long ago that clients insisted that the technology go nowhere near their work, fearing what would happen if their data disappeared into someone else's model.

"It was clear to me then that we don't get to just exist as we are and continue to be at the top of our game," she says.

Cooley had remade itself once before. The firm's Silicon Valley roots were both a strength and a liability, said Conroy in an interview. Cooley was known for helping startups get off the ground. The conventional wisdom was that as those companies grew, they would graduate to one of the elite New York law firms for their biggest deals and courtroom battles.

To keep clients from the garage to the boardroom, as Conroy put it, Cooley needed to expand. It opened new offices and built out its litigation and capital markets practices. The firm also spent years courting Wall Street banks, says Proffitt, so that when a company asked which law firm to hire for its IPO, Cooley would make its shortlist.

Today, its client roster reads like a Kiplinger roundup of hot tech stocks: Nvidia, Uber, Snowflake, and Zoom, to name a few listings it worked on. Since 2016, Cooley has advised issuers on 183 IPOs that raised nearly $59 billion, making it the second-most active firm by deal count after Latham, according to Deal Point Data. Proffitt wouldn't discuss reports that Cooley has landed OpenAI's IPO work.

For 16 years, Conroy pushed Cooley toward what he calls Big Law's "winner's circle." Proffitt's job is to get it there.

Startup speed

Her strategy starts with making Cooley move more like the tech companies it represents.

Proffitt recruited David Wang, a former lawyer turned legal technology executive, with an ambitious mandate. She didn't just want to make Cooley's lawyers more productive, Wang said in an interview. She wanted to change how clients interact with them altogether.

Earlier this year, Cooley launched a tool with the startup Legora that lets Y Combinator founders review common contracts without calling a lawyer. OpenAI helped it build a tool for Cooley's lawyers to prepare paperwork for companies going public. Next, Cooley is working with Google on an AI agent that scans documents for confidential information before they're filed in court, then suggests redactions for lawyers to review.

There's something almost cannibalistic about a law firm building software that could eat into its own billable hours. But Cooley sees a bigger risk in letting someone else do it. In-house legal teams are increasingly using chatbots to take the first crack at work they would otherwise send to outside counsel. A new breed of "AI-native" law firms is promising cheaper, faster services.

Big Law does not want to be caught flatfooted. Firms are throwing money at startups like Harvey and Legora, and increasingly, they're building their own technology. Kirkland has committed $500 million to proprietary software, starting with a platform for private equity fundraising built with Palantir. Latham bought its own Nvidia servers so it can customize models in-house. Like Cooley, Wilson Sonsini has self-service tools that let companies handle basic legal work.

For Proffitt, the danger isn't lost billable hours. It's the missed connections. The scrappy startup that needs a contract reviewed today might need help closing an acquisition later. But if the bots take care of the small stuff, Cooley could miss its chance to build the relationship.

Proffitt says Cooley must find new ways to connect with clients. Putting technology in their hands is one option, even if it means giving away a little of the work.

"When you need the next thing that matters, the thing that you don't trust to put into the machine," she says, "how do I ensure that you want to talk to our team?"

The firm is also rethinking its own structure for the new era. Wang now leads Cooley AI, a wholly owned subsidiary designed to operate at something closer to startup speed. The separate company gives his team more freedom to hire engineers and put new technology through its paces, he says, without getting bogged down in the parent firm's bureaucracy.

The irony, Proffitt says, is that all this technology could leave lawyers with more time for the human stuff. Lawyers may visit their clients more. Talk through thorny decisions. Drop in on the strategy session to learn how their advice fits into a client's business.

Keeping those relationships alive might require a little more old-fashioned schmoozing. When I asked Proffitt whether the answer was throwing great parties, she didn't entirely disagree. "Everyone loves a party," she says.

The future of legal work

Proffitt doesn't pretend to have a crystal ball. She has ideas, though.

The billable hour? Not dead yet. She expects law firms to offer clients a menu of pricing options, from hourly rates to flat fees and outcome-based pricing.

Hiring slowdowns at the junior level? "Too early to tell," she says.

The apprenticeship model? That gets trickier. If software can write first drafts and spot issues, how will young lawyers get the practice they need? Proffitt says Cooley is exploring ways for associates to sharpen their skills on simulated legal matters, starting with AI-powered mock depositions.

Proffitt came up in an era when canceled dinners and all-nighters were a badge of honor. She's betting that the next generation won't need quite so many of them to become great lawyers. Her test will come a decade from now, when today's junior associates are ready to make partner.

If Cooley has found a better way to teach them, perhaps the old model won't be missed. If it hasn't, no amount of AI can make up the difference.

Melia Robinson is a senior correspondent at Business Insider, where she writes about how artificial intelligence is changing the legal industry.

• Amazon is on an unprecedented spending spree to build more AI data center capacity than anyone else.
• The company has extensive experience, yet even it's struggling to bring capacity online fast enough.
• Internal documents show Amazon getting bilions of dollars of Nvidia GPUs before they can be deployed.

At an internal staff meeting in September, AWS CFO John Felton had a joke for Prasad Kalyanaraman, the executive overseeing much of Amazon's AI infrastructure expansion.

"You've taken us free cash flow negative as a company, so congratulations," Felton said, according to a recording of the meeting obtained by Business Insider.

The remark was lighthearted. But it captured a stunning reversal.

Just two years ago, Wall Street was debating what Amazon would do with its growing cash hoard. Now, cash flow has evaporated as Amazon embarks on its biggest bet ever, spending $220 billion this year alone to build the physical backbone for AI.

At the meeting, Kalyanaraman did not dispute Felton's premise. Amazon's machine-learning and AI business is "hugely free cash flow negative," he said, adding that he expects the company's free cash flow to remain negative for "the next couple of years or so."

Amazon has made big bets before. It spent heavily on cloud computing, fulfillment centers, and its delivery network long before they became some of the company's most valuable assets. Investors questioned those investments at the time, but Amazon ultimately built enormous, profitable businesses from them.

AI is testing this playbook at a far larger scale. Amazon is committing hundreds of billions of dollars to data centers, servers, and power before investors know how quickly those investments will generate revenue.

The company is the best, or among the best, at building data centers, with decades of experience. But the size and complexity of these projects, and the bottlenecks holding progress back, are challenging — even for such a respected cloud pioneer.

Internal documents reviewed by Business Insider and people familiar with the matter show the company trying to coordinate a sprawling industrial system whose parts move on different schedules. A delay in power, equipment, or construction can leave billions of dollars in hardware waiting — and Amazon's cash tied up — while forecasts and costs keep shifting.

Why Amazon thinks it will work

Amazon says it has strong evidence that the capacity will be needed. AWS revenue grew 37% in the second quarter, its fastest pace in 18 quarters, while its backlog reached $496 billion.

CEO Andy Jassy thinks the company has a "clear line of sight" to strong financial returns from this record investment cycle. In his latest annual shareholder letter, he called AI a "once in a lifetime opportunity" and said Amazon would not be conservative in its investments.

"We've been through this cycle with the first big AWS growth wave, and liked the results," Jassy wrote. "We expect to feel similarly about this next wave."

Investors are concerned by the scale of the industry's expansion, especially as AI data centers are costing more to build and taking longer to complete.

The market is "repricing anything that funds multi-year builds against revenue that arrives later," Dan Ives, an analyst at Yorkville Ives, wrote in a recent report. Growing uncertainty around data center permitting and the political fight over electricity prices have given investors another reason to question how quickly these investments will pay off, he added.

Racks, but not enough power

One major industry challenge is securing enough power to run the equipment that goes inside data centers. This includes expensive racks of servers that contain GPUs and other chips that train and run AI models and services such as ChatGPT.

Internal emails from August show Amazon preparing a new "Early Rack Receipt" process for an expected wave of server racks carrying Nvidia's GB300 chips at US facilities before final deployment.

One Amazon email projected the company would take delivery of about $5 billion of Nvidia GB300 racks in August, followed by another roughly $3 billion each month "for the foreseeable future."

Some AWS data center sites had room for more racks but not enough available power to turn them on, people familiar with the effort said, leaving the equipment to be staged at intermediary warehouses until the facilities were ready. These people asked not to be identified discussing sensitive matters.

Timing and coordination

Usually, Amazon doesn't pay for racks until the gear is put into a data center, leaving suppliers to carry the cost of the equipment in transit, according to the internal documents obtained by Business Insider. This helps the company conserve cash.

However, the intensity of the AI data center building boom has made this type of coordination harder. Amazon has to compete more for scarce resources as it jockeys with rivals for access to Nvidia GPUs and other AI components.

Under the new "Early Rack Receipt" process, Amazon now takes ownership of these racks earlier in the supply chain, rather than waiting until the equipment reaches a data center.

The means spending cash sooner. And any delays getting the racks installed and plugged into a reliable power source potentially pushes back the moment when revenue starts flowing from these assets.

At least one AWS supply chain team did not have "a clear forecasted path" for getting racks into data centers, according to one of the emails reviewed by Business Insider.

An Amazon spokesperson said the company routinely stages finished hardware near deployment sites so it can be installed once power capacity is available, calling that approach "best business practice."

The spokesperson added that AWS has "long-established systems" to track infrastructure assets and disputed that the broader company lacks a forecasted path for getting racks into data centers.

This problem is not unique to Amazon.

Bernstein analysts wrote in a recent note that power permits, cooling systems, electrical equipment, construction, and hardware all move on separate schedules.

"Timing is imperfect," the analysts said.

"Inherently uncertain"

During the internal staff meeting in September, Felton, the AWS CFO, described the broader problem eloquently: "How do you work in the future when the future is inherently uncertain?"

Kalyanaraman, the AI infrastructure leader, said Amazon's internal outlook for the return on its AI investments had improved. But the assumptions behind those returns keep shifting.

"The forecast is changing on a daily basis," Kalyanaraman said. "The world that we live in is extremely dynamic."

Those shifting assumptions include when data centers will be ready and how much equipment AWS needs to keep on hand, he explained.

An eight-week supply buffer might be routine for a smaller company. But at Amazon's scale, Kalyanaraman said, this could mean holding "billions and billions of dollars" worth of additional equipment inventory — tying up precious cash.

Frugality meets the AI boom

Such tensions are especially striking for Kalyanaraman, a 21-year Amazon veteran who earlier this year was promoted to the elite S-team that reports directly to Jassy.

Amazon's founding story is defined by frugality. It famously used cheap doors as desks when founder Jeff Bezos started in Seattle in the mid-90s.

Kalyanaraman has absorbed this lore into bones. In late 2023, as AWS faced slower growth and layoffs, he urged employees to do more with less. "Frugality breeds innovation," he said back then.

That instinct still shapes his approach. In the September meeting this year, Kalyanaraman told Felton that AWS tries to make major investments at the "last responsible moment," when it has the clearest possible view of demand.

"If we can wait to spend the capital as late as possible, it's better for us," he said.

But the frenetic pace of the AI boom makes this principle difficult to follow. By the time demand is fully visible, the servers, power, and construction capabilities that AWS needs may no longer be available. That puts pressure on the company to commit more money sooner to secure supply and meet its data center capacity goals.

Kalyanaraman recalled telling Jassy in 2023 that AWS would "surely" be out of its capacity crunch by 2027. Instead, Amazon still expects demand to exceed its available capacity in 2027, the AI infrastructure chief said during the meeting this September.

Secured Power at Risk

Getting enough electricity may be the biggest challenge for an industry leader like Amazon.

The company has 44 gigawatts of data center capacity under development across 16 states, more than double Google, Meta, and Microsoft, according to Cleanview Research estimates.

An internal AWS dashboard called "Secured Power at Risk" tracks utility and regulatory constraints affecting electricity capacity AWS has lined up for its data centers.

The risks include transmission bottlenecks, requirements to reduce use during grid stress, and "use it or lose it" provisions that can jeopardize capacity if a data center project misses usage or construction milestones.

In other words, AWS is not simply waiting for electricity to arrive. It is managing a portfolio of commitments that can become more costly if a data center project is delayed.

Maryland proposals

A submission to Maryland's utility regulator last year, obtained through a public records request, illustrates the kind of exposure that can accompany massive data center buildouts.

Amazon told the Maryland Public Service Commission that large data center customers could help pay for grid upgrades or bring new power capacity to market without burdening other electricity ratepayers.

The company also proposed setting aside collateral to help utilities get more comfortable with the large investments needed to generate more electricity for data centers. Amazon proposed three years of collateral so that if a large electricity customer abandoned unused capacity, the utility would have time to re-sell the power.

The proposal is not evidence that AWS has made such a payment or posted collateral. It does, however, show that large data centers can face extra financial obligations, beyond their own electricity bills, if projects are delayed or cancelled.

The Amazon spokesperson said such utility rules are not unique to AWS. The company has not disclosed how much cash it has paid upfront to secure power.

New constraints 'keep popping up'

The AI buildout also incurs expenses that are harder to model than a conventional capex plan.

In the September meeting this year, Kalyanaraman said that while reviewing plans for gigawatts of capacity in West Texas, AWS confronted a labor problem: There weren't enough nearby pipefitters, electricians, and other skilled workers to build the facilities.

The company's response, he said, was to pay to construct housing complexes near its data centers so workers could live there for the two or three years needed to complete the projects.

Even the crates used to ship servers have become a planning issue. It may seem absurd to worry about the price of a container when servers cost hundreds of thousands of dollars, Kalyanaraman said. But at AWS's scale, where the company needs so many crates, even trivial items can become a material expense.

"We have new constraints that keep popping up," Kalyanaraman said.

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• Anthropic published new surveys comparing its staffers' sentiments to those of US workers.
• The AI startup's employees expect the tech to change work and the economy far more dramatically.
• Most Anthropic employees guessed that unemployment would top 12% in 2030.

Anthropic employees believe that AI will make their labor obsolete. Most US workers don't see their jobs that way at all.

The AI company published research on Friday that compares surveys with US adults against an internal poll of 1,334 Anthropic employees. Most of the Anthropic staffers said AI will handle at least 80% of their jobs by 2030, while only about 5% of the US workers felt the same.

The research, titled "The AI expectations gap," shows the chasm between how the employees at the AI startup feel and how other American adults feel. Anthropic workers are far more optimistic about the progress of AI capabilities, how much it's already saving time, and how fast the economy will grow.

The median Anthropic employee said that by the end of 2030, they expect AI to handle 95% of the work of building a new AI model.

Peter McCrory, Anthropic's chief economist, wrote on X that the views might help outsiders prepare for more capable AI systems.

"We're publishing this research because Anthropic runs roughly a year and a half ahead of the economy on AI adoption, so what happens at Anthropic could be a leading indicator for the broader world," he said.

Anthropic workers expect higher unemployment and extreme GDP growth

Anthropic's surveys examined how workers already use AI and how they think it will change.

"US adults and Anthropic staff largely agree about what AI can do today," the researchers wrote. "However, they disagree about how quickly it will improve, how widely it will be used, and how large the productivity gains measured by time saved will be."

There are a few possible explanations for the discrepancies. Anthropic employees have larger budgets for the tools and often get access to unreleased models. US workers, on average, are more likely to work with their hands or in a service industry.

The researchers found that workers in manual trades, production, and transport thought AI would handle the least of their work by 2030, compared with Anthropic staffers, tech workers, and respondents in business and finance.

Most Anthropic employees surveyed said that they expect the unemployment rate to top 12% in 2030. The majority of the US workers thought it would hover around or under 8%. It's currently 4.2%.

So far, researchers have found mixed evidence on AI disrupting the job market — a Yale team recently found it had mainly changed jobs, and had "no connection" to changes in unemployment.

The Anthropic researchers also compiled survey responses to estimate predictions on economic growth. Based on their answers, the median US adult's guess for GDP growth in 2030 was 5.4%, compared with 17.1% among Anthropic employees. The country's GDP grew by 2.2% last year.

Anthropic's staffers are following their leader

Anthropic's CEO, Dario Amodei, has become one of the industry's most closely watched voices on labor upheaval. In March of 2025, he said he expected AI to write 90% of code within 6 months, and "essentially all of the code" within the year. He made more headlines that May, telling Axios that AI could wipe out half of entry-level white-collar jobs within five years and lift unemployment to 10% or 20%.

Amodei expanded on that claim in a later essay, writing that he expects AI to be different from prior technological changes. He wrote that he expects an "unprecedented" short-term shock to labor, and that the economy will grow dramatically.

"AI isn't a substitute for specific human jobs but rather a general labor substitute for humans," he wrote.

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• Nvidia's communications operation has been reshaped as the company became the face of the AI boom.
• Roughly 15 staffers have left the lean team since 2025 as Nvidia reorganized its communications org.
• Former employees described growing workloads as responsibilities expanded.

Nvidia's communications organization has been reshaped as the company became the face of the AI boom, with multiple teams brought under new leadership and a string of departures.

Business Insider identified roughly 15 communications employees who have left Nvidia since 2025, based on LinkedIn profiles and interviews with former employees.

The organization now numbers roughly 70 to 80 people globally, and has more than doubled in size since Mylene Mangalindan joined as vice president of corporate communications in 2023, according to a person close to the company.

The departures have also included newer hires. Anna Soellner, who was recruited to lead corporate communications, left after roughly four months, Business Insider previously reported.

Nvidia is known for high retention. It reported companywide turnover of 3.7% in fiscal 2026, up from 2.5% the prior year, and well below the tech industry average of 21.9% cited in its latest sustainability report.

Mangalindan succeeded longtime communications chief Bob Sherbin, who retired in 2024. She previously worked at the advisory firm Brunswick Group.

She was brought in to "bring fresh blood" and "upgrade the team" to meet Nvidia's growing profile, one former employee said.

At the end of 2024, Nvidia restructured its communications organization. It brought enterprise public relations under Mangalindan's leadership alongside the corporate communications team she already led, according to two former employees.

Corporate communications focuses on Nvidia's reputation and major media outlets, while enterprise handles product and industry messaging, including for its data center business.

One former employee said the consolidation reflected the growing importance of Nvidia's data center business, which sells chips and systems that power AI and had become its biggest revenue driver.

Analyst relations, social media, and influencer marketing also moved under Mangalindan's remit this year, another former employee said.

Three former employees said Nvidia's communications team had long operated with relatively lean staffing, even as workloads grew alongside the company's public profile, leaving staff juggling multiple responsibilities.

These employees said they experienced long hours, difficulty taking time off, and pressure to respond quickly to emails and Slack messages.

A person close to Nvidia said the company's lean staffing allows employees to move quickly and also requires long hours. The person said Mangalindan encourages staff to take vacation, though the team's small size can make scheduling time off difficult, particularly in the summer.

Nvidia is widely known for its demanding work environment. CEO Jensen Huang has emphasized operating at the "speed of light" and is known for fostering a culture of constant accountability.

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• OpenAI's Alexander Embiricos said the AI era gives a choice: work more, or work less.
• He's in charge of Dots, the company's new always-on work assistant.
• AI is often pitched as freeing up time. Embiricos responded to the idea that it might add more work.

As the competitive AI race pushes tech workers into long hours, the head of OpenAI's new Dots product says AI gives people another option: work a whole lot less.

Alexander Embiricos, who leads OpenAI's enterprise product and helms the new Dots agent tool, told a crowd at TechCrunch's Disrupt conference on Thursday that AI's capabilities have created something of a fork in the road for workers. You can grind to meet the moment. Or you can use AI to kick your feet up a little.

"We basically have a lot more choice now," he said.

Embiricos made the comments after a reporter asked about when AI systems will actually deliver more free time. The reporter shared an anecdote where an OpenAI employee used a ChatGPT mobile feature to work in their car and on a plane — not exactly liberated by the new tech.

Embiricos said that the moment has already arrived where a worker can "outsource" tasks to AI and do less work. Then again, some people are so excited about AI's potential that they feel like it's an "interesting, ripe moment" to put in extra hours.

"I think that's why a lot of people are motivated to work very hard right now. That includes myself," he said. "But I think actually there is this choice, and there's totally this other setup where you could delegate a ton more things."

OpenAI is billing its Dots tool as a workplace assistant, always on and capable of proactively handing tasks and sorting to-dos. Embiricos uses his Dot often in Slack, he said, engaging on various threads.

His perspective illustrates how early companies are in their journey to adopt AI tools. Most companies have not yet automated their work tasks, and many workers are still debating how much to use the tools. Early AI adopters, meanwhile, can sprint through some work that used to take days or weeks, especially in software engineering.

Embiricos summed up the situation he feels workers are in: "You either choose: do you expand the ambition of what you can do, or do you do less? I do think we're there."

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