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Coding is supposed to be genAI’s killer use case. But what if its benefits are a mirage?

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Hello and welcome to Eye on AI…In this edition: Meta is going big on data centers…the EU publishes its code of practice for general purpose AI and OpenAI says it will abide by it…the U.K. AI Security Institute calls into question AI “scheming” research.

The big news at the end of last week was that OpenAI’s plans to acquire Windsurf, a startup that was making AI software for coding, for $3 billion fell apart. (My Fortune colleague Allie Garfinkle broke that bit of news.) Instead, Google announced that it was hiring Windsurf’s CEO Varun Mohan and cofounder Douglas Chen and a clutch of other Windsurf staffers, while also licensing Windsurf’s tech—a deal structured similarly to several other big tech-AI startup not-quite-acquihire acquihires, including Meta’s recent deal with Scale AI, Google’s deal with Character.ai last year, as well as Microsoft’s deal with Inflection and Amazon’s with Adept. Bloomberg reported that Google is paying about $2.4 billion for Windsurf’s talent and tech, while another AI startup, Cognition, swooped in to buy what was left of Windsurf for an undisclosed sum. Windsurf may have gotten less than OpenAI was offering, but OpenAI’s purchase reportedly fell apart after OpenAI and Microsoft couldn’t agree on whether Microsoft would have access to Windsurf’s tech.

The increasingly fraught relationship between OpenAI and Microsoft is worth a whole separate story. So too is the structure of these non-acquisition acquihires—which really do seem to blunt any legal challenges, either from regulators or the venture backers of the startups. But today, I want to talk about coding assistants. While a lot of people debate the return on investment from generative AI, the one thing seemingly everyone can agree on is that coding is the one clear killer use case for genAI. Right? I mean, that’s why Windsurf was such a hot property and why Anyshphere, the startup behind the popular AI coding assistant Cursor, was recently valued at close to $10 billion. And GitHub Copilot is of course the star of Microsoft’s suite of AI tools, with a majority of customers saying they get value out of the product. Well, a trio of papers published this past week complicate this picture.

Experiment calls gains from AI coding assistants into question

METR, a nonprofit that benchmarks AI models, conducted a randomized control trial involving 16 developers earlier this year to see if using code editor Cursor Pro integrated with Anthropic’s Claude Sonnet 3.5 and 3.7 models, actually improved their productivity. METR surveyed the developers before the trial to see if they thought it would make them more efficient and by how much. On average, they estimated that using AI would allow them to complete the assigned coding tasks 24% faster. Then the researchers randomized 246 software coding tasks, either allowing them to be completed with AI or not. Afterwards, the developers were surveyed again on what impact they thought the use of Cursor had actually had on the average time to complete the tasks. They estimated that it made them on average 20% faster. (So maybe not quite as efficient as they had forecast, but still pretty good.) But, and now here’s the rub, METR found that when assisted by AI it actually took the coders 19% longer to finish tasks.

What’s going on here? Well, one issue was that the developers, who were all highly experienced, found that Cursor could not reliably generate code as good as theirs. In fact, they accepted less than 44% of the code-generated responses. And when they did accept them, three-quarters of the developers felt the need to still read over every line of AI-generated code to check it for accuracy, and more than half of the coders made major changes to the Cursor-written code to clean it up. This all took time—on average 9% of the developers time was spent reviewing and cleaning up AI-generated outputs. Many of the tasks in the METR experiment involved large code bases, sometimes consisting of over 100,000 lines of code, and the developers found that sometimes Cursor made strange changes in other parts of this code base that they had to catch and fix.

Is it just vibes all the way down?

But why did the developers think the AI was making them faster when in fact it was slowing them down? And why, when the researchers followed up with the developers after the experiment ended, did they discover that 69% of the coders were continuing to use Cursor?

Some of it seems to be that despite the time it took to edit the Cursor-generated code, the AI assistance did actually ease the cognitive burden for many of the coders. It was mentally easier to fix the AI-generated code than to have to puzzle out the right solution from scratch. So is the perceived ROI from “vibe coding” itself just vibes? Perhaps. That would actually square with what The Wall Street Journal noted about a different area of genAI use—lawyers using genAI copilots. The newspaper reported that a number of law firms found that given how long it took to fact-check AI-generated legal research, they were not sure lawyers were actually saving any time using the tools. But when they surveyed lawyers, especially junior lawyers, they all reported high satisfaction using the AI copilots and that they felt it made their jobs more enjoyable.

But a couple of other studies from last week suggest that maybe it all depends on exactly how you use AI coding assistance. A team from Harvard Business School and Microsoft looked at two years of observations of software developers using GitHub Copilot (which is Microsoft product) and found that those using the tool spent more time on coding and less time on project management tasks, in part because GitHub Copilot allowed them to work independently instead of having to use large teams. It also allowed the coders to spend more time exploring possible solutions to coding problems and less time actually implementing the solutions. This too might explain why coders enjoy using these AI tools—because it allows them to spend more time on parts of the job they find intellectually interesting— even if it isn’t necessarily about overall time-savings.

Maybe the problem is coders just aren’t using enough AI?

Finally, let’s look at the third study, which is from researchers at Chinese AI startup Modelbest, Chinese universities BUPT and Tsinghua University, and the University of Sydney. They found that while individual AI software development tools often struggled to reliably complete complicated tasks, the results improved markedly when multiple large language models were prompted to each take on a specific role in the software development process and to pose clarifying questions to one another aimed at minimizing hallucinations. They called this architecture “ChatDev.”

So maybe there’s a case to be made that the problem with AI coding assistants is how we are using them, not anything wrong with the tech itself? Of course, building teams of AI agents to work in the way ChatDev suggests also uses up a lot more computing power, which gets expensive. So maybe we’re still facing that question: is the ROI here a mirage?

With that, here’s more AI news.

Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn

Before we get to the news, the U.S. paperback edition of my book, Mastering AI: A Survival Guide to Our Superpowered Future, is out from Simon & Schuster. Consider picking up a copy for your bookshelf.

Also, if you want to know more about how to use AI to transform your business? Interested in what AI will mean for the fate of companies, and countries? Then join me at the Ritz-Carlton, Millenia in Singapore on July 22 and 23 for Fortune Brainstorm AI Singapore. This year’s theme is The Age of Intelligence. We will be joined by leading executives from DBS Bank, Walmart, OpenAI, Arm, Qualcomm, Standard Chartered, Temasek, and our founding partner Accenture, plus many others, along with key government ministers from Singapore and the region, top academics, investors and analysts. We will dive deep into the latest on AI agents, examine the data center build out in Asia, examine how to create AI systems that produce business value, and talk about how to ensure AI is deployed responsibly and safely. You can apply to attend here and, as loyal Eye on AI readers, I’m able to offer complimentary tickets to the event. Just use the discount code BAI100JeremyK when you checkout.

Note: The essay above was written and edited by Fortune staff. The news items below were selected by the newsletter author, created using AI, and then edited and fact-checked.

AI IN THE NEWS

White House reverses course, gives Nvida greenlight to sell H20s to China. Nvidia CEO Jensen Huang said the Trump administration is set to reverse course and ease export restrictions on the company’s H20 AI chip, with deliveries to resume soon. Nvidia also introduced a new AI chip for the Chinese market that complies with current U.S. rules, as Huang visits Beijing in a diplomatic push to reassure customers and engage officials. While China is encouraging buyers to adopt local alternatives, companies like ByteDance and Alibaba continue to prefer Nvidia’s offerings due to their superior performance and software ecosystem. Nvidia’s stock and that of TSMC, which makes the chips for Nvidia, jumped sharply on the news. Read more from the Financial Times here.

Zuckerberg confirms Meta will spend hundreds of billions in data center push. In a Threads post, Meta CEO Mark Zuckerberg confirmed  that the company is spending “hundreds of billions of dollars” to build massive AI-focused data centers, including one called Prometheus set to launch in 2026. The data centers are part of a broader push toward developing artificial general intelligence or “superintelligence.” Read more from Bloomberg here.

OpenAI and Mistral say they will sign EU code of practice for general-purpose AI. The EU published its code of practice last week for general-purpose AI systems under the EU AI Act, about two months later than initially expected. Adhering to  the code, which is voluntary, gives companies assurance that they are in compliance with the Act. The code imposes a stringent set of public and government reporting requirements on frontier AI model developers, requiring them to provide a wealth of information about their models’ design and testing to the EU’s new AI Office. It also requires public transparency around the use of copyrighted materials in the training of AI systems. You can read more about the code of practice from Politico here. Many had expected the big technology vendors and AI companies to form a united front in opposing the code—Meta and Google had previously attacked drafts of it, claiming it imposed too great a burden on tech firms—but  OpenAI said in a blog post Friday that it would sign up to the standards. Mistral, the French AI model developer, also said it would sign—although it had previously asked the EU to delay enforcement of the AI Act, whose provisions on general-purpose AI are set to come into force on August 2nd. That may up the pressure on other AI companies to agree to comply too.

Report: AWS is testing a new cloud service to make it easier to use third-party AI models. That’s according to a story in The Information, which says Amazon cloud service AWS is making the move after losing business from several AI startups to Google Cloud. Some customers complained it was too difficult to tap models from OpenAI and Google, which are hosted on other clouds, from within AWS.

Amazon mulls further multi-billion dollar investment in Anthropic. That’s according to a story in the Financial Times. Amazon has already invested $8 billion in Anthropic and the two companies have formed an ever-closer alliance, with Anthropic working with Amazon on several massive new data centers and helping it develop its next generation Trainium2 AI chips.

EYE ON AI RESEARCH

Could all those studies about scheming AI be faulty? That’s the suggestion of a new paper  out from a group of researchers at the  U.K. government’s AI Security Institute. The paper, called “Lessons from a Chimp: AI ‘Scheming’ and the Quest for Ape Language” examines recent claims that advanced AI models engage in deceptive or manipulative behavior—what AI Safety  researchers call “scheming.” Drawing an analogy to 1970s research about whether non-human primates were capable of using language—which ultimately were found to have overstated the depth of linguistic capacity that chimpanzees possess—the authors argue that the AI scheming literature suffers from similar flaws.

Specifically, the researchers say the AI scheming research suffers from an over-interpretation of anecdotal behavior, a lack of theoretical clarity, an absence of rigorous controls, and a reliance on anthropomorphic language. They caution that current studies often confuse AI systems following human-provided instructions with intentional deception and may exaggerate the implications of observed behaviors. While acknowledging that scheming could pose future risks, the authors call for more scientifically robust methodologies before drawing strong conclusions. They offer concrete recommendations, including clearer hypotheses, better experimental controls, and more cautious interpretation of AI behavior.

FORTUNE ON AI

The world’s best AI models operate in English. Other languages—even major ones like Cantonese—risk falling further behind —by Cecilia Hult

How to know which AI tools are best for your business needs—with examples —by Preston Fore

Jensen Huang says AI isn’t likely to cause mass layoffs unless ‘the world runs out of ideas’ —by Marco Quiroz-Gutierrez

Commentary: I’m leading the largest global law firm as AI transforms the legal profession. Lawyers must double down on this one skill —by Kate Barton

AI CALENDAR

July 13-19: International Conference on Machine Learning (ICML), Vancouver

July 22-23: Fortune Brainstorm AI Singapore. Apply to attend here.

July 26-28: World Artificial Intelligence Conference (WAIC), Shanghai. 

Sept. 8-10: Fortune Brainstorm Tech, Park City, Utah. Apply to attend here.

Oct. 6-10: World AI Week, Amsterdam

Oct. 21-22: TedAI San Francisco. Apply to attend here.

Dec. 2-7: NeurIPS, San Diego

Dec. 8-9: Fortune Brainstorm AI San Francisco. Apply to attend here.

BRAIN FOOD

AI is not going to save the news media. I’ve been thinking a lot about AI’s impact on the news media lately both because it happens to be the industry I’m in and also because Fortune has recently started experimenting more with using AI to produce some of our basic news stories. (I use AI a bit to produce the short news blurbs for this newsletter too, although I don’t use it to write the main essay.) Well, Jason Koebler, a cofounder of tech publication 404 Media, has an interesting essay out this week on why he thinks many media organizations are being misguided in their efforts to use AI to produce news more efficiently.

He argues that the media’s so-called “pivot to AI” is a mirage—a desperate, misguided attempt by executives to appear forward-thinking while ignoring the structural damage AI is already inflicting on their businesses. He argues that many news execs are imposing AI on newsrooms with no clear business strategy beyond vague promises of innovation. He says this approach won’t work: relying on the same tech that’s gutting journalism to save it is both delusional and self-defeating.

Instead, he argues, the only viable path forward is to double down on what AI can’t replicate: trustworthy, personality-driven, human journalism that resonates with audiences. AI may offer productivity boosts at the margins—transcripts, translations, editing tools—but these don’t add up to a sustainable model. You can read his essay here



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‘Its own research shows they encourage addiction’: Highest court in Mass. hears case about Instagram, Facebook effect on kids

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Massachusetts’ highest court heard oral arguments Friday in the state’s lawsuit arguing that Meta designed features on Facebook and Instagram to make them addictive to young users.

The lawsuit, filed in 2024 by Attorney General Andrea Campbell, alleges that Meta did this to make a profit and that its actions affected hundreds of thousands of teenagers in Massachusetts who use the social media platforms.

“We are making claims based only on the tools that Meta has developed because its own research shows they encourage addiction to the platform in a variety of ways,” said State Solicitor David Kravitz, adding that the state’s claim has nothing to do the company’s algorithms or failure to moderate content.

Meta said Friday that it strongly disagrees with the allegations and is “confident the evidence will show our longstanding commitment to supporting young people.” Its attorney, Mark Mosier, argued in court that the lawsuit “would impose liabilities for performing traditional publishing functions” and that its actions are protected by the First Amendment.

“The Commonwealth would have a better chance of getting around the First Amendment if they alleged that the speech was false or fraudulent,” Mosier said. “But when they acknowledge that its truthful that brings it in the heart of the First Amendment.”

Several of the judges, though, seem to more concerned about Meta’s functions such as notifications than the content on its platforms.

“I didn’t understand the claims to be that Meta is relaying false information vis-a-vis the notifications but that it has created an algorithm of incessant notifications … designed so as to feed into the fear of missing out, fomo, that teenagers generally have,” Justice Dalila Wendland said. “That is the basis of the claim.”

Justice Scott Kafker challenged the notion that this was all about a choose to publish certain information by Meta.

“It’s not how to publish but how to attract you to the information,” he said. “It’s about how to attract the eyeballs. It’s indifferent the content, right. It doesn’t care if it’s Thomas Paine’s ‘Common Sense’ or nonsense. It’s totally focused on getting you to look at it.”

Meta is facing federal and state lawsuits claiming it knowingly designed features — such as constant notifications and the ability to scroll endlessly — that addict children.

In 2023, 33 states filed a joint lawsuit against the Menlo Park, California-based tech giant claiming that Meta routinely collects data on children under 13 without their parents’ consent, in violation of federal law. In addition, states including Massachusetts filed their own lawsuits in state courts over addictive features and other harms to children.

Newspaper reports, first by The Wall Street Journal in the fall of 2021, found that the company knew about the harms Instagram can cause teenagers — especially teen girls — when it comes to mental health and body image issues. One internal study cited 13.5% of teen girls saying Instagram makes thoughts of suicide worse and 17% of teen girls saying it makes eating disorders worse.

Critics say Meta hasn’t done enough to address concerns about teen safety and mental health on its platforms. A report from former employee and whistleblower Arturo Bejar and four nonprofit groups this year said Meta has chosen not to take “real steps” to address safety concerns, “opting instead for splashy headlines about new tools for parents and Instagram Teen Accounts for underage users.”

Meta said the report misrepresented its efforts on teen safety.

___

Associated Press reporter Barbara Ortutay in Oakland, California, contributed to this report.



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Quant who said passive era is ‘worse than Marxism’ doubles down

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Inigo Fraser Jenkins once warned that passive investing was worse for society than Marxism. Now he says even that provocative framing may prove too generous.

In his latest note, the AllianceBernstein strategist argues that the trillions of dollars pouring into index funds aren’t just tracking markets — they are distorting them. Big Tech’s dominance, he says, has been amplified by passive flows that reward size over substance. Investors are funding incumbents by default, steering more capital to the biggest names simply because they already dominate benchmarks.

He calls it a “dystopian symbiosis”: a feedback loop between index funds and platform giants like Apple Inc., Microsoft Corp. and Nvidia Corp. that concentrates power, stifles competition, and gives the illusion of safety. Unlike earlier market cycles driven by fundamentals or active conviction, today’s flows are automatic, often indifferent to risk.

Fraser Jenkins is hardly alone in sounding the alarm. But his latest critique has reignited a debate that’s grown harder to ignore. Just 10 companies now account for more than a third of the S&P 500’s value, with tech names driving an outsize share of 2025’s gains.

“Platform companies and a lack of active capital allocation both imply a less effective form of capitalism with diminished competition,” he wrote in a Friday note. “A concentrated market and high proportion of flows into cap weighted ‘passive’ indices leads to greater risks should recent trends reverse.” 

While the emergence of behemoth companies might be reflective of more effective uses of technology, it could also be the result of failures of anti-trust policies, among other things, he argues. Artificial intelligence might intensify these issues and could lead to even greater concentrations of power among firms. 

His note, titled “The Dystopian Symbiosis: Passive Investing and Platform Capitalism,” is formatted as a fictional dialog between three people who debate the topic. One of the characters goes as far as to argue that the present situation requires an active policy intervention — drawing comparisons to the breakup of Standard Oil at the start of the 20th century — to restore competition.

data-srcyload

In a provocative note titled “The Silent Road to Serfdom: Why Passive Investing is Worse Than Marxism” and written nearly a decade ago, Fraser Jenkins argued that the rise of index-tracking investing would lead to greater stock correlations, which would impede “the efficient allocation of capital.” His employer, AllianceBernstein, has continued to launch ETFs since the famous research was published, though its launches have been actively managed. 

Other active managers have presented similar viewpoints — managers at Apollo Global Management last year said the hidden costs of the passive-investing juggernaut included higher volatility and lower liquidity. 

There have been strong rebuttals to the critique: a Goldman Sachs Group Inc. study showed the role of fundamentals remains an all-powerful driver for stock valuations; Citigroup Inc. found that active managers themselves exert a far bigger influence than their passive rivals on a stock’s performance relative to its industry.

“ETFs don’t ruin capitalism, they exemplify it,” said Eric Balchunas, Bloomberg Intelligence’s senior ETF analyst. “The competition and innovation are through the roof. That is capitalism in its finest form and the winner in that is the investor.”

Since Fraser Jenkins’s “Marxism” note, the passive juggernaut has only grown. Index-tracking ETFs, which have grown in popularity thanks to their ease of trading and relatively cheaper management fees, are often cited as one of the primary culprits in this debate. The segment has raked in $842 billion so far this year, compared with the $438 billion hauled in by actively managed funds, even as there are more active products than there are passive ones, data compiled by Bloomberg show. Of the more than $13 trillion that’s in ETFs overall, $11.8 trillion is parked in passive vehicles. The majority of ETF ownership is concentrated in low-cost index funds that have significantly reduced the cost for investors to access financial markets. 

In Fraser Jenkins’s new note, one of his fictitious characters ask another what the “dystopian symbiosis” implies for investors. 

“The passive index is riskier than it has been in the past,” the character answers. “The scale of the flows that have been disproportionately into passive cap-weighted funds with a high exposure to the mega cap companies implies the risk of a significant negative wealth effect if there is an upset to expectations for those large companies.”



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Why the timing was right for Salesforce’s $8 billion acquisition of Informatica — and for the opportunities ahead

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The must-haves for building a market-leading business include vision, talent, culture, product innovation and customer focus. But what’s the secret to success with a merger or acquisition? 

I was asked about this in the wake of Salesforce’s recently completed $8 billion acquisition of Informatica. In part, I believe that people are paying attention because deal-making is up in 2025. M&A volume reached $2.2 trillion in the first half of the year, a 27% increase compared to a year ago, according to JP Morgan. Notably, 72% of that volume involved deals greater than $1 billion. 

There will be thousands of mergers and acquisitions in the United States this year across industries and involving companies of all sizes. It’s not unusual for startups to position themselves to be snapped up. But Informatica, founded in 1993, didn’t fit that mold. We have been building, delivering, supporting and partnering for many years. Much of the value we bring to Salesforce and its customers is our long-earned experience and expertise in enterprise data management. 

Although, in other respects, a “legacy” software company like ours — founded well before cloud computing was mainstream — and early-stage startups aren’t so different. We all must move fast and differentiate. And established vendors and growth-oriented startups have a few things in common when it comes to M&A, as well. 

First and foremost is a need to ensure that the strategies of the two companies involved are in alignment. That seems obvious, but it’s easier said than done. Are their tech stacks based on open protocols and standards? Are they cloud-native by design? And, now more than ever, are they both AI-powered and AI-enabling? All of these came together in the case of Salesforce and Informatica, including our shared belief in agentic AI as the next major breakthrough in business technology.

Don’t take your foot off the gas

In the days after the acquisition was completed, I was asked during a media interview if good luck was a factor in bringing together these two tech industry stalwarts. Replace good luck with good timing, and the answer is a resounding, “Yes!”

As more businesses pursue the productivity and other benefits of agentic AI, they require high-quality data to be successful. These are two areas where Salesforce and Informatica excel, respectively. And the agentic AI opportunity — estimated to grow to $155 billion by 2030 — is here and now. So the timing of the acquisition was perfect. 

Tremendous effort goes into keeping an organization on track, leading up to an acquisition and then seeing it through to a smooth and successful completion. In the few months between the announcement of Salesforce’s intent to acquire Informatica and the close, we announced new partnerships and customer engagements and a fall product release that included autonomous AI agents, MCP servers and more. 

In other words, there’s no easing into the new future. We must maintain the pace of business because the competitive environment and our customers require it. That’s true whether you’re a small, venture-funded organization or, like us, an established firm with thousands of employees and customers. Going forward we plan to keep doing what we do best: help organizations connect, manage and unify their AI data. 

Out with the old, in with the new

It’s wrong to think of an acquisition as an end game. It’s a new chapter. 

Business leaders and employees in many organizations have demonstrated time and again that they are quite good at adapting to an ever-changing competitive landscape. A few years ago, we undertook a company-wide shift from on-premises software to cloud-first. There was short-term disruption but long-term advantage. It’s important to develop an organizational mindset that thrives on change and transformation, so when the time comes, you’re ready for these big steps. 

So, even as we take pride in all that we accomplished to get to this point, we now begin to take on a fresh identity as part of a larger whole. It’s an opportunity to engage new colleagues and flourish professionally. And importantly, customers will be the beneficiaries of these new collaborations and synergies. On the day Informatica was welcomed into the Salesforce family and ecosystem, I shared my feeling that “the best is yet to come.” That’s my North Star and one I recommend to every business leader forging ahead into an M&A evolution — because the truest measure of success ultimately will be what we accomplish next.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.



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