Welcome to Eye on AI. In this edition…Anthropic is winning over business customers, but how are its own engineers using its Claude AI models…OpenAI CEO Sam Altman declares a “code red”…Apple reboots its AI efforts—again…Former OpenAI chief scientist Ilya Sutskever says “it’s back to the age of research” as LLMs won’t deliver AGI…Is AI adoption slowing?OpenAI certainly has the most recognizable brand in AI. As company founder and CEO Sam Altman said in a recent memo to staff, “ChatGPT is AI to most people.” But while OpenAI is increasingly focused on the consumer market—and, according to news reports declaring “a code red” in response to new, rival AI models from
Google (see the “Eye on AI News” section below)—it may already be lagging in the competition for enterprise AI. In this battle for corporate tech budgets, one company has quietly emerged as the vendor big business customers seem to prefer: Anthropic.
Anthropic has, according to some research, moved past OpenAI in enterprise marketshare. A Menlo Ventures survey from the summer showed Anthropic with a 32% market share by model usage compared to OpenAI’s 25% and Google’s 20%. (OpenAI disputes these numbers, noting that Menlo Ventures is an Anthropic investor and that the survey had a small sample size. It says that it has 1 million paying business customers compared to Anthropic’s 330,000.) But estimates in a HSBC research report on OpenAI that was published last week also give Anthropic a 40% marketshare by total AI spending compared to OpenAI’s 29% and Google’s 22%.
How did Anthropic take the poll position in the race for enterprise AI adoption? That’s the question I set out to answer in the latest cover story of
Fortune magazine. For the piece, I had exclusive access to Anthropic cofounder and CEO Dario Amodei and his sister Daniela Amodei, who serves as the company’s president and oversees much of its day-to-day operations, as well as to numerous other Anthropic execs. I also spoke to Anthropic’s customers to find out why they’ve come to prefer its Claude models. Claude’s prowess at coding, an area Anthropic devoted attention to early on, is clearly one reason. (More on that below.) But it turns out that part of the answer has to do with Anthropic’s focus on AI safety, which has given corporate tech buyers some assurance that its models are a less risky than competitors’. It’s a logic that undercuts the argument of some Anthropic critics, including powerful figures such as White House AI and crypto czar David Sacks, who see the company’s advocacy of AI safety testing requirements as a mistaken policy that will slow AI adoption.
Now the question facing Anthropic is whether it can hold on to its lead, raise enough funds to cover its still massive burn rate, and manage its hypergrowth without coming apart at the seams. Do you think Anthropic can go the distance? Give the story a read
here and let me know what you think.
How is AI changing coding?Now, back to Claude and coding. In March, Dario Amodei
made headlines when he said that by the end of the year 90% of software code within enterprises would be written by AI. Many scoffed at that forecast, and, in fact, Amodei has since walked back the statement slightly, saying that he never meant to imply there wouldn’t still be a human in the loop before that code is actually deployed. He’s also said that his prediction was not far off as far as Anthropic itself is concerned, but he’s used a far looser percentage range for that,
saying in October that these days “70, 80, 90% of code” is touched by AI at his company.
Well, Anthropic has a team of researchers that looks at the “societal impacts” of AI technology. And to get a sense of how exactly AI is changing the nature of software development, it examined how 132 of its own engineers and researchers are using Claude. The study used both qualitative interviews with the employees as well as an examination of their Claude usage data. You can read Anthropic’s blog on the study
here, but we’ve got an exclusive first look at what they found:
Anthropic’s coders self-reported that they used Claude for about 60% of their work tasks. More than half of the engineers said they can “fully delegate” up to between none and 20% of their work to Claude, because they still felt the need to check and verify Claude’s outputs. The most common uses of Claude were debugging existing code, helping human engineers understand what parts of the codebase were doing, and, to a somewhat lesser extent, implementing new software features. It was far less common to use Claude for high-level software design and planning tasks, data science tasks, and front-end development.
In response to my questions about whether Anthropic’s research contradicted Amodei’s prior statements, an Anthropic spokesperson noted the study’s small sample size. “This is not a reflection of concertedly surveying engineers across the entire company,” the spokesperson said. Anthropic also noted that the research did not include “writing code” as a distinctive task, so the research could not provide an apples-to-apples comparison with Amodei’s statements. It said that the engineers all defined the idea of automation and “fully delegating” coding tasks to Claude differently, further muddying any clear reflection on Amodei’s remarks.
Nevertheless, I think it’s telling that Anthropic’s engineers and researchers were not exactly ready to hand a lot of important tasks to Claude. In interviews, they said they tended to hand Claude tasks that they were fairly confident were not complex, that were repetitive or boring, where Claude’s work could be easily verified, and, notably, “where code quality isn’t critical.” That seems a somewhat damning assessment of Claude’s current abilities.
On the other hand, the engineers said that without Claude, about 27% of the work they are now doing simply would not have been done at all in the past. This included using AI to build interactive dashboards that they just would not have bothered building before, and building tools to perform small code fixes that they might not have bothered remediating previously. The usage data also found that 8.6% of Claude Code tasks were what Anthropic categorized as “papercut fixes.”
Not just deskilling, but devaluing too? Opinions were divided.The most interesting findings of the report were how using Claude made the engineers feel about their work. Many were happy that Claude was enabling them to handle a wider range of software development tasks than previously. And some said using Claude freed them to think about higher level skills—considering product design concepts and user experience more deeply, for instance, instead of focusing on the rudiments of how to execute the design.
But some worried about losing their own coding skills. “Now I rely on AI to tell me how to use new tools and so I lack the expertise. In conversations with other teammates I can instantly recall things vs now I have to ask AI,” one engineer said. One senior engineer worried particularly about what this would do to more junior coders. “I would think it would take a lot of deliberate effort to continue growing my own abilities rather than blindly accepting the model output,” the senior developer said. Some engineers reported practicing tasks without Claude specifically to combat deskilling.
And the engineers were split about whether using Claude robbed them of the meaning and satisfaction they took from work. “It’s the end of an era for me—I’ve been programming for 25 years, and feeling competent in that skill set is a core part of my professional satisfaction,” one said. Another reported that “spending your day prompting Claude is not very fun or fulfilling.” But others were more ambivalent. One noted that they missed the “zen flow state” of hand coding but would “gladly give that up” for the increased productivity Claude gave them. At least one said they felt more satisfaction in their job. “I thought that I really enjoyed writing code, and instead I actually just enjoy what I get out of writing code,” this person said.
Anthropic deserves credit for being transparent about what it knows about how its own products are impacting its workforce—and for reporting the results even if they contradict things their CEO has said. The issues the Anthropic survey has brought up around deskilling and the impact of AI on the sense of meaning that people derive from their work are issues more and more people will be facing across industries soon.
Ok, I hope to see many of you in person at
Fortune Brainstorm AI San Francisco next week! If you are still interested in joining us you can click
here to apply to attend.
And with that, here’s more AI news.
Jeremy Kahnjeremy.kahn@fortune.com@jeremyakahn
