{"id":165077,"date":"2025-12-03T01:15:15","date_gmt":"2025-12-03T01:15:15","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/165077\/"},"modified":"2025-12-03T01:15:15","modified_gmt":"2025-12-03T01:15:15","slug":"anthropics-safety-first-approach-has-won-over-big-business-and-how-its-own-engineers-use-claude","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/165077\/","title":{"rendered":"Anthropic’s safety first approach has won over big business\u2014and how its own engineers use Claude"},"content":{"rendered":"

Welcome to Eye on AI. In this edition\u2026Anthropic is winning over business customers, but how are its own engineers using its Claude AI models\u2026OpenAI CEO Sam Altman declares a \u201ccode red\u201d\u2026Apple<\/a> reboots its AI efforts\u2014again\u2026Former OpenAI chief scientist Ilya Sutskever says \u201cit\u2019s back to the age of research\u201d as LLMs won\u2019t deliver AGI\u2026Is AI adoption slowing?<\/p>\n

OpenAI certainly has the most recognizable brand in AI. As company founder and CEO Sam Altman said in a recent memo to staff, \u201cChatGPT is AI to most people.\u201d But while OpenAI is increasingly focused on the consumer market\u2014and, according to news reports declaring \u201ca code red\u201d in response to new, rival AI models from Google<\/a> (see the \u201cEye on AI News\u201d section below)\u2014it 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.<\/p>\n

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\u2019s 25% and Google\u2019s 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\u2019s 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\u2019s 29% and Google\u2019s 22%.<\/p>\n

How did Anthropic take the poll position in the race for enterprise AI adoption? That\u2019s 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\u2019s president and oversees much of its day-to-day operations, as well as to numerous other Anthropic execs. I also spoke to Anthropic\u2019s customers to find out why they\u2019ve come to prefer its Claude models. Claude\u2019s 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\u2019s focus on AI safety, which has given corporate tech buyers some assurance that its models are a less risky than competitors\u2019. It\u2019s 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\u2019s advocacy of AI safety testing requirements as a mistaken policy that will slow AI adoption.<\/p>\n

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<\/a> and let me know what you think.<\/p>\n

How is AI changing coding?<\/p>\n

Now, back to Claude and coding. In March, Dario Amodei made headlines<\/a> 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\u2019t still be a human in the loop before that code is actually deployed. He\u2019s also said that his prediction was not far off as far as Anthropic itself is concerned, but he\u2019s used a far looser percentage range for that, saying in October<\/a> that these days \u201c70, 80, 90% of code\u201d is touched by AI at his company.<\/p>\n

Well, Anthropic has a team of researchers that looks at the \u201csocietal impacts\u201d 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\u2019s blog on the study here<\/a>, but we\u2019ve got an exclusive first look at what they found:<\/p>\n

Anthropic\u2019s coders self-reported that they used Claude for about 60% of their work tasks. More than half of the engineers said they can \u201cfully delegate\u201d up to between none and 20% of their work to Claude, because they still felt the need to check and verify Claude\u2019s 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.<\/p>\n

In response to my questions about whether Anthropic\u2019s research contradicted Amodei\u2019s prior statements, an Anthropic spokesperson noted the study\u2019s small sample size. \u201cThis is not a reflection of concertedly surveying engineers across the entire company,\u201d the spokesperson said. Anthropic also noted that the research did not include \u201cwriting code\u201d as a distinctive task, so the research could not provide an apples-to-apples comparison with Amodei\u2019s statements. It said that the engineers all defined the idea of automation and \u201cfully delegating\u201d coding tasks to Claude differently, further muddying any clear reflection on Amodei\u2019s remarks.<\/p>\n

Nevertheless, I think it\u2019s telling that Anthropic\u2019s 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\u2019s work could be easily verified, and, notably, \u201cwhere code quality isn\u2019t critical.\u201d That seems a somewhat damning assessment of Claude\u2019s current abilities.<\/p>\n

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 \u201cpapercut fixes.\u201d<\/p>\n

Not just deskilling, but devaluing too? Opinions were divided.<\/p>\n

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\u2014considering product design concepts and user experience more deeply, for instance, instead of focusing on the rudiments of how to execute the design.<\/p>\n

But some worried about losing their own coding skills. \u201cNow 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,\u201d one engineer said. One senior engineer worried particularly about what this would do to more junior coders. \u201cI would think it would take a lot of deliberate effort to continue growing my own abilities rather than blindly accepting the model output,\u201d the senior developer said. Some engineers reported practicing tasks without Claude specifically to combat deskilling.<\/p>\n

And the engineers were split about whether using Claude robbed them of the meaning and satisfaction they took from work. \u201cIt\u2019s the end of an era for me\u2014I\u2019ve been programming for 25 years, and feeling competent in that skill set is a core part of my professional satisfaction,\u201d one said. Another reported that\u00a0 \u201cspending your day prompting Claude is not very fun or fulfilling.\u201d But others were more ambivalent. One noted that they missed the \u201czen flow state\u201d of hand coding but would \u201cgladly give that up\u201d for the increased productivity Claude gave them.\u00a0At least one said they felt more satisfaction in their job. \u201cI thought that I really enjoyed writing code, and instead I actually just enjoy what I get out of writing code,\u201d this person said.<\/p>\n

Anthropic deserves credit for being transparent about what it knows about how its own products are impacting its workforce\u2014and 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.<\/p>\n

Ok, I hope to see many of you in person at Fortune Brainstorm AI San Francisco next week!\u00a0If you are still interested in joining us you can click here<\/a> to apply to attend. <\/p>\n

And with that, here\u2019s more AI news.<\/p>\n

Jeremy Kahn
jeremy.kahn@fortune.com<\/a>
@jeremyakahn\n<\/p>\n

FORTUNE ON AI<\/p>\n

Five years on, Google DeepMind\u2019s AlphaFold shows why science may be AI\u2019s killer app<\/a>\u2014by Jeremy Kahn<\/p>\n

Exclusive: Gravis Robotics raises $23M to tackle construction\u2019s labor shortage with AI-powered machines<\/a>\u2014by Beatrice Nolan\n<\/p>\n

The creator of an AI therapy app shut it down after deciding it\u2019s too dangerous. Here\u2019s why he thinks AI chatbots aren\u2019t safe for mental health<\/a>\u2014by Sage Lazzaro<\/p>\n

Nvidia\u2019s CFO admits the $100 billion OpenAI megadeal \u2018still\u2019 isn\u2019t signed\u2014two months after it helped fuel an AI rally<\/a>\u2014by Eva Roytburg\n<\/p>\n

AI startup valuations are doubling and tripling within months as back-to-back funding rounds fuel a stunning growth spurt<\/a>\u2014by Allie Garfinkle\n<\/p>\n

Insiders say the future of AI will be smaller and cheaper than you think<\/a>\u2014by Jim Edwards\n<\/p>\n

AI IN THE NEWS<\/p>\n

OpenAI declares \u201ccode red\u201d over enthusiasm for Google Gemini 3 and rival models. OpenAI CEO Sam Altman has declared a \u201cCode Red\u201d inside OpenAI as competition from Google\u2019s newly strengthened Gemini 3 model\u2014and from Anthropic and Meta\u2014intensifies. Altman told staff in an internal memo that the company will redirect resources toward improving ChatGPT and delay initiatives like a planned roll-out of advertising within the popular chatbot. It\u2019s a striking reversal for OpenAI, coming almost three years to the day after the debut of ChatGPT, which put Google on a backfoot and caused its CEO Sundar Pichai to reportedly issue his own \u201ccode red\u201d inside the tech giant. You can read more from Fortune\u2019s Sharon Goldman here<\/a>.<\/p>\n

ServiceNow buys identity and access management company Veza to help with AI agent push. The big SaaS software vendor is acquiring Veza, a startup that bills itself as \u201can AI-native identity-security platform.\u201d The company plans to use Veza\u2019s capabilities to bolster its agentic AI offerings and grow its cybersecurity and risk management business, which is one of ServiceNow\u2019s fastest growing segments, with more than $1 billion in annual contract value. The financial terms of the deal were not announced, but Veza was last valued at $808 million when it raised a $108 million Series D financing round in April and news reports suggested that ServiceNow was paying an amount north of $1 billion to buy the company. Read more from ServiceNow here<\/a>.
OpenAI suffers data breach. The company said some customers of its API service\u2014but not ordinary ChatGPT users\u2014may have had profile data exposed after a cybersecurity breach at its former analytics vendor, Mixpanel. The leaked information includes names, email addresses, rough location data, device details, and user or organization IDs, though OpenAI says there is no evidence that any of its own systems were compromised. OpenAI has ended its relationship with Mixpanel, has notified affected users, and is warning them to watch for phishing attempts, according to a story<\/a> in tech publication The Register.
Apple AI head steps down as company\u2019s AI efforts continue to falter. John Giannandrea, who had been heading Apple\u2019s AI efforts, is stepping down after seven years. The move comes as the company faces criticism for lagging rivals in rolling out advanced generative AI features, including long-delayed upgrades to Siri. He will be replaced by veteran AI executive Amar Subramanya, who previously held senior roles at Microsoft and Google and is expected to help sharpen Apple\u2019s AI strategy under software chief Craig Federighi. Read more from The Guardian here<\/a>.
OpenAI invests in Thrive Holdings in the latest \u2018circular\u2019 deal in AI. OpenAI has taken a stake in Thrive Holdings\u2014an AI-focused private-equity platform created by Thrive Capital, which is itself a major investor in, you got it, OpenAI. It is just the latest example of the tangled web of interlocking financial relationships OpenAI has woven between its investors, suppliers, and customers. Rather than investing cash, OpenAI received a \u201cmeaningful\u201d equity stake in exchange for providing Thrive-owned companies with access to its models, products, and technical talent, while also gaining access these companies\u2019 data, which will be used to fine-tune OpenAI\u2019s models. You can read more from the Financial Times here<\/a>.<\/p>\n

EYE ON AI RESEARCH<\/p>\n

Back to the drawing board. There was a time, not all that long ago, when it would have been hard to find anyone who was as fervent an advocate of the \u201cscale is all you need\u201d hypothesis of AGI than Ilya Sutskever. (To recap, this was the idea that simply building bigger and bigger Transformer-based large language models and feeding them ever more data and training them on ever larger computing clusters would eventually deliver human-level artificial general intelligence and, beyond that, superintelligence greater than all humanity\u2019s collective wisdom.) So it was striking to see the former OpenAI chief scientist sit down with podcaster Dwarkesh Patel in an episode of the \u201cDwarkesh\u201d podcast that dropped last week and hear him say he is now convinced that LLMs will never deliver human-level intelligence.
Sutskever now says he is convinced LLMs will never be able to generalize well to domains that were not explicitly in their training data, which means they will struggle to ever develop truly new knowledge. He also noted that LLM training is highly inefficient\u2014requiring thousands or millions of examples of something and repeated feedback from human evaluators\u2014whereas people can usually learn something from just a handful of examples and can also fairly easily analogize from one domain to another.
As a result, Sutskever, who now runs his own AI startup, Safe Superintelligence, tells Patel that its \u201cback to the age of research again\u201d\u2014looking for new ways of designing neural networks that will achieve the field\u2019s Holy Grail of AGI. Sutskever said he has some intuitions on how to achieve this, but that for commercial reasons he wasn\u2019t going to share them on \u201cDwarkesh.\u201d Despite his silence on those trade secrets, the podcast is worth listening to. You can hear the whole thing here<\/a>. (Warning, it\u2019s long. You might want to give it to your favorite AI to summarize.)\u00a0<\/p>\n

AI CALENDAR<\/p>\n

Dec. 2-7:\u00a0NeurIPS, San Diego\n<\/p>\n

Dec. 8-9:\u00a0Fortune Brainstorm\u00a0AI\u00a0San Francisco. Apply to attend\u00a0here<\/a>.\n<\/p>\n

Jan. 6:\u00a0Fortune Brainstorm Tech CES Dinner. Apply to attend here<\/a>.\n<\/p>\n

Jan. 19-23:World Economic Forum, Davos, Switzerland.<\/p>\n

Feb. 10-11:\u00a0AI Action Summit, New Delhi, India.\n<\/p>\n

BRAIN FOOD<\/p>\n

Is AI adoption slowing? That\u2019s what a story<\/a> in The Economist argues, citing a number of recently released figures. New U.S. Census Bureau data show that employment-weighted workplace AI use in America has slipped to about 11%, with adoption falling especially sharply at large firms\u2014an unexpectedly weak uptake three years into the generative-AI boom. Other datasets point to the same cooling: Stanford researchers find usage dropping from 46% to 37% between June and September, while Ramp reports that AI adoption in early 2025 surged to 40% before flattening, suggesting momentum has stalled.
This slowdown matters because big tech firms plan to spend $5 trillion on AI infrastructure in the coming years and will need roughly $650 billion in annual revenues\u2014mostly from businesses\u2014to justify it. Explanations for the slow pace of AI adoption range from macroeconomic uncertainty to organizational dynamics, including managers\u2019 doubts about current models\u2019 ability to deliver meaningful productivity gains. The article argues that unless adoption accelerates, the economic payoff from AI will come more slowly and unevenly than investors expect, making today\u2019s massive capital expenditures difficult to justify.<\/p>\n","protected":false},"excerpt":{"rendered":"Welcome to Eye on AI. In this edition\u2026Anthropic is winning over business customers, but how are its own…\n","protected":false},"author":2,"featured_media":165078,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[345,1463,343,344,4194,48596,3484,85,46,1748,35849,125],"class_list":{"0":"post-165077","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-anthropic","10":"tag-artificial-intelligence","11":"tag-artificialintelligence","12":"tag-coding","13":"tag-dario-amodei","14":"tag-eye-on-ai","15":"tag-il","16":"tag-israel","17":"tag-openai","18":"tag-software-developers","19":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/165077","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=165077"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/165077\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/165078"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=165077"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=165077"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=165077"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}