Anthropic’s Claude AI Has 1 Killer Use Case, According to New Data

Software engineering is the overwhelming favorite use case for Claude, Anthropic’s AI model, according to a new report published by the company. The report, the third in a series tracking AI’s economic effects, also breaks down how enterprises are using Anthropic’s AI models. The takeaway? Enterprises are heavily focused on using Claude to automate tasks. The report, titled “Uneven Geographic and Enterprise AI Adoption,” found that 36 percent of sampled conversations on Claude.ai, Anthropic’s ChatGPT-like platform for chatting with Claude, are centered on providing software development assistance. That makes it by far the AI model’s most popular use case. It should come as no surprise, then, that software developers working on applications are Claude’s heaviest users, making up 5.2 percent of all usage. The other top Claude.ai uses, according to Anthropic’s data, include providing assistance with writing, acting as a virtual tutor, conducting research, and supplying financial guidance and investment assistance. The report also tracked how enterprises are using Claude’s API, which enables developers to integrate Claude into their products and software applications. The data shows that businesses are largely using Claude to automate tasks, rather than using it as a learning tool or a collaborator. Anthropic says this shouldn’t come as a surprise, because the API naturally lends itself to automation. “Businesses provide context,” the company explained, “Claude executes the task, and the output flows directly to end users or downstream systems.” Like with Claude.ai, according to the report, software development is by far the most popular use for enterprises using the Claude API, with just under half of all API traffic accounting for computer and mathematical tasks. More specifically, 6.1 percent of all Claude API use is for resolving technical issues and workflow problems in software development; 6 percent is for debugging and developing front-end code and components for web applications; 5.2 percent for developing or managing professional business software; and 4.9 percent for troubleshooting and optimizing software. In the report, Anthropic wrote that code generation tasks dominate API traffic “because they hit a sweet spot where model capabilities excel, deployment barriers are minimal, and employees can adopt the new technology quickly.” But coding isn’t the only way that enterprises are using Claude. Ten percent of API usage comes in the form of office and administrative tasks, 7 percent is for science tasks, 4 percent is for sales and marketing tasks, and 3 percent is for business and financial operations. The report also examined how the cost of using Claude to handle specific tasks correlates with usage amounts. According to the data, tasks typical of computer and mathematical jobs, like coding and data analysis, cost over 50 percent more than sales-related tasks, but still dominate overall use of the tech. This, according to the company, “suggests that cost plays an immaterial role in shaping patterns of enterprise AI deployment.” Rather than focusing on costs, Anthropic postulated, “businesses likely prioritize use in domains where model capabilities are strong and where Claude-powered automation generates enough economic value in excess of the API cost.” The report also revealed how each state in the U.S. typically uses Claude (specifically Claude.ai). Unsurprisingly, California (where Anthropic is based) is far and away the biggest Claude user, accounting for 25.3 percent of total use. Other states with heavy Claude usage include New York (9.3 percent), Texas (6.7 percent), and Virginia (4 percent). BY BEN SHERRY @BENLUCASSHERRY

Gen-Z AI Founders Are Merging Work and Life in These 3 Ways

Young AI founders in San Francisco are upending preconceived notions about Gen Z’s approach to work-life balance. In a recent Wall Street Journal article, founders from ages 18 to 32 described a lifestyle entirely structured around their companies. These founders and their grind-first mindsets are in stark contrast to a 2024 Deloitte survey, which found that while 36 percent of Gen Z respondents consider work to be central to their identity, 25 percent consider work-life balance the top factor in choosing an employer. Far from quiet quitting, these founders are working seven day weeks, living in their offices, and eating only for sustenance. And they couldn’t be happier, at least according to the Journal’s reporting. Here’s what these young founders are doing to win in the AI era. Living in the office Several young founders interviewed by the Journal claimed to be working constantly. Marty Kausas, a 28-year-old founder building an AI startup called Pylon, said he had recently worked three 92-hour weeks in a row. And Nico Laqua, a 25-year-old cofounder of AI-powered insurance startup Corgi, said that he lives in his office and typically spends “every waking hour” working (doggedly, perhaps) on his company. He claims to only hire people willing to work seven days a week. Indeed, Corgi is currently hiring for a chef to provide the team with breakfast, lunch, and dinner seven days a week. Blowing up the work-life balance Even when they’re not physically in the office, these founders are reportedly almost always advancing their business interests in some way. Recent social activities for Kausas include attending a hackathon and taking a bike ride with a fellow founder. Emily Yuan, a Corgi co-founder, told reporters that she and her founder friends spend their free time discussing funding rounds while exercising and going to saunas. De-centralizing food Another common theme among the interviewed founders is their attitudes toward food and meals. Kausas told the Journal that he eats pre-packaged breakfasts and lunches from nutrition and supplements company Blueprint, because “the workday is more efficient if he doesn’t have to think about food.” Haseab Ullah, founder of an AI customer support chatbot, also claimed to have a utilitarian approach to eating. Usually, his only meal of the day is an Uber Eats-delivered treat, a tactic that he said helps him “save time and avoid cooking.” (A young person using Uber Eats to avoid cooking may not be a shocker, but using it to source every meal sounds more extreme.) Michelle Fang, an event planner at VC firm Headline, told the Journal that many founder-focused get-togethers in San Francisco don’t even serve alcohol, both because it is “out of fashion in the San Francisco crowd,” and because many founders “aren’t old enough to drink” yet. BY BEN SHERRY @BENLUCASSHERRY

OpenAI Introduces GPT-5-Codex, an AI Model Built Just for Coding

OpenAI has announced its newest model, GPT-5-Codex. The new model has been optimized for agentic coding in OpenAI’s suite of AI-powered software engineering tools, which is called Codex. This year, AI programs that can write and edit software have emerged as the most lucrative use case for AI, propelling multiple companies to huge revenue increases. These tools are being used both by professional developers to make their work more efficient, and by casual vibe coders, who lack the technical skill to create websites and apps. The Sam Altman-led company claims that by training this new AI model on real-world engineering tasks, it can outperform the default model. In a benchmark that compared that model and GPT-5-Codex’s ability to refactor code (essentially reorganizing and cleaning up code), GPT-5-Codex scored nearly 20 percent higher than the default model, which is simply called GPT-5. GPT-5-Codex is also said to be a strong independent worker. It can work autonomously on software for long stretches of time. According to a press release, OpenAI has seen the model “work independently for more than seven hours at a time on large, complex tasks, iterating on its implementation, fixing test failures, and ultimately delivering a successful implementation.” The new model could also help alleviate one of the most notable pain points of vibe coding: bad code. Many software developers have remarked that much of their time working with AI-assisted code editors is spent cleaning up the AI’s code, which isn’t always as thoughtfully written as a human expert’s would be. But OpenAI says that GPT-5-Codex has been “trained specifically for conducting code reviews and finding critical flaws.” In practice, the company says, this means GPT-5-Codex will review an entire codebase to identify flaws and autonomously test apps to find errors. OpenAI says that Codex currently handles “the vast majority” of proposed changes to code being written by OpenAI staffers, “catching hundreds of issues every day—often before a human review begins.” But even with its improved code review abilities, OpenAI still recommends using Codex as an additional reviewer; it says in a press release that it is “not a replacement for human reviews.” Unlike the normal version of GPT-5, GPT-5-Codex won’t be immediately available via API, and OpenAI recommends only using the model for coding tasks in Codex-supported environments. In addition, Codex is coming to mobile devices for the first time. Previously, to access Codex, you’d either need to use ChatGPT on a desktop computer or invoke Codex in an IDE (integrated development environment) like VSCode or Cursor. Now, Codex will be accessible in the ChatGPT iOS app, enabling easier coding on the go. Codex, and GPT-5-Codex, is available across all of ChatGPT’s paid tiers, with $20-per-month ChatGPT Plus members getting enough access to “cover a few focused coding sessions each week.” Meanwhile, $200-per-month ChatGPT Pro members will get enough to “support a full workweek across multiple projects.” Companies that pay for ChatGPT’s SMB-focused Business plan can purchase credits to give their developers more access to Codex, while larger companies with ChatGPT’s Enterprise plan get a shared credit pool. In OpenAI’s press release, engineers and tech leads at companies including Cisco, Duolingo, Ramp, Vanta, and Virgin Atlantic praised Codex’s utility, but it remains to be seen if GPT-5-Codex can help OpenAI take market share away from Anthropic, whose similar Claude Code product has proved very popular with professional and casual software developers. BY BEN SHERRY @BENLUCASSHERRY

‘I Feel Like a Better Manager’: Execs Share How AI Transforms How They Lead

It hasn’t taken long for business leaders to discover that AI can help them manage people, and they are using it in ways that executives likely couldn’t have dreamed of several years ago—from reimagining how an org chart works to using AI to help them write a tricky email. We spoke to five CEOs—and one chief human resources officer—to learn how they are harnessing AI to help get the most out of their people. They are: Arvind Jain, CEO, Glean, an AI enterprise search platform that has 1,000 employees and was most recently valued at $7.2 billion, according to PitchBook Stacy Spikes, CEO, MoviePass, a subscription-based movie ticketing service, which recently announced a $100 million capital investment Aakash Shah, CEO, Wyndly, a startup focusing on personalized and modern allergy treatments, which ranked No. 333 on the Inc. 5000 this year Renata Black, CEO, EBY, a membership-based women’s intimate apparel company that has raised more than $18 million, according to PitchBook Ashley Kirkwood, CEO, Speak Your Way to Cash, a sales and speaking training organization Ali Bebo, chief human resources officer, Pearson, a U.K.-based education and testing services company Throughout this process, these leaders are finding that AI is pushing their employees to reach beyond what they thought they were capable of—like setting benchmarks, preparing for one-on-ones, and improving reports before they reach their managers. And it’s giving CEOs a lot to consider when it comes to how they run their workplace. The technology, says Spikes, is “going to create more than it will take away.” 1. Supercharge the org chart Jain, who started Glean in 2019, sees himself as a facilitator. That means he has to make sure every task gets assigned to the right person or group—and for him, an old-fashioned org chart just isn’t good enough. “It gets obsolete quickly, because the world is changing so fast,” he says. That’s why his company, which makes AI tools designed to help businesses find answers and automate workflows, has created a kind of living org chart with AI. Jain says that when he has an idea, he doesn’t have time to waste working out which person or team has capacity to take it on. Instead, he wants to get straight to the person or people who can best work on it with him. Glean’s AI examines employees’ work and contributions in real time, mapping core competencies in a way a traditional org chart can’t. The AI is “constantly observing on any given subject matter who are the top voices, who are the ones who are answering the most questions in Slack or in Teams, who are the ones who are writing authoritative documents on that,” Jain says. He adds that he uses this tool every day to help Glean move fast on new ideas and keep projects on track. Pearson’s Bebo says that employees use an in-house AI agent called CARA that can answer questions about their role and ways that they can excel or get promoted: “She is what I would describe as our people’s friend as they think about navigating their career here,” Bebo says. CARA is designed to act as an enabler, helping both employees and managers be more effective and understand where they are in relation to their job expectations and goals. “We don’t want to have AI replace managers, but we really want to think about how it helps our managers even perform better,” she says. One way Spikes sees AI transforming his workforce at MoviePass is by creating more opportunities for the people he has—and for tomorrow’s hires. “I’m finding that it is overall increasing how you’re going to use people, not decreasing how you’re going to use them,” he says. “I think that’s the beauty of this emerging technology.” 2. Transform meetings from status updates into deep conversations Shah, Wyndly co-founder and CEO, uses AI to better prepare for his one-on-ones, especially with his executive team and co-founder, Manan Shah, his cousin. He sees it as akin to the culinary technique of “mise en place,” where chefs prep everything they need before they turn on the heat. “If we can get everything prepped before we’re ready to jump into the work, it makes the work both more fulfilling but also just more effective,” he says, adding that it also creates room for more interpersonal connections between him and his direct reports. “I think that’s what the difference maker is between a good and a bad leader, at least for me, is whenever I’ve been able to spend more time on the interpersonal stuff, I found that I feel like a better manager,” Shah says. At intimate apparel retailer EBY, CEO Black says the entire company is mandated to use AI to help optimize reports and analysis before presenting anything to her. Black makes them show her their original plan and how they optimized it using AI. As a result, her people have more clarity into what they are doing and how to achieve their full potential, she says. “AI allows them to present information in a much clearer way that allows them to be more confident in what they’re presenting,” she says. In turn, she is able to give them better feedback. 3. Power up performance reviews and employee evaluations Bebo, who joined Pearson in 2021 to assist in its culture and business transformation, says that AI agents are embedded in the performance reviews at the company. But while managers are still doing the employee evaluations, the AI can help both employees and leaders craft sharper and more articulate reviews and self-assessments so that every single one “sounds like Pearson.” The agents aren’t mandatory, but for managers who do use them, Bebo reports that they have sped up the performance review process and helped them deliver meaningful feedback to their employees. Glean takes this approach one step further in its performance reviews, says CEO Jain. While managers and employees use AI prompts to help them write their assessments like at Pearson, Glean also uses AI to collect and analyze each employee’s contribution to the company, enabling managers to have a complete, clear, and—crucially—objective record of everything the employee did during the review period. That combats biases and favoritism, Jain says, but it also means he doesn’t forget or overlook any of his employees’ achievements or sticking points. “The conversation shifts from getting on the same page to, actually, we are already on the same page, and this is now a time to solve problems that you run into so that you can become better, you can grow as an employee,” he says. 4. Use AI prompts to get the best responses from your people Spikes, who co-founded MoviePass in 2011, left in 2018, and then returned to save the company in 2021, says he started using AI prompts with his teams to challenge them to think differently about how they are tackling business challenges or new projects. “That curiosity helps speed up the team,” he says, mentioning that some projects that used to take weeks now take as little as a couple of hours. What that gives him as a manager is not just a faster outcome, but also more opportunities for iterations and feedback, leading to a better outcome. “You get much more of a response loop that you just didn’t have before,” Spikes says. Jain also uses AI prompts with his Glean executive team, asking them to set business goals each week. Then he uses a custom-built AI that helps him track progress and gather insights on each of those goals. He says that gives him a “deep understanding” of precisely where there was forward momentum and where there were slowdowns or blocks. And Wyndly CEO Shah says his business is moving to a similar model. When people do their daily check-in, they are prompted to think about how what they are doing is aligning with the business’s goals and to preempt what questions Shah might have for them based on what they report. That way, he says, “everyone’s speaking the same language.” 5. Let AI be a thought partner Knowing what to say and how to say it is crucial to getting a CEO’s message and vision across to their employees, and AI can act like the ultimate comms specialist and thought partner to do just that. “Anytime I have to write a very complicated email, I just press play. I tell it exactly what I want to say, and then I say, polish this up, and then make it super short and punchy. And it gives me a really strong response,” EBY’s Black says. Speak Your Way to Cash CEO Kirkwood, who published a book with the same name as her company in 2021, agrees that AI can help take the edge off otherwise potentially tense interactions with staff. “If I have to have a difficult conversation, it’s helpful for me to have a script,” she says. “That way I can have it quickly, succinctly, get in and out, and not open up any legal liabilities.” AI can also help temper hard-to-hear feedback so that your employees get the message without getting over-anxious, Black says, adding that because she has a very direct style of communication, AI can help soften her tone without losing impact. “That’s like the AI coaching me on my leadership skills,” she says. Wyndly’s Shah puts it another way: When he wants to send out a company-wide message at Wyndly, AI is a strategy for getting over “blank-page syndrome.” And at Pearson, some of the company’s executives have created digital twins that act as “thought partners,” helping them role-play different conversations and strengthen their arguments, Bebo says. “Think of AI as your friend and a partner,” she says. “It doesn’t replace your owning and delivering and making sure you’re sending the right message. It’s just sharpening the conversation.” BY CLAIRE CAMERON, FREELANCE WRITER

ELON MUSK xAI STRATEGIC ACQUISITION OF X(FORMERLY TWITTER)

Elon Musk Just Pulled Off His Most Strategic Move Yet—And No One Saw It Coming. His AI company, xAI, just acquired X (formerly Twitter) in a massive $33 billion deal. On the surface, it looks like just another corporate shuffle. But in reality, Musk may have just outmaneuvered the entire AI industry. Here’s why this changes everything: • X is valued at $33 billion • xAI is now worth a staggering $80 billion • The deal is an all-stock transaction, excluding $12 billion in X’s debt At first glance, it seems like Musk took a loss—after all, he originally paid $44 billion for Twitter. But this move isn’t about social media. It’s about something far more valuable: data. The Real Reason Musk Bought Twitter Back in 2022, people were confused. Why would the world’s richest man, known for building rockets and electric cars, want a struggling social media platform? Now, the answer is clear: Twitter (now X) was never just a social media company—it was a massive, real-time data engine. With 600 million active users generating a constant stream of conversations, opinions, and real-world events, X is a goldmine for training AI models. And that’s exactly what xAI needs to take on OpenAI, Anthropic, and Google. The Timing Is No Coincidence - Just a few months ago, xAI secured a $6 billion funding round at a $24 billion valuation. Now, after this acquisition, its valuation has skyrocketed to $80 billion—outpacing even OpenAI’s growth. Why does this matter? Most AI companies struggle to get high-quality, real-world data. Their models rely on stale, pre-existing datasets that don’t reflect real-time human behavior. But xAI now has something its competitors don’t: a live firehose of human interaction. This means: ✅ More human-like AI models ✅ A competitive edge in real-time applications ✅ The ability to train AI on the most up-to-date information available anywhere What Happens Next? This merger isn’t just about an AI assistant inside X. It’s the foundation for something much bigger. 1️⃣ AI-Driven Content & Conversations Expect smarter content recommendations that understand not just what you like, but why you like it. AI-generated insights, real-time fact-checking, and even automated dispute resolution could change how people engage online. 2️⃣ X Becomes More Than Social Media This could push X toward becoming a full-fledged “everything app”—integrating AI-powered tools for content creation, virtual assistants, and even education. 3️⃣ Regulatory Strategy at Play By structuring the deal as xAI acquiring X (instead of the other way around), Musk positions this as an AI-driven initiative rather than a social media consolidation—potentially avoiding regulatory roadblocks. The Bottom Line This isn’t just another tech merger. It’s a calculated move that positions xAI as a major player in AI, while using X’s data to supercharge its models. Musk isn’t just competing with OpenAI, Google, and Anthropic. He’s changing the game entirely.

OpenAI Introduces GPT-5-Codex, an AI Model Built Just for Coding

OpenAI has announced its newest model, GPT-5-Codex. The new model has been optimized for agentic coding in OpenAI’s suite of AI-powered software engineering tools, which is called Codex. This year, AI programs that can write and edit software have emerged as the most lucrative use case for AI, propelling multiple companies to huge revenue increases. These tools are being used both by professional developers to make their work more efficient, and by casual vibe coders, who lack the technical skill to create websites and apps. The Sam Altman-led company claims that by training this new AI model on real-world engineering tasks, it can outperform the default model. In a benchmark that compared that model and GPT-5-Codex’s ability to refactor code (essentially reorganizing and cleaning up code), GPT-5-Codex scored nearly 20 percent higher than the default model, which is simply called GPT-5. GPT-5-Codex is also said to be a strong independent worker. It can work autonomously on software for long stretches of time. According to a press release, OpenAI has seen the model “work independently for more than seven hours at a time on large, complex tasks, iterating on its implementation, fixing test failures, and ultimately delivering a successful implementation.” The new model could also help alleviate one of the most notable pain points of vibe coding: bad code. Many software developers have remarked that much of their time working with AI-assisted code editors is spent cleaning up the AI’s code, which isn’t always as thoughtfully written as a human expert’s would be. But OpenAI says that GPT-5-Codex has been “trained specifically for conducting code reviews and finding critical flaws.” In practice, the company says, this means GPT-5-Codex will review an entire codebase to identify flaws and autonomously test apps to find errors. OpenAI says that Codex currently handles “the vast majority” of proposed changes to code being written by OpenAI staffers, “catching hundreds of issues every day—often before a human review begins.” But even with its improved code review abilities, OpenAI still recommends using Codex as an additional reviewer; it says in a press release that it is “not a replacement for human reviews.” Unlike the normal version of GPT-5, GPT-5-Codex won’t be immediately available via API, and OpenAI recommends only using the model for coding tasks in Codex-supported environments. In addition, Codex is coming to mobile devices for the first time. Previously, to access Codex, you’d either need to use ChatGPT on a desktop computer or invoke Codex in an IDE (integrated development environment) like VSCode or Cursor. Now, Codex will be accessible in the ChatGPT iOS app, enabling easier coding on the go. Codex, and GPT-5-Codex, is available across all of ChatGPT’s paid tiers, with $20-per-month ChatGPT Plus members getting enough access to “cover a few focused coding sessions each week.” Meanwhile, $200-per-month ChatGPT Pro members will get enough to “support a full workweek across multiple projects.” Companies that pay for ChatGPT’s SMB-focused Business plan can purchase credits to give their developers more access to Codex, while larger companies with ChatGPT’s Enterprise plan get a shared credit pool. In OpenAI’s press release, engineers and tech leads at companies including Cisco, Duolingo, Ramp, Vanta, and Virgin Atlantic praised Codex’s utility, but it remains to be seen if GPT-5-Codex can help OpenAI take market share away from Anthropic, whose similar Claude Code product has proved very popular with professional and casual software developers. BY BEN SHERRY @BENLUCASSHERRY

Anthropic Says This AI Tool Can Now Create and Edit Documents

Anthropic’s Claude AI has been updated with the ability to create and edit files, including PDFs, Excel spreadsheets, Word documents, Google docs, and more. Anthropic made their announcement on their blog, explaining that the new features live on its consumer-facing platform, Claude.ai. Until now, the platform could analyze files, but couldn’t create or manipulate them. (Claude.ai is basically Anthropic’s version of ChatGPT.) In a video detailing how the new feature works, a user asks Claude to help them analyze revenue data for their small food truck fleet and package the findings in a Google doc. After the user uploads a few CSV files containing the data, Claude performs its analysis, creates a series of data visualizations, and puts it all together in a handy DOCX file that can either be downloaded or opened directly in Google Drive. “Whether you need a customer segmentation analysis, sales forecasting, or budget tracking,” Anthropic wrote in its blog, “Claude handles the technical work and produces the files you need.” To create files, Claude uses what Anthropic refers to as a “private computer environment,” in which the AI model can write code and run programs. This is similar to ChatGPT’s recently announced agent mode, which gives the AI platform access to a virtual browser that it can use to navigate the internet. These features, which involve giving an AI model access to additional tools, are referred to as agentic capabilities. The company advises starting “with straightforward tasks like data cleaning or simple reports,” and then working up to “complex projects like financial models once you’re comfortable with how Claude handles files.” Currently, when users ask Claude to create a document or spreadsheet, the model opens a window called an Artifact, which is essentially an interactive block of content. Prior to the release of these new features, if you were to ask for a document, Claude would create a document Artifact. If you asked for a spreadsheet, it would create an interactive Artifact. Now, instead of keeping those Artifacts contained within chats, users can download and use their AI-created files. Anthropic says that file creation is currently available for workplace-based Claude Team and Enterprise users, and Claude Max subscribers, who pay $200 per month to the company. Claude Plus users, who pay $20 per month, will get access to the feature “in the coming weeks.” BY BEN SHERRY @BENLUCASSHERRY

The Best AI Success Stories Are Sitting on Hard Drives and Have 1 User

I had coffee with my favorite CTO yesterday and he told me about his new AI app. It’s basically a CTO-in-a box. And it’s awesome. And he’s the only one using it. And it’s going to stay that way. Despite my trying to persuade him otherwise. One of the reasons there’s so little proof of the value of AI is that the best, most useful, most ingenious apps actually never leave the creator’s hard drive. In fact, once my friend pointed out what he was doing, I myself realized that most of what I’ve created with AI is available only to me on my hard drive, and moreover, that’s definitely where my best stuff is. In fact, it seems like most of the better “AI apps” aren’t even primarily AI, but AI being implemented, like my CTO friend implemented it, to unlock automation and unstructured data — and ultimately narrative output — in a way that couldn’t be done before. So why is this happening? The Genius of CTO-in-a-Box I’m probably overhyping this because he’s my buddy and he kindly listens to a lot of my BS before it gets to you folks, but my CTO friend’s CTO-in-a-box isn’t anything to eff with. He and I worked shoulder-to-shoulder for years, and together we developed some amazing little features, a few apps, and the tech backbone of a multimillion-dollar business. I say “we” but all I did was dream stuff up with him, vet it, and MVP it out, after which he and his brilliant team coded it. And they got it right the first time every time, and he usually added his own flair to surprise me with some technical trick no one would ever notice but made what we were doing 10 times better under the hood. He left that company not long after I did, and despite my trying to wrangle him into what I was doing, he took another job, to come in and do a technical turnaround on a private equity-purchased startup that had tons of potential but was stagnating. He hadn’t done anything like a turnaround before and I had just finished one. We have coffee every two weeks and so our conversations turned to the science of the turnaround. Then he disappeared for a month, and when we got back together, yesterday, he shocked the hell out of me. “Basically, what I did was take every bit of data, company data, sales data, all the code, all the documentation — they had a lot of ‘stuff’ [his air quotes] just sitting in directories and databases,” he told me. “I slammed it all into a vector database, wrote some code, integrated Claude Code to build some agents and totally write the front end, and now the LLM is like my personal assistant.” He’s underselling it. I know this because of the example he gave me. Builders Gonna Build “We had a sudden spike in resources, so I asked it what was going on, and it brought me to the right section of code that was the problem and hypothesized why, and I fixed it in 30 seconds,” he said. And then he made me jealous. “Oh, it also does all my weekly status reports and my standup agenda and all the reporting I have to do for the ELT and the board,” he continued. “I don’t let it send emails, but it’ll create the draft for me to review with the summary and a link to the report.” “Tell me you built it so anyone can use it,” I said. “Of course,” he responded. “I mean, not for all the outliers, but yeah you could start over and import new data, it knows what it’s getting and what to do with it.” “Tell me it’s self-perpetuating with new data it creates on its own,” I said, “like those email summaries and reports.” He just smiled. “Dude,” I said and threw my hands up. “It’s a CTO-in-a-box. Let me at it.” “No,” he laughed. “It’s staying on my hard drive.” “But you built it like a product.” “Because that’s how I roll.” Then he took a smug sip of his mocha whatever and I couldn’t help not being mad at him. Don’t Be So Quick to Write Off AI I say this as the guy who can’t stop writing off AI. Nah, I’ve been disparaging how we’ve been selling AI for years now, having been building it since 2010, and, in a nascent sense, as far back as 2000. But each time I’ve firebombed today’s AI hype in public, especially generative AI — because that’s the “AI” everyone is familiar with and what 95 percent of people are talking about when they say “AI” — I’ve prefaced my flaming with how amazing the technology actually can be when you know what you’re doing. In the hands of my CTO friend, amazing doesn’t even begin to describe what you can do. For the record, he’s on the uppermost subscription level of at least five different providers, a four-figure-a-month bill footed by his private equity overlords. And he’s aware that he will be squeezed soon. In fact, he said openly, “I got on the gravy train while the platforms are loss-leading.” They’ll price him out, and that’s another reason not to build a public product around it. He doesn’t know the true economics. Do What the CTOs Are Doing Of course, I asked my CTO friend to send me his documentation, because of course he documented it, and I’m building something around content and creators that could use its own CTO-in-a-box. And that got me thinking. Right now, all the coding I’ve done with the AI and the agents and such, it’s all sitting on my hard drive, and like my friend, I’ve built it like a product but I’m the only user in the credentials table. But unlike my friend, I built it like a product because I am indeed thinking of packaging it and selling it as a product down the road. If I could just stop writing for a while and get my brain on it for more than five minutes. Which, in today’s world, actually gets a lot of Claude coding done. It’s the peer review that takes time, if you get me. If I’ve got advice, it’s this. If you want to build something with AI, find the people who are doing amazing things on their hard drive — facing real challenges, solving real problems, and not just leveraging AI to jump on the gravy train. Buy them a mocha whatever and ask them what they’re doing and how they’re doing it. Because the more my CTO friend spoke, the more my vision was clouded by dollar signs. The problem is that for every story like his I hear 100 more stories about chatbot wrappers and unstructured data parsers being sold like they’re magic. Those aren’t being funded anymore, finally. That opens the door for people to wring real value and usage out of this AI nonsense. If you’re a fan of real value and usage, jump on my email list. I try to talk about that as much as possible, whether that’s AI or tech or something else. EXPERT OPINION BY JOE PROCOPIO, FOUNDER, JOEPROCOPIO.COM @JPROCO

Mark Cuban Has 2 Words for People Who Don’t Want to Learn AI

Skims founding partner and sometimes visiting Shark Tank Shark Emma Grede was never an AI skeptic, exactly. In 2023, she offered a cash bonus to her staff for finding creative ways to use AI in their work. But she herself was mostly just using ChatGPT as an occasional replacement for Google search. “I’m using AI like a 42-year-old woman,” she joked in a recent Fortune interview. Then she had former Shark Mark Cuban on her podcast. Turns out the billionaire founder and former Mavs owner has strong words — two, to be exact — for people like Grede who are dragging their feet on experimenting with AI. Talking to Cuban was enough to convince Grede to change her approach. She started Googling class on AI and downloading AI apps immediately. The episode “gave me a new urgency around how I use AI,” she told Fortune. “He gave me a kick.” It might be just the kick you need too. Not learning AI? Mark Cuban says “you’re f***ed” On her podcast, Grede didn’t ask Cuban about AI. She asked him about how to get started with a business idea. But the billionaire entrepreneur insisted that now, there’s no difference between going from idea to execution and utilizing AI. You need the latter to do the former fast and well. “The first thing you have to do is learn AI,” Cuban responded. “Whether it’s ChatGPT, Gemini, Perplexity, Claude, you’ve got to spend tons and tons and tons of time just learning how it works and how to ask it questions.” Noodling around with new tools and asking various AI models questions is how Cuban is spending his time at the moment. And he has no patience for founders and others in business who aren’t doing the same. “What do you say to someone who is like, ‘I don’t like AI. I don’t want any more technology in my life’?” Grede asked. Cuban’s answer was short, punchy, and profane: “You’re f***ed.” Is Mark Cuban right? Cuban went on to explain that the current moment is much like his early career at the dawn of the internet age. New, hugely disruptive technology is rolling out at an incredible rate. Those who don’t run to keep up are going to end up as roadkill. Saying you don’t want to use AI, he says, “is like people saying back in the day, I don’t want to use the PC. I don’t want to use the internet. I don’t need a cellphone, Wi-Fi.” Those businesses died. Is he right in making the comparison? He’s certainly correct that those around you are adopting AI at a rate equal to or greater than the rate at which the internet took off. Harvard researchers have compared recent data on AI usage to government data on the uptake of new technology at the turn of the millennium. They found more people are using AI more quickly these days than people started adopting the internet back then. “The usage rate [for AI] … is actually higher than both personal computers and the internet at the same stage in their product cycles,” the trio of researchers explained to The Harvard Gazette. No one can predict the future. And the breathlessness of some discussions of AI certainly suggest that the hype will exceed the reality in plenty of areas. We may yet witness an AI “trough of disillusionment” or even crash. But the numbers strongly suggest that Mark Cuban is on to something when he says that ignoring AI is just not a viable option. What happened to businesses that ignored the internet? “If you were to go back to 1984 and tell people, ‘Hey, there’s this new thing called the personal computer. I have a crystal ball. Twenty years from now, everybody’s going to have one of these and every single new technological development and every single new product is going to be using it as the base.’ Knowing that now, what would you do differently?” the Harvard researchers ask. “You could make billions and billions of dollars,” they add. According to their data, they say, “it sure looks like generative AI is going to be on that scale,” and “the spoils will go to people who can figure out how to harness it first and best.” How to get started with AI If you’re convinced, how do you start learning AI? Playing around with new tools and technologies as Cuban suggests is certainly a good first step. Elsewhere, Cuban — along with other tech icons like Tim Cook and Bill Gates — has outlined specific ways he’s using AI, which could give you additional ideas. Other AI experts have advice as well. Nvidia CEO Jensen Huang has talked on multiple occasions about how he’s personally experimenting with AI. OpenAI president Greg Brockman has offered advice on honing your AI prompting skills. No one knows exactly how the AI revolution will play out, or even the best way to start to prepare. But even the skeptics should probably heed Mark Cuban’s words and admit that AI is going to change the world. If you stick your head in the sand, you’re doomed. Better start experimenting today so you can be prepared however this thing plays out. EXPERT OPINION BY JESSICA STILLMAN @ENTRYLEVELREBEL

Is the AI Bubble Too Big to Fail?

On Wednesday, analysts bemoaned Nvidia’s lackluster Q2 earnings. The company posted a 56 percent gain in sales, its smallest in more than two years, despite the chipmaker’s positioning as one of the biggest winners of the AI boom. The company’s inability to live up to its expectations has reignited fears of an AI bubble on the precipice of rupture. Despite Silicon Valley throwing hundreds of billions of dollars into its most speculative gamble yet, the revolutionary promises, and more important, profits, of AI have yet to materialize. OpenAI is expected to lose money this year, even as its revenue exceeds a projected $20 billion. Meta’s CFO told investors, “We don’t expect that the genAI work is going to be a meaningful driver of revenue this year or next year,” despite the company dropping upwards of $70 billion on its AI investments this year. A recent MIT study found that U.S. companies have invested between $30 billion and $40 billion into generative AI tools but are seeing “zero return” from AI agents. Some fear that all of this could presage a collapse bigger than the dot-com bust of the early 2000s. As Apollo Global Management’s chief economist warned in a recent investor’s note, big tech firms are driving the market with valuations more bloated than they were in the 1990s. This would be scary for big tech companies—except many of them, according to several researchers who spoke to Inc., are already too big to fail, thanks to how closely the industry has become intertwined with our economy and government. The leading AI companies believe “the only way for this technology to exist is to be as big as possible, and the only way for it to get better is to throw more money at it,” says Catherine Bracy, CEO of the policy and research organization Tech Equity. That need for money and investment has spurred an industry lobbying blitz, pushing everyone from OpenAI CEO Sam Altman to VCs like Andreessen Horowitz into the halls of Congress over the past couple of years. Just earlier this week, The Wall Street Journal reported that Andreessen Horowitz and OpenAI are behind a nascent lobbying campaign through a super PAC network that’s already amassed $100 million to elect AI-friendly candidates. Those beltway relationships appear to be paying off. Currently, more than 30 states offer tax incentives for data center construction. But the booming growth of the industry has been enormously costly, largely owing to the vast amounts of energy needed to run large language models. The Trump administration’s AI Action Plan frames the industry’s growth as essential to “human flourishing” in the U.S. and the country’s continued geopolitical dominance. “We’re now locked into a particular version of the market and the future where all roads lead to big tech,” says Amba Kak, co-executive director of the AI Now Institute, which studies AI development and policy. Indeed, the success of major stock indexes—and perhaps your 401(k)—is resting on the continued growth of AI: Meta, Amazon, and the chipmakers Nvidia and Broadcom have accounted for 60 percent of the S&P 500’s returns this year. But ultimately, in the event of a market reckoning, it’s likely that the biggest companies would remain relatively unscathed. “AI is too big to fail in the United States, both because of how intertwined it has become with the government, and also because of how much AI investment is propping up the stock market and the entire economy,” says Daron Acemoglu, an economist at MIT. When the bubble pops, it’s likely going to be the smallest AI businesses, those riding the AI hype train with products based on existing LLMs, that’ll get wiped out in an eventual rupture. “Those little companies are not going to get bailed out,” he argues. Hardware companies like Nvidia or big tech firms, with diverse revenue streams, are likely to be better insulated from the potential fallout of the bubble popping. As Timnit Gebru, a former Google AI researcher and founder of the Distributed AI Research Institute, puts it, a chipmaker like Nvidia is essentially just selling shovels during a gold rush. “Shovels are still useful with or without the gold rush,” she says. BY SAM BLUM @SAMMBLUM

Why Google’s New AI Image Generator Could Give OpenAI a Run for Its Money

Google just dropped a major update for its AI image generation tech, enabling anyone to generate images with more accurate outcomes. In a blog post, Google revealed Gemini 2.5 Flash Image (also called nano-banana), its latest and greatest AI model for generating and editing images. Google says the new model gives users the ability to blend multiple images into a single image, maintain character consistency across multiple generations, and make more granular tweaks to specific parts of an image. One of the model’s new features is that ability to maintain character consistency, meaning that if you create a specific look for an AI-generated character, the character will maintain that look each time you generate a new image featuring them. “You can now place the same character into different environments,” Google wrote, “showcase a single product from multiple angles in new settings, or generate consistent brand assets, all while preserving the subject.” Gemini 2.5 Flash Image can also make more granular edits to images, like blurring a background, and changing the color of an item of clothing. Another major feature is the ability to fuse multiple images into a single image. Google says this could let people place an object into a room or to restyle an environment with a new color scheme or texture. To demonstrate, Google built a demo in which users can upload a picture of a room, upload images of products that they’d like to see in the room, and then drag the product image to the specific place where they want it to appear in the room. It’s not difficult to imagine people using this feature to see how a new appliance or piece of furniture will look in their home before committing to a purchase. Google also says that Gemini 2.5 Flash Image is particularly adept at sticking to visual templates, such as real estate listing cards, uniform employee badges, and trading cards. This kind of feature could also be used to create thumbnails for YouTube videos. Gemini 2.5 Flash actually debuted on website LMArena last week under the codename nano-banana. LMArena is a platform for evaluating an AI’s performance against other AIs, and big artificial intelligence companies often submit their new models to the site before publicly revealing them. Also of note is Gemini 2.5 Flash Image’s API price. According to Google, the model is priced at $30 per one million output tokens. In comparison, OpenAI’s image-generation API fees cost $40 per one million output tokens, making Google’s offering significantly cheaper. The new model can be used in the Gemini app and in Google AI Studio. BY BEN SHERRY @BENLUCASSHERRY

Mark Cuban Says Young People Should Learn This Crucial AI Skill

Legendary investor Mark Cuban has some advice for college students looking to break into the red-hot AI industry: become an AI integrator. During a livestreamed interview on TBPN (the Technology Business Programming Network), Cuban told hosts John Coogan and Jordi Hays that young people in college should learn everything they can about how to integrate AI within corporations, particularly within small to medium-size businesses. Cuban claimed that “every single company” needs professionals with AI implementation skills because there currently aren’t any intuitive ways for corporations to integrate AI into their work. “There are 33 million companies in this country,” Cuban said, and only a select few have dedicated AI budgets or keep AI experts on payroll. But these companies will still need to adapt for the AI era. Cuban likened this issue to how he started his career as an entrepreneur. “When I was 24,” Cuban said, “I was walking into companies who had never seen a PC before in their lives and explaining to them the value.” Cuban said he would meet with the owners of these companies and present them with customized plans that used computers to fulfill their specific business needs. “This is where kids coming out of college are really gonna have a unique opportunity,” said Cuban. Students spending their senior years “learning the difference between Sora and Veo [two popular AI video-generation tools],” or learning how to customize an AI model, will be able to walk into any business and identify clear areas where AI implementation would meaningfully impact their operations. TBPN co-host Coogan agreed with Cuban’s take, and added that he and Hays hired two interns this summer “because they just built products. Instead of saying, ‘Here’s what I can do,’ they just showed us. They took a day and just built something.” Meanwhile, trying to work at one of the big tech companies with a computer science degree is “probably not the right way to go,” says Cuban. Instead, he says, “go into any other company that has no idea about AI but needs it to compete. There’ll be more jobs than people for a long, long time.” BY BEN SHERRY @BENLUCASSHERRY

Why Companies Are Offering Young Workers With AI Skills 6-Figure Salaries

While the entry-level job market on the whole is still hurting, recent graduates who possess AI skills are finding sizable demand for their services. And starting salaries can reach up to hundreds of thousands of dollars per year. A new report by hiring firm Burtch Works finds that the starting salary of AI-skilled workers with zero to three years’ of work experience now averages $131,139—a 12 percent jump from the year prior. Data scientists with the same level of limited experience are averaging $109,545 a year. Compensation levels vary slightly by industry, the report found, but the mean salary for all covered industries with zero to three years’ experience was in the six-figure range. Health care/pharma is currently paying the most to AI-fluent workers, with a mean salary of $123,804. Consulting and tech are at a virtual tie at the bottom of the list, at roughly $104,500. “AI professionals still command a 9 to 13 percent cash premium over data scientists. The gap is widest where scarce [generative AI] expertise adds the most value,” Burtch Works wrote in its report. “If you’re seeking a job in AI and data science, quantify your genAI successes to demonstrate your skills in action [and] reference market data during salary negotiations.” The current demand for AI knowledge is unprecedented. Job search site Indeed earlier this year said the number of postings for generative AI-related jobs had tripled between January 2024 and January 2025. That followed a 75X increase from April 2022 to April 2024. New college graduates are not just digital natives, they’re often AI natives, having grown up with early versions of the technology and learning as it has evolved. That can make them a more natural fit for AI-themed jobs than more experienced workers, who may be more resistant to adopting the technology, in part because of fears it will make their jobs irrelevant. That has led to a bidding war for AI-savvy graduates. OpenAI is reportedly offering a base salary of $167,000, with more than $80,000 in stock options, to entry-level workers, bringing its average compensation to $248,000, according to Levels.fyi, a compensation-data provider. Scale AI reportedly has a total starting compensation package average of $185,000, and Databricks is offering $235,000. Within a couple of years, those numbers nearly double, per the Levels.fyi data. Several dozen users of Levels.fyi have claimed to have received offers of over $1 million from AI companies, with some of them having less than a decade of experience. At the same time, the number of AI job openings has soared. A study released in January by job tracking firm LinkUp and the University of Maryland found that from the beginning of 2018 to the end of 2024, the number of overall job openings was down 17 percent and total IT job openings fell by 27 percent. AI job openings, however, saw a 68 percent increase. Demand for AI skills has become so intense that many hiring managers say they would consider bringing aboard an inexperienced worker with AI expertise versus a more experienced employee. And 66 percent of those managers said they wouldn’t hire someone who lacked AI skills, according to the 2024 Annual Work Trend Index by Microsoft and LinkedIn. BY CHRIS MORRIS @MORRISATLARGE