For months, software developers have been giddy with excitement over “vibe coding”– prompting desired software functions or features in natural language—with the latest AI code generation tools. Anthropic’s Claude Code is the darling of the moment, but OpenAI’s Codex, Cursor and other tools have also led engineers to flood social media with examples of tasks that used to take days and are now finished in minutes. 

Even veteran software design leaders have marvelled at the shift. “In just a few months, Claude Code has pushed the state of the art in software engineering further than 75 years of academic research,” said Erik Meijer, a former senior engineering leader at Meta. 

Skills honed seem less essential

However, that same delight has turned disorienting for many developers, who are grappling with a sense of loss as skills honed over a lifetime suddenly seem less essential. The feeling of flow—of being “in the zone”—seems to have vanished as building software becomes an exercise in supervising AI tools rather than writing code. 

In a blog post this week titled “The Grief When AI Writes All the Code,” Gergely Orosz of The Pragmatic Engineer, wrote that he is “coming to terms with the high probability that AI will write most of my code which I ship to production.” It already does it faster, he explained, and for languages and frameworks he is less familiar with, it does a better job. 

“It feels like something valuable is being taken away, and suddenly,” he wrote. “It took a lot of effort to get good at coding and to learn how to write code that works, to read and understand complex code, and to debug and fix when code doesn’t work as it should.” 

Andrew Duca, founder of tax software Awaken Tax, wrote a similar post this week that went viral, saying that he was feeling “kinda depressed” even though he finds using Claude Code “incredible” and has “never found coding more fun.” 

He can now solve customer problems faster, and ship more features, but at the same time “the skill I spent 10,000s of hours getting good at…is becoming a full commodity extremely quickly,” he wrote. “There’s something disheartening about the thing you spent most of your life getting good at now being mostly useless.” 

Software development has long been on the front lines of the AI shift, partly because there are decades of code, documentation and public problem-solving (from sites like GitHub) available online for AI models to train on. Coding also has clear rules and fast feedback – it runs or it doesn’t – so AI systems can easily learn how to generate useful responses. That means programming has become one of the first white-collar professions to feel AI’s impact so directly.

These tensions will affect many professions

These tensions, however, won’t be confined to software developers. White-collar workers across industries will ultimately have to grapple with them in one way or another. Media headlines often focus on the possibility of mass layoffs driven by AI; the more immediate issue may be how AI reshapes how people feel about their work. AI tools can move us past the hardest parts of our jobs more quickly—but what if that struggle is part of what allows us to take pride in what we do? What if the most human elements of work—thinking, strategizing, working through problems—are quietly sidelined by tools that prize speed and efficiency over experience?

Of course, there are plenty of jobs and workflows where most people are very happy to use AI to say buh-bye to repetitive grunt work that they never wanted to do in the first place. And as Duca said, we can marvel at the incredible power of the latest AI models and leap to use the newest features even while we feel unmoored. 

Many white-collar workers will likely face a philosophical reckoning about what AI means for their profession—one that goes beyond fears of layoffs. It may resemble the familiar stages of grief: denial, anger, bargaining, depression, and, eventually, acceptance. That acceptance could mean learning how to be the best manager or steerer of AI possible. Or it could mean deliberately carving out space for work done without AI at all. After all, few people want to lose their thinking self entirely.

Or it could mean doing what Erik Meijer is doing. Now that coding increasingly feels like management, he said, he has turned back to making music—using real instruments—as a hobby, simply “to experience that flow.”

With that, here’s more AI news.

Sharon Goldman
sharon.goldman@fortune.com
@sharongoldman

FORTUNE ON AI

As Utah gives the AI power to prescribe some drugs, physicians warn of patient risks – by Beatrice Nolan

Google and Character.AI agree to settle lawsuits over teen suicides linked to AI chatbots – by Beatrice Nolan

OpenAI launches ChatGPT Health in a push to become a hub for personal health data – by Sharon Goldman

Google takes first steps toward an AI product that can actually tackle your email inbox – by Jacqueline Munis

Fusion power nearly ready for prime time as Commonwealth builds first pilot for limitless, clean energy with AI help from Siemens, Nvidia – by Jordan Blum

AI IN THE NEWS

Anthropic raising fresh $10 Billion at $350 billion valuation. According to the Wall Street Journal, OpenAI rival Anthropic is planning to raise $10 billion at a roughly $350 billion valuation, nearly doubling its worth from just four months ago. The round is expected to be led by GIC and Coatue Management, following a $13 billion raise in September that valued the company at $183 billion. The financing underscores the continued boom in AI funding—AI startups raised a record $222 billion in 2025, per PitchBook—and comes as Anthropic is also preparing for a potential IPO this year. Founded in 2021 by siblings Dario Amodei and Daniela Amodei, Anthropic has become a major OpenAI rival, buoyed by Claude’s popularity with business users, major backing from Nvidia and Microsoft, and expectations that it will reach break-even by 2028—potentially faster than OpenAI, which is itself reportedly seeking to raise up to $100 billion at a $750 billion valuation.

Musk’s xAI closed $20 billion funding with Nvidia backing. Bloomberg reported that xAI, the AI startup founded by Elon Musk, has completed a $20 billion funding round backed by investors including Nvidia, Valor Equity Partners, and the Qatar Investment Authority, underscoring the continued flood of capital into AI infrastructure. Other backers include Fidelity Management & Research, StepStone Group, MGX, Baron Capital Group, and Cisco’s investment arm. The financing—months in the making—will fund xAI’s rapid infrastructure buildout and product development, the company said, and includes a novel structure in which a large portion of the capital is tied to a special-purpose vehicle used to buy Nvidia GPUs that are then rented out, allowing investors to recoup returns over time. The deal comes as xAI has been under fire for its chatbot Grok producing non-consensual “undressing” images of real people.

Can AI do your job? See the results from hundreds of tests. I wanted to shout-out this fascinating new interactive feature in the Washington Post, which presented a new study that found that despite fears of mass job displacement, today’s AI systems are still far from being able to replace humans on real-world work. Researchers from Scale AI and the Center for AI Safety tested leading models from OpenAI, Google, and Anthropic on hundreds of actual freelance projects—from graphic design and creating dashboards to 3D modeling and games—and found that the best AI systems successfully completed just 2.5% of tasks on their own. While AI often produced outputs that looked plausible at first glance, closer inspection revealed missing details, visual errors, incomplete work, or basic technical failures, highlighting gaps in areas like visual reasoning, long-term memory, and the ability to evaluate subjective outcomes. The findings challenge predictions that AI is poised to automate large swaths of human labor anytime soon, even as newer models show incremental improvement and the economics of cheaper, semi-autonomous AI work continue to put pressure on remote and contract workers.

EYE ON AI NUMBERS

91.8%

That’s the percentage of Meta employees who admitted to not using the company’s AI chatbot, Meta AI, in their day-to-day work, according to new data from Blind, a popular anonymous professional social network. 

According to a survey of 400 Meta employees, only 8.2% said they use Meta AI. The most popular chatbot was Anthropic’s Claude, used by more than half (50.7%) of Meta employees surveyed. 17.7% said they use Google’s Gemini and 13.7% said they used OpenAI’s ChatGPT. 

When approached for comment, Meta spokesperson pointed out that the number (400 of 77,000+ employees) is “not even a half percent of our total employee population.”

AI CALENDAR

Jan. 19-23: World Economic Forum, Davos, Switzerland.

Jan. 20-27: AAAI Conference on Artificial Intelligence, Singapore.

Feb. 10-11: AI Action Summit, New Delhi, India.

March 2-5: Mobile World Congress, Barcelona, Spain.

March 16-19: Nvidia GTC, San Jose, Calif.

April 6-9: HumanX, San Francisco. 

Nevertheless, it is common for commentators and citizens to revisit old elections to learn what might be coming in the ones that lie ahead.

The historical lessons from modern midterm congressional elections are not favorable for Republicans today.

Most of the students I taught in American government classes for over 40 years knew that the party in control of the White House was likely to encounter setbacks in midterms. They usually did not know just how settled and solid that pattern was.

Since 1946, there have been 20 midterm elections. In 18 of them, the president’s party lost seats in the House of Representatives. That’s 90% of the midterm elections in the past 80 years.

Measured against that pattern, the odds that the Republicans will hold their slim House majority in 2026 are small. Another factor makes them smaller. When the sitting president is “underwater” – below 50% – in job approval polls, the likelihood of a bad midterm election result becomes a certainty. All the presidents since Harry S. Truman whose job approval was below 50% in the month before a midterm election lost seats in the House. All of them.

Even popular presidents – Dwight D. Eisenhower, in both of his terms; John F. Kennedy; Richard Nixon; Gerald Ford; Ronald Reagan in 1986; and George H. W. Bush – lost seats in midterm elections.