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Engineers buck against ‘vibe-coding’ label, saying responsibility still lies with the humans behind the code

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One of the hottest markets in the artificial intelligence industry is selling chatbots that write computer code.

Some call it “vibe-coding” because it encourages an AI coding assistant to do the grunt work as human software developers work through big ideas. Others dislike that term. But there’s no question that these tools are transforming the job experience for many tech workers amid an intense rivalry between leading AI companies to make the best one.

“The essence of it is you’re no longer in the nitty-gritty syntax,” said Cat Wu, project manager of Anthropic’s Claude Code. “You’re not looking at every single line of code. You’re more trying to communicate this higher-level goal of what you want to accomplish.”

Wu added, however, that ”vibe-coding” is not a term she uses. “We definitely want to make it very clear that the responsibility, at the end of the day, is in the hands of the engineers.”

Anthropic launched the latest version of its flagship Claude chatbot on Monday, boasting that Claude Sonnet 4.5 will be the “world’s best” for coding and other complex tasks.

Large language models behind generative AI chatbots like Claude, ChatGPT and Google’s Gemini are capable of many things, from homework help to organizing meal plans, but the “top use case” for most businesses has been in coding and software engineering, said Gartner analyst Philip Walsh.

“That is often the first thing large organizations go after,” Walsh said. “I think there’s broad recognition among these AI model providers that coding is really where they’re getting the most traction.”

And while Walsh said Anthropic’s products are a favorite for software developers, it is hardly the only player in a rapidly growing and consolidating market.

San Francisco and the surrounding Bay Area remain the center of the battle to make the best AI coder, home not just to fierce rivals OpenAI and Anthropic but startups like Anysphere, Cognition and Harness, as well as Microsoft-owned GitHub.

“This is the most competitive space in the industry right now,” said Windsurf CEO Jeff Wang, speaking by video call from the startup’s office in Mountain View, California.

Windsurf’s coding assistant launched less than a year ago, but as its popularity grew, hitting 200,000 users in its first two months, it quickly found itself at the center of a bidding war between tech giants. OpenAI sought to acquire it. Then, Google scooped up Windsurf’s founders and research team, leaving a shell of a company that another AI coding startup, Cognition, acquired in July.

“It’s been a really volatile time at Windsurf,” Wang told employees in a July email as he announced the merger with Cognition, maker of the AI coding assistant Devin. Two months later, the two companies’ integration is “going really well,” Wang told The Associated Press from a conference room called New Kelp City, named for a fictional setting in SpongeBob SquarePants.

Some AI coding assistants automatically finish the code that human programmers are writing, much like the “autocorrect” features that suggest the next lines of an email or text. More advanced tools known as AI agents are given more autonomy to access computer systems and do the work themselves.

Anthropic said its new Claude Sonnet 4.5, on a test before its public release Monday, was able to code autonomously for more than 30 hours on a project for London-based startup iGent.

Anthropic’s first coding assistant was developed largely by accident when the company’s Boris Cherny built an internal toy project and started using it to accelerate his own work. Then the rest of his team adopted it.

“Over time, we realized that it was just virally spreading within Anthropic,” Wu said.

Anthropic, in a consumer usage report earlier this month, said coding is the top use for Claude, with about 39% of its users saying they use the chatbot for coding.

OpenAI, by contrast, says writing is the most common work task for ChatGPT, with coding and self-expression as more “niche” activities on the platform. Even so, OpenAI has sought to catch up, introducing in September a new GPT-5-Codex that it says can work for longer on complex coding tasks.

Among the most coveted customers for big AI model developers are coding startups like Anysphere, maker of the popular coding tool Cursor, which relies heavily on Anthropic’s Claude and recently cemented a partnership with OpenAI.

It was Cursor’s Composer, combined with Anthropic’s Claude Sonnet, that prominent AI researcher Andrej Karpathy was playing with when he coined the phrase “vibe-coding” in February.

“There’s a new kind of coding I call ‘vibe coding’, where you fully give in to the vibes, embrace exponentials, and forget that the code even exists,” he wrote on X.

It was “getting too good,” he said, so much so that he could speak his instructions and “barely even touch the keyboard” and use it for throwaway weekend projects.

“It’s not really coding – I just see stuff, say stuff, run stuff, and copy-paste stuff, and it mostly works.”

Anthropic shipped Claude Code a few weeks later.

Some platforms, like Sweden-based Lovable, cater to vibe-coders with an approach that encourages anyone to “create apps and websites by chatting with AI.” But most tools are designed for professionals with programming expertise.

The phenomenon has raised fears of job loss in software careers, fueled by comments from tech CEOs who say AI is speeding up software development and making their teams more efficient.

Walsh said Gartner’s position is that AI will not replace software engineers and will actually require more.

“There’s so much software that isn’t created today because we can’t prioritize it,” Walsh said. “So it’s going to drive demand for more software creation, and that’s going to drive demand for highly skilled software engineers who can do it.”

Economists, however, are also beginning to worry that AI is taking jobs that would otherwise have gone young or entry-level workers. In a report last month, researchers at Stanford University found “substantial declines in employment for early-career workers’’ — ages 22-25 — in fields most exposed to AI.

Stanford researchers also found that AI tools by 2024 were able to solve about 72% of coding problems, up from just over 4% a year earlier. It’s likely to have grown even higher since then.

Karpathy didn’t respond to requests for comment. But the idea that non-technical people in an organization can “vibe-code” business-ready software is a misunderstanding of what Karpathy meant when he came up with the term, Walsh said.

“That’s simply not happening. The quality is not there. The robustness is not there. The scalability and security of the code is not there,” Walsh said. “These tools reward highly skilled technical professionals who already know what ‘good’ looks like.”

Wu said she’s told her younger sister, who’s still in college, that software engineering is still a great career and worth studying.

“When I talk with her about this, I tell her AI will make you a lot faster, but it’s still really important to understand the building blocks because the AI doesn’t always make the right decisions,” Wu said. “A lot of times the human intuition is really important.”



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Leaders at Davos are obsessing over how to use AI at scale

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  • In today’s CEO Daily: Fortune‘s AI editor Jeremy Kahn reports on the AI buzz at Davos
  • The big story: SCOTUS could upend Trump’s leverage to acquire Greenland.
  • The markets: Jolted by Trump’s renewed tariff threats.
  • Plus: All the news and watercooler chat from Fortune.

Good morning. I’m on the ground in Davos, Switzerland, for this year’s World Economic Forum. As Diane wrote yesterday, U.S. President Donald Trump’s arrival later this week along with a large delegation of U.S. officials eclipses pretty much every other discussion at Davos this year. But, when people here aren’t talking about Trump, they are talking about AI.

At Davos last year, the hype around AI agents was pierced by the shock of DeepSeek’s R1 model, which was released during the conference. We’ll see if a similar bit of news upends the AI narrative again this year. (There are rumors that DeepSeek is planning to drop another model.) But, barring that, business leaders seem to be less wowed by the hype around AI this year and more concerned with the nitty-gritty of how to implement the technology successfully at scale.

On Monday, Srini Tallapragada, Salesforce’s chief engineering and customer success officer, told me the company is using ‘forward deployed engineers’ to tighten feedback loops between customers and product teams. Salesforce is also offering pre-built agents, workflows, and playbooks to help customers re-engineer their businesses—and avoid getting stuck in “pilot purgatory.”

Meanwhile, at a side event in Davos called A Compass for Europe, that focused on how to restore the continent’s flagging competitiveness, AI was front-and-center. Christina Kosmowski, the CEO of LogicMonitor, told the assembled CEOs that to achieve AI success at scale, companies should take a “top down” approach, with the CEO and leadership identifying the highest value use cases and driving the whole organization to align around achieving them. Neeti Mehta Shukla, the cofounder and chief impact officer at Automation Anywhere, said it was critical to move beyond measuring automation’s impact only through the lens of labor savings. She gave specific customer examples where uplifting data quality, improving customer satisfaction, or moving more workers to new tasks, were better metrics than simply looking at cost per unit output. Finally, Lila Tretikov, head of AI strategy at NEA, said Europe has enough talent and funding to build world-beating AI companies—what it lacks is ambition and willingness to take big bets.

Later, I met with Bastian Nominacher, co-founder and co-CEO of process analytics software platform Celonis. He echoed some of these points, telling me that to achieve ROI with AI generally required three things: strong leadership commitment, the establishment of a center of excellence within the business (this led to an 8x higher return than for companies that didn’t do this!), and finally having enough live data connected to the AI platform.

For further AI insights from Davos, check out Fortune’s Eye on AI newsletter. Meanwhile, Fortune is hosting a number of events in Davos throughout the week. View that lineup here. And my colleagues will be providing more reporting from Davos to CEO Daily and fortune.com throughout the week.—Jeremy Kahn

Contact CEO Daily via Diane Brady at diane.brady@fortune.com

This is the web version of CEO Daily, a newsletter of must-read global insights from CEOs and industry leaders. Sign up to get it delivered free to your inbox.



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Stock market today: Dow futures tumble 400 points on Trump’s tariffs over Greenland, Nobel prize

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U.S. stock futures dropped late Monday after global equities sold off as President Donald Trump launches a trade war against NATO allies over his Greenland ambitions.

Futures tied to the Dow Jones industrial average sank 401 points, or 0.81%. S&P 500 futures were down 0.91%, and Nasdaq futures sank 1.13%. 

Markets in the U.S. were closed in observance of the Martin Luther King Jr. Day holiday. Earlier, the dollar dropped as the safe haven status of U.S. assets was in doubt, while stocks in Europe and Asia largely retreated.

On Saturday, Trump said Denmark, Norway, Sweden, France, Germany, the United Kingdom, the Netherlands, and Finland will be hit with a 10% tariff starting on Feb. 1 that will rise to 25% on June 1, until a “Deal is reached for the Complete and Total purchase of Greenland.”

The announcement came after those countries sent troops to Greenland last week, ostensibly for training purposes, at the request of Denmark. But late Sunday, a message from Trump to European officials emerged that linked his insistence on taking over Greenland to his failure to be award the Nobel Peace Prize.

The geopolitical impact of Trump’s new tariffs against Europe could jeopardize the trans-Atlantic alliance and threaten Ukraine’s defense against Russia.

But Wall Street analysts were more optimistic on the near-term risk to financial markets, seeing Trump’s move as a negotiating tactic meant to extract concessions.

Michael Brown, senior research strategist at Pepperstone, described the gambit as “escalate to de-escalate” and pointed out that the timing of his tariff announcement ahead of his appearance at the Davos World Economic Forum this week is likely not a coincidence.

“I’ll leave others to question the merits of that approach, and potential longer-run geopolitical fallout from it, but for markets such a scenario likely means some near-term choppiness as headline noise becomes deafening, before a relief rally in due course when another ‘TACO’ moment arrives,” he said in a note on Monday, referring to the “Trump always chickens out” trade.

Similarly, Jonas Goltermann, deputy chief markets economist at Capital Economics, also said “cooler heads will prevail” and downplayed the odds that markets are headed for a repeat of last year’s tariff chaos.

In a note Monday, he said investors have learned to be skeptical about all of Trump’s threats, adding that the U.S. economy remains healthy and markets retain key risk buffers.

“Given their deep economic and financial ties, both the US and Europe have the ability to impose significant pain on each other, but only at great cost to themselves,” Goltermann added. “As such, the more likely outcome, in our view, is that both sides recognize that a major escalation would be a lose-lose proposition, and that compromise eventually prevails. That would be in line with the pattern around most previous Trump-driven diplomatic dramas.”



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Goldman investment banking co-head Kim Posnett on the year ahead, from an IPO ‘mega-cycle’ to another big year for M&A to AI’s ‘horizontal disruption’

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Ahead of the World Economic Forum‘s Annual Meeting in Davos, Switzerland, Fortune connected with Goldman Sachs’ global co-head of investment banking, Kim Posnett, for her outlook on the most urgent issues in business as 2026 gathers steam.

A Fortune Most Powerful Woman, Posnett is one of the bank’s top dealmakers, also serving as vice chair of the Firmwide Client Franchise Committee and is a member of the Management Committee. She was previously the global head of the Technology, Media and Telecommunications, among several other executive roles, including Head of Investment Banking Services and OneGS. She talked to Fortune about how she sees the current business environment and the most significant developments in 2026, in terms of AI, the IPO market and M&A activity. Goldman has been the No. 1 M&A advisory globally for the last 20 years, including in 2025 — and Posnett has been one of the star contributors, advising companies including Amazon, Uber, eBay, Etsy, and X.

  • Heading into Davos, how would you describe the current environment?  

As the global business community converges at Davos, we are seeing powerful catalysts driving M&A and capital markets activity. The foundational drivers that accelerated business activity in the second half of 2025 have continued to improve and remain strong heading into 2026. A constructive macro backdrop — including AI serving as a growth catalyst across sectors and geographies — is fueling CEO and board confidence, and our clients are looking to drive strategic and financing activity focused on scale, growth and innovation. As AI moves from theoretical catalyst to an industrial driver, it is creating a new set of priorities for the boardroom that are top of mind for every client we serve heading into 2026.

  • What were the most significant AI developments in 2025, and what should we expect in 2026?

2025 was a breakout year for AI where we exited the era of AI experimentation and entered the era of AI industrialization. We witnessed major technical and structural breakthroughs across models, agents, infrastructure and governance. It was only a year ago, in January 2025, when DeepSeek launched its DeepSeek-R1 reasoning model challenging the “moats” of closed-source models by proving that world-class reasoning could be achieved with fully open-source models and radical cost efficiency. That same month, Stargate – a historic $500 billion public-private joint venture including OpenAI, SoftBank and Oracle – signaled the start of the “gigawatt era” of AI infrastructure. Just two months later in March 2025, xAI’s acquisition of X signaled a new strategy where social platforms could function as massive real-time data engines for model training. By year end, we saw massive, near-simultaneous escalation in model capabilities with the launches of OpenAI’s GPT-5.1 Pro, Google’s Gemini 3, and Anthropic’s Claude 4.5, all improving deep thinking and reasoning, pushing the boundaries of multimodality, and setting the standard for autonomous agentic workflows. 

In the enterprise, the conversation has matured from “What is AI?” just a few years ago to “How fast can we deploy?” We have moved past the pilot phase into a period of deep structural transformation. For companies around the world, AI is fundamentally reshaping how work gets done. AI is no longer just a feature; it is the foundation of a new kind of productivity and operating leverage. Forward-leaning companies are no longer just using AI for automation; they are building agentic workflows that act as a force multiplier for their most valuable asset: human capital. We are starting to see the first real, measurable returns on investment as firms move from ‘AI-assisted’ tasks to ‘AI-led’ processes, fundamentally shifting the cost and speed of execution across organizations. 

Of course, all this progress is not without regulatory and policy complexities. As AI reaches consumer, enterprise and sovereign scale, we are seeing a divergence in global policy that boards must navigate with care. In the United States, recent Executive Orders — such as the January 2025 ‘Removing Barriers’ order and the subsequent ‘Genesis Mission’ — have signaled a decisive shift toward prioritizing American AI dominance by rolling back prior reporting requirements and accelerating infrastructure buildouts. Contrast this with the European Union, where the EU AI Act is now in full effect, imposing strict guardrails on ‘high-risk’ systems and general-purpose models. Meanwhile, the UK has adopted a “pro-innovation” hybrid model: on the one hand, promoting “safety as a service”, while also investing billions into national compute and ‘AI Growth Zones’ to bridge the gap between innovation and public trust. For our clients, the challenge is no longer just regulatory compliance; it is strategic planning and arbitrage – deciding where to build, where to deploy, who to partner with, what to buy and how to maintain a global edge across a fragmented regulatory landscape.

As we enter 2026, the pace of innovation isn’t just accelerating; it is forcing a total rethink of business processes and capital allocation for every global enterprise. 

  • Given the expectation and anticipation for IPOs this year, what is your outlook for the market and how will it be characterized?

We are entering an IPO “mega-cycle” that we expect will be defined by unprecedented deal volume and IPO sizes. Unlike the dot-com wave of the late 1990s, which saw hundreds of small-cap listings, or even the 2020-2021 surge driven by a significant number of billion-dollar IPOs, this next IPO cycle will have greater volume and the largest deals the market has ever seen. It will be characterized by the public debut of institutionally mature titans, as well as totally disruptive, fast moving and capital consumptive innovators. Over the last decade, some companies have stayed private longer and raised unprecedented amounts of private capital, allowing a cohort of businesses to reach valuations and operational scale previously unseen in the private markets. We are no longer talking about “unicorns” — we are talking about global companies with the gravity and scale of Fortune 500 incumbents at the time they go public.  For investors, the reopening of the IPO window will enable an opportunity to invest in the most transformative and fastest growing companies in the world and a generational re-weighting of the public indices. 

In 2018, the five largest public tech companies were collectively valued at $3.3 trillion, led by Apple at ~$1 trillion. Today, the five largest public tech companies are valued at $18.3 trillion, more than five and half times larger.  Even more significant, the 10 largest private tech companies in 2018 were valued at $300 billion. Today, the 10 largest private tech companies are valued at $3 trillion, more than 10 times larger. These are iconic, generational companies with unprecedented private market caps some of which have unprecedented capital needs which should lead to an unprecedented IPO market. 

Each of these companies will have their own objectives on IPO timing, size and structure which will influence if, how and when they come to the market, but the potential across the board is significant. During the last IPO wave, Goldman Sachs was at the center of IPO innovation by leading the first direct listings and auction IPOs, and we expect more innovation with this upcoming wave. The current confluence of a constructive macro backdrop and groundbreaking technological advancements is doing more than just reopening the window; it is creating a generational opportunity for investors to participate in the companies that will define the next century of global business.

  • M&A activity exploded in 2025, are the markers there for another boom year?

As we enter 2026, the global M&A market has transitioned from a year of recovery ($5.1 trillion of M&A volume in 2025, up 44% YoY) to one that is bold and strategic. While the second half of 2025 was defined by a “thawing” — driven by a constructive regulatory environment, fed easing cycle and normalizing valuations — the year ahead will be defined by ambition. 

We have entered an era of broad, bold and ambitious strategic dealmaking: transformative, high-conviction transactions where industry leaders are no longer just consolidating for scale, but also moving aggressively to acquire the strategic assets, AI capabilities and digital infrastructure that will define the next decade. CEO and board confidence have reached a multi-year high, underpinned by the realization that in an AI-industrialized economy, standing still is the greatest risk of all. The quality and pace of strategic discussions that we are having with our clients signals that the world’s most influential companies — across sectors and regions — are ready to deploy their balance sheets and public currencies to redraw the competitive map. 

AI is no longer an isolated tech trend; it is a horizontal disrupter, broadening the appetite for strategic M&A across every sector of the economy. While the dialogue in boardrooms has moved from theoretical ‘AI pilots’ to large-scale capital deployment, the speed of technology is currently outpacing traditional governance frameworks. Boards and management teams are being asked to make multi-billion dollar, high-stakes decisions in a landscape where historical benchmarks often no longer apply. In this environment, M&A has become a tool for strategic leapfrogging — allowing companies to move both defensively to protect their core and offensively to secure the critical infrastructure and talent needed for non-linear growth. Success in 2026 will be defined by strategic conviction: the ability to turn this unprecedented complexity into a clear, actionable strategy and competitive advantage.

As AI continues to reshape corporate M&A strategy, we are also seeing financial sponsors return to the center of the M&A stage. Sponsor M&A activity accelerated sharply in 2025 — with M&A volumes surging over 50% as the bid-ask spread between buyers and sellers started to narrow, financing markets became more constructive and innovative deal structures enabled private equity firms to pursue larger, more complex transactions. With $1 trillion of global sponsor dry powder and over $4 trillion of unmonetized sponsor portfolio companies, the pressure for capital return to LPs has continued to escalate. Financial sponsors are entering 2026 with a dual-focus: executing take-privates and strategic carveouts to deploy fresh capital, while simultaneously utilizing reopened monetization paths – from IPOs to secondary sales to strategic sales — to satisfy demand for liquidity. With monetization paths reopening and valuation gaps narrowing, sponsors are entering 2026 with greater flexibility, reinforced by a healthier macroeconomic backdrop and improving liquidity conditions. 

This Q&A is based on an email conversation with Kim Posnett. This piece has been edited for length and clarity.



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