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If one thing became clear at the HumanX conference in San Francisco this week, where 6,500 executives, founders and investors gathered to talk about artificial intelligence, it’s that OpenAI no longer dominates the conversation in their industry. For now, at least, that distinction belongs to Anthropic.
Anthropic’s viral coding agent, Claude Code, was the tool on everyone’s lips, even as many attendees acknowledged that OpenAI, Cursor and Google are offering strong alternatives.
Despite its spat with the Pentagon that went public last month and quickly made its way to the courtroom, Anthropic has only gained momentum. The Department of Defense blacklisted Claude, but after opposing rulings in two courts, Anthropic can keep working with other federal agencies while the cases play out.
Anthropic’s early strength in the enterprise has positioned it to benefit from the soaring popularity of AI coding agents, which are used to generate, edit and review code. So while OpenAI kicked off the generative AI boom with the launch of ChatGPT in 2022, Anthropic may be best set up to win contracts from the biggest spenders.
CNBC spoke with 19 executives and investors at HumanX, some of whom asked not to be named in order to speak freely. Here are the top three takeaways.
Claude has ‘become a religion’
Anthropic was founded in 2021 by a group of researchers and executives who defected from OpenAI. The startup is valued at $380 billion, making it one of the most valuable private companies in the world.
Claude Code launched to the general public in May 2025, and as of February was generating more than $2.5 billion in annualized revenue. Arvind Jain, CEO of enterprise AI company Glean, said Claude Code has inspired “Claude Mania,” which is putting pressure on business leaders to deploy it.
“It has become a religion, that’s the level of that mania,” Jain said in an interview. “Everybody, if you go and ask them today, ‘Hey, if I gave you one AI tool, what tool would you want?’ The answer would be Claude.”
On Tuesday, Anthropic announced a new AI model, Claude Mythos Preview, with advanced cybersecurity capabilities thanks to its strong coding and reasoning skills. The model sparked a lot of buzz at HumanX, even though its rollout is limited to a select group of roughly 50 companies.
Victor Riparbelli, CEO of AI video company Synthesia, said Anthropic has managed to demonstrate focus and restraint with its models and product, which can be difficult for a young hyper-growth company.
“The guys at Anthropic were just like, ‘We’re not going to do anything about video, we’re not going to care about voice models, we’re just going to solve code gen,’ and now we’re here,” Riparbelli said in an interview. “OpenAI has had the problem of having to market six different products, which just takes up mind space for the consumer.”
One investor cautioned that while Anthropic has been consistent and managed to identify a sticky AI use case, the industry is still young, and momentum could easily swing in another direction.
AI change management
As tech companies work to usher their customers into the AI era, they’re also grappling with how to leverage and deploy agents internally. Even for Silicon Valley startups, keeping up with the pace of change is no easy feat.
Ashwin Sreenivas, president of AI startup Decagon, said the advent of coding agents has led to a number of shifts within his company. Decagon has changed its interview process to allow candidates to use the tools, and the company is able to rely on smaller teams of engineers.
A project that may have required four or five engineers “becomes two engineers because everyone can move a lot faster and go a lot farther,” Sreenivas said in an interview.
For Navrina Singh, CEO of AI governance startup Credo AI, the proliferation of new AI tools has been simultaneously exciting and anxiety inducing for her. Overcommunicating, particularly with her customers, has become essential, she said.
“The things that I could not do last year and I needed to hire 10 people, I can actually build over a weekend and deploy for myself and for the company,” Singh said. “The anxiety is I can’t control my roadmap, and I can’t control my commitments to the enterprise customers who love more clarity and who like a little bit more stability.”
Big tech incumbents are navigating similar changes.
Cisco President Jeetu Patel said roughly 85% of his company’s engineering workforce, or about 18,000 employees, are using AI, but the path to getting there was unlike what he’d anticipated. Patel said Cisco initially learned it i needed to prioritize adoption over outcomes, and to trust that model capabilities will continue to improve.
“You can’t think of these as tools, you have to think of these as digital coworkers that are joining your team, because your composition of your scrum team changes,” Patel said at the conference. “You might not have a scrum team of eight people. You might have a scrum team of two people and six agents, or two people and infinite agents.”
The race against China
Qwen3 is Alibaba’s latest large language model, which it says combines traditional LLM capabilities with “advanced, dynamic reasoning.”
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The fragile two-week ceasefire agreement between the U.S. and Iran has massive implications for energy and financial markets across the globe. But the vast majority of execs and investors who spoke to CNBC at HumanX this week said they’re not yet experiencing any direct business impact from the latest conflict in the Middle East.
Rather, they’re focused on another looming geopolitical problem: China’s open-weight models.
In AI, a model is considered open weight if its parameters, or the elements that improve its outputs and predictions during training, are publicly available. As of April, Chinese open-weight models, including GLM-5.1, Kimi K2.5 and Qwen3.5, dominate industry benchmarks.
American companies are swarming to China’s models. Cursor built its Composer 2 model using Kimi 2.5. Airbnb CEO Brian Chesky told CNBC in October that his company’s chatbot was largely dependent on Alibaba’s Qwen.
Given the importance the U.S. AI industry is placing on beating China when it comes to innovation, there’s a big emphasis domestically on closing the gap in open weight. Two investors told CNBC they’re dedicating a lot of their time and resources to that effort, and a third said it’s one of the key problems for the industry to solve right now.
Glean’s Jain said having multiple options is critical.
“The trend that we see is that enterprises today, they’re very wary of depending on one or two providers for all of their AI,” Jain said. “They don’t want to work with just one model company, because they know that innovation is happening across many and also in open source. You want to have a choice.”
