As AI giants spend billions racing to build the biggest models and data centres, Anthropic is taking a different approach. Guided by a “do more with less” philosophy, president and co-founder Daniela Amodei says the company believes smarter engineering and disciplined spending can still compete in an industry increasingly defined by scale.
Across Silicon Valley, scale has become the dominant belief. Companies are raising record capital, locking in hardware years ahead, and building massive data centres in the hope that the biggest intelligence factory will prevail. OpenAI stands as the clearest example, with around $1.4 trillion in headline compute and infrastructure commitments tied to vast campuses and next generation chips. Anthropic argues there is another path, where smarter spending, better algorithms, and efficient deployment can keep a company at the frontier without trying to outbuild rivals. “I think what we have always aimed to do at Anthropic is be as judicious with the resources that we have while still operating in this space where it’s just a lot of compute,” Amodei told a broadcaster. “Anthropic has always had a fraction of what our competitors have had in terms of compute and capital, and yet pretty consistently we’ve had the most powerful, most performant models for the majority of the past several years.”
The stance is notable given the background of Daniela Amodei and her brother Dario Amodei, who is Anthropic’s CEO. Dario Amodei helped popularize the scaling paradigm that more compute, data, and larger models drive predictable gains. That belief now underpins chip valuations and massive capital spending. Even so, Anthropic is trying to show that the next phase of competition will not be decided only by the largest training runs. Its focus includes higher quality data, post training methods that improve reasoning, and product choices that lower running costs. The company still expects rising needs, with roughly $100 billion in compute commitments. “The compute requirements for the future are very large,” Amodei said. “So, our expectation is yes, we will need more compute to be able to just stay at the frontier as we get bigger.”
Amodei also warned that headline spending figures are often not directly comparable and that early long-term commitments carry risk. “We have continued to be surprised even as the people who pioneered this belief in scaling laws,” she said. “The exponential continues until it doesn’t.” She drew a line between fast technological gains and slower real-world adoption, where business processes can lag. That enterprise focus has driven Anthropic’s growth, with revenue rising 10x year over year for 3 straight years and Claude available across major cloud platforms, even those selling rival models. As 2026 begins, both Anthropic and OpenAI face pressure to show discipline ahead of possible public market moves. If investors keep rewarding scale, the biggest builders may win. If efficiency matters more, Anthropic’s bet could pay off.
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