LLMs getting better at end-to-end software, says Anthropic CEO Dario Amodei

Anthropic's Chief Executive Dario Amodei

• LLMs now handle end-to-end software workflows, says Anthropic CEO
• AI tools trigger $300B IT stock sell-off over automation concerns
• India seen as fertile ground for rapid AI adoption and innovation

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AI firm Anthropic's Chief Executive Dario Amodei, on February 16, said Large Language Models (LLMs) are now moving decisively toward handling end-to-end software workflows, a shift that could fundamentally reshape how enterprises build and deploy technology.

The comments come at a time when brutal sell-offs wiped out roughly $300 billion globally from IT stocks, on concerns around automation-led disruption.

“I think on software, we're starting to go more end to end. The models are starting to do multi-stage workflows and humans can step into the role of supervisors and accelerate themselves by a factor of 10x to 100x,” Amodei said on February 16 after opening the company's India office in Bengaluru

Global stock markets were rattled after Anthropic released a new set of AI tools for corporate legal teams. The announcement, made last week, led to sharp sell-offs across European legal software companies, US technology firms, and Indian IT stocks.

Meanwhile, he added that LLMs can increasingly take tasks from the finance or legal space. “These are areas where increasingly the models get better. And so I think there's a lot of startups and things to be built where,” Amodei added.

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Speaking to developers and enterprise leaders, Amodei said that organisations that “skate to where the puck is going” are building for the capabilities models will have a year or two from now, not just what they can do today.

He added that companies that understand this are deploying AI agents broadly across functions, including legal, finance and communications, even before fully packaged products exist. That approach, he highlights, allows them to anticipate the roadmap and extract value faster than peers

Amodei also highlighted India as a uniquely fertile ground for this shift, citing the country’s scale, developer energy and ability to experiment quickly.

He pointed to examples of AI being embedded into digital public infrastructure (DPI) and government data systems, arguing that such speed and adoption are rare elsewhere.