How Investors Think AI Will Actually Make Money
Briefly

How Investors Think AI Will Actually Make Money
"You might say that the biggest AI startups are led by professionally unreliable narrators, who theorize about the future of their companies - and their industry, and humanity in general - with a variety of clear but sometimes conflicting biases. This can make it somewhat hard, from the outside, to figure out which vision investors are banking on, beyond a general fear of missing out: Mass labor automation? AI-assisted research? Mainstream search-like products that could unseat Google?"
"One is vibey: A slightly underwhelming GPT-5 release, accompanied by a change in rhetoric from some AI leaders, has shifted the conversation away from acceleration and superintelligence and back toward nervous talk about bubbles. The other has shown up in deals: After Google beat out OpenAI to acquire (or acqui-hire) AI software development startup Windsurf, both OpenAI and xAI are reportedly stalking AI coding assistant startup Cursor, which rebuffed OpenAI earlier this year but may now be exploring deals to license data;"
Major AI startups present competing and often conflicting visions about future products and impacts, complicating investor assessments. Recent shifts include a tepid GPT-5 rollout and a rhetorical move from acceleration and superintelligence toward concerns about market bubbles. Strategic acquisitions and dealmaking—Google acquiring Windsurf, OpenAI and xAI pursuing Cursor, and Nvidia buying an AI coding startup—indicate renewed focus on AI coding assistants. AI coding has emerged as an early, monetizable LLM use case for enterprises and developers. Anthropic raised $13 billion in a Series F led by ICONIQ, valuing it at $183 billion post-money, signaling strong investor backing.
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