Keep pulling the thread on David Sachs.
Big tech's AI capital expenditure is projected to surpass $800 billion in 2026 alone.
David Sachs has argued that big tech's AI capex spending could create a 2.5% GDP tailwind this year and a 3% tailwind next year.
The defining relationship of the American economy is the interplay between AI lab revenue growth and AI infrastructure buildout.
In the first quarter of the year, AI-driven investment contributed approximately 75% of the increase in US GDP, which grew at a 2% annualized rate.
According to data from the St. Louis Fed, AI investment accounted for 39% of marginal US GDP growth over the trailing four quarters.
The revenue potential from selling AI on a per-seat basis, at $20 to $200 per month, was insufficient to justify trillions of dollars in infrastructure spending.
The AI economic model has shifted from an assisted, seat-based paradigm to an agentic, usage-based consumption paradigm.
Anthropic experienced a surge that brought its annual revenue run rate to $30 billion, which later increased to $47 billion by late May.
OpenAI's revenue increased significantly in the first quarter, aided by its agentic token vehicle, Codex.
At the beginning of the year, Anthropic doubled its number of enterprise customers spending over $1 million annually from 500 to more than 1,000 in under two months.
Uber exhausted its entire annual AI budget in the first four months of the year and subsequently implemented a $1,500 per month spending cap per employee.
Cursor's Composer 2.5 model achieves performance comparable to Opus 4.7 and GPT-5.5 at one-tenth of the cost.