I’ve called November 2025 the November inflection point because that was when GPT-5.1 and Opus 4.5, combined with their respective coding agent harnesses, got good—good enough that we’ve spent the last six months adapting to agent systems that can reliably get useful work done.
I think April 2026 is a new inflection point where the revenue implications of this have started to land, to the benefit of the frontier AI labs and with material impacts on the budgets of large companies.
We’ll know for sure how real this moment is when the S-1 documents for the upcoming Anthropic and OpenAI IPOs give us some real, audited numbers to get our teeth into.
— Simon Willison in I think Anthropic and OpenAI have found product-market fit
What if AI is more expensive than junior developers? Everything stays the same, but AI companies go bankrupt and the AI bubble bursts much earlier than expected.
Is this scenario so crazy? Simon spends ~2000$ per month, which is a reasonable cost of a junior developer in Portugal or another near-shore country. Now I’m sure he is more productive with those tokens than he would with a junior developer. In fact, he would be less productive given the cost of training. But developers can leave anytime, and it is a good idea to train new productive developers.
Of course LLM providers do not want the AI bubble to burst. To avoid it, they can just reduce infrastructure and training costs. No CEO will do that at the risk of losing the monopoly race to their competitors. So it’s a race to the bottom, aiming to become the last survivor. I wonder if this has happened in the past, and what was the role of nationalization in the process….