This essay dissects the widening gap between AI hype and reality, arguing that large language models have hit a plateau - the “S-curve” - despite industry claims of imminent superintelligence. It contrasts bold predictions and massive investments with underwhelming flagship releases, framing today’s AI era as less about building godlike intelligence and more about integrating imperfect tools into real-world products. The piece suggests that the true future of AI lies not in transcendence, but in the messy, necessary work of making these systems actually useful.

When vendor promises meet government warrants, the warrants win every time. Microsoft's Senate testimony shows why "trust us" isn't a data protection strategy.

Well, the internet did what the internet does best this week: it collectively lost its mind over a number in an S-1 filing. Figma disclosed they signed a ~$550 million contract with AWS, someone used arithmetic (the secret weapon of Cloud Finance) to determine that this was roughly $300,000 per day on AWS, and suddenly everyone with a social media account became a cloud economics expert.

Disclaimer: This post was written May 2025, and the arguments apply to AI code capabilities at this time. The arguments around lack of competence are certainly likely to become less prevalent-while the parts about the desecration of the joys of programming, and fundamental human understanding of programming-are likely to become

AI coding assistants are React evangelists.