We are programming AI in assembly language

In the series of articles I’ve been writing for Fast Company devoted to what I believe corporate AI should be, I’ve been touching on a very provocative idea: Perhaps the biggest problem of corporate AI as we know it so far is not intelligence, but the level at which we are programming it. As we speak, frontier models, elastic cloud infrastructure, vector databases, managed APIs, and large amounts of computation are available to basically any serious company. As a substrate, this is extraordinarily powerful. However, in order to put AI systems into production, we still require engineers who hand-assemble fundamental things such as persistence, memory, permissions, tracing, retries, orchestration, durable execution, tool access, context management, and evaluation. As we said before, this is like the internet in 1991, before the web was invented. Today, high-level languages (programming languages that use strong abstraction from the computer’s hardware details, so it’s easier for humans to read and write) are normal. However, decades ago, developers had to fight the machine directly, in machine or assembly language, something that John Backus described as “a hand-to-hand combat with …