Why AI labs are betting big on AI coding

Welcome to AI Decoded, Fast Company’s weekly newsletter that breaks down the most important news in the world of AI. I’m Mark Sullivan, a senior writer at Fast Company, covering emerging tech, AI, and tech policy. This week, I’m focusing on why the big AI labs are concentrating so intensely on AI coding. I also look at Apple’s renewed AI plans, and at new legal threats to AI chatbots. Sign up to receive this newsletter every week via email here. And if you have comments on this issue and/or ideas for future ones, drop me a line at sullivan@fastcompany.com, and follow me on X @thesullivan. Why the major AI companies are so focused on coding Researchers and executives at big AI labs like OpenAI, Anthropic, and Google talk about AI-generated code a lot. Tools like Anthropic’s Claude Code, OpenAI’s Codex, and Google’s AlphaCode 2 have become a major research focus. But the reasons for that are more complicated than you might think. OpenAI and Anthropic are widely expected to go public soon, and both are spending far more than they’re making. Developing frontier AI models is enormously expensive, and the labs still haven’t sold enough access to their models to enterprises and consumers to cover the costs. AI coding tools, though, are a bright spot. Over the last eight months, they’ve matured to the point where they can reliably build whole software projects from plain-language prompts. Since companies spend heavily on software development, they’re willing to pay for AI that helps engineers work faster. But revenue may not be the labs’ main motivation. They aren’t simply chasing a profitable killer app to offset massive capex before an IPO. They have a bigger, longer-term goal. They believe AI coding may be the path to artificial general intelligence (AGI), or AI systems that are generally as smart as humans. They believe they can create AI coding agents that are so good that they can improve the code that goes into the AI models themselves. The tools could even wor