Designing Tech Stacks for AI-Generated Code

Something strange is happening in backend engineering. The tools writing our code are getting smarter every quarter, but the infrastructure those tools have to target hasn't changed in a decade. We're pointing increasingly capable AI agents at the same sprawling, multi-service architectures we built for human developers, and then wondering why the output is fragile. The conversation around AI-assisted development has been almost entirely about the models. Which agent is best. Which IDE integration is fastest. Which model scores highest on SWE-bench. But there's a quieter, more consequential question that almost nobody is asking: what should the target architecture look like when the developer is an AI? The mismatch nobody talks about Here's the core tension. Modern backend architecture evolved to solve human organizational problems. Microservices exist because teams needed to deploy independently. ORMs exist because developers didn't want to write SQL. Docker exists because "works on m