AI makes tech debt more expensive

> Companies with relatively young, high-quality codebases benefit the most from generative AI tools, while companies with gnarly, legacy codebases will struggle to adopt them. In other words, the penalty for having a ‘high-debt’ codebase is now larger than ever.

This mirrors my experience using LLMs on personal projects. They can provide good advice only to the extent that your project stays within the bounds of well-known patterns. As soon as your codebase gets a little bit "weird" (ie trying to do anything novel and interesting), the model chokes, starts hallucinating, and makes your job considerably harder.

Put another way, LLMs make the easy stuff easier, but royally screws up the hard stuff. The gap does appear to be widening, not shrinking. They work best where we need them the least.

> the model chokes, starts hallucinating, and makes your job considerably harder.

Coincidentally this also happens with developers in unfamiliar territory.

I often think of LLMs as a really smart junior developer - full of answers, half correct, with zero wisdom but 100% confidence

I'd like to think most developers know how to say "I don't know, let's do some research" but in reality, many probably just take a similar approach to the LLM - feign competence and just hack out whatever is needed for today's goal, don't worry about tomorrow.