Yeah, not only is the structure of business workflows often resistant to mature software dev workflows, developers themselves increasingly lack the discipline, skills or interest in backwards compatibility or good initial designs anyway. Add to this the trend that fast changing software is actually a decent strategy to keep LLMs befuddled, and it’s probably going to become an unofficial standard to maintain support contracts.
On that subject, ironically code gen by ai for ai related work is often least reliable due to fast churn. Langchain is a good example of this and also kind of funny, they suggest / integrate gritql for deterministic code transforms rather than using AI directly: https://python.langchain.com/docs/versions/v0_3/.
Overall.. mastering things like gritql, ast grep, and CST tools for code transforms still pays off. For large code bases, No matter how good AI gets, it is probably better to get them to use formal/deterministic tools like these rather than trust them with code transformations more directly and just hope for the best..
On that subject, ironically code gen by ai for ai related work is often least reliable due to fast churn. Langchain is a good example of this and also kind of funny, they suggest / integrate gritql for deterministic code transforms rather than using AI directly: https://python.langchain.com/docs/versions/v0_3/.
Overall.. mastering things like gritql, ast grep, and CST tools for code transforms still pays off. For large code bases, No matter how good AI gets, it is probably better to get them to use formal/deterministic tools like these rather than trust them with code transformations more directly and just hope for the best..