| My advice is to learn the fundamentals of software engineering. Take some good books or resources, learn what makes a practice good or bad and implement it via projects. Some ideas on what you should learn based on what you said: Data modeling or database design: this is probably where AI-generated apps rot fastest as they grow. Learn normalization, indexing, and why schema choices matter. Security basics: auth, input sanitization, secrets management, common vuln classes (OWASP top 10 is a fine starting ground). Testing philosophy: not necessarily syntax, but why you test, what to test, and how tests let you (and the AI) refactor safely. This is probably the single most important thing for someone building with AI, since its a safety net for code you didnt write line-by-line. System design and architecture basics: how to break something into services/modules, when not to, tradeoffs of monoliths vs. microservices at small scale, stuff like that. I would really recommend you to learn syntax, however the bare minimum is to be able to read the code and actually understand it. For example, knowing when a function is doing too much. |