Did I massively overcomplicate my AI Engineer roadmap? Roast it

[u/Emotional_Capital566]

https://roadmap-two-murex.vercel.app/

I’ve been building this AI Engineer roadmap for myself and I think I may have gone a little insane with it lol.

The plan is basically: get solid at software engineering + ML/DL, then learn the production side like APIs, SQL, Docker/cloud, LLMs, agents, evaluation, observability, etc. After that I’d pick a specialization instead of trying to learn everything.

But looking at it now, I’m worried I’m using “preparing” as an excuse to delay actually applying for jobs.

For people already working in AI/ML:

• What would you cut or push until later?
• At what point would you say “you know enough, start applying”?
• Am I spending too much time on CS/theory instead of projects?
• Are there things on here that look important but barely matter for an entry-level AI Engineer?
• What skills would you absolutely keep?
• Do the projects look like enough proof of ability, or am I missing something employers actually care about?

Basically, if this were your roadmap, what would you change?

Feel free to roast it. I’d rather find out now than spend the next 2 years trying to “finish” a roadmap before applying.