[janalsncm]

AI engineer: makes API calls to a hosted LLM.

ML engineer: builds models and deploys them.

Hosted models have eaten a lot of the domain of ML but the difference is pretty clear in industries like recommendation, where LLMs are slower, less accurate, and cannot be personalized, not to mention orders of magnitude more expensive.

Agentic engineer would be someone who builds agents not just someone who uses them. Anyone can use Claude code.

[simonw]

"Anyone can use Claude code"

I'll happily push back against that. Using Claude Code and similar tools effectively is way, way harder than people expect.

Anyone can pick up a guitar and strum the strings, but it takes a whole lot of work to actually get good with it.

[Cherryontop11]

> I'll happily push back against that. Using Claude Code and similar tools effectively is way, way harder than people expect.

No it's actually not that difficult. Even if you are not a "prompt engineer" you will get out what is needed from claude if you use simple logic (no need to be technical). In fact this whole "Prompt Engineering" scam will go extinct soon, as SOTA LLM's already catching up on most edge cases and prompting issues.

> Anyone can pick up a guitar and strum the strings, but it takes a whole lot of work to actually get good with it.

Really the wrong analogy here. You are comparing a human who learned guitar through years of practice. When with AI who itself already knows how to play. You're not learning an instrument. You're more like someone who just hired a virtuoso musician. Yes, you need to tell them what song you want,but you don't need to teach them chord progressions. The model already knows the hard part.