Technology

I would say absolutely in the general sense nost people, and the salesmen, frame them in.

When I was invited to assist with the GDC development, I got a chance to partner with a few AI developers and see the development process firsthand, try my hand at it myself, and get my hands on a few low parameter models for my own personal use. It's really interesting just how capable some models are in their specific use-cases. However, even high param. models easily become useless at the drop of a hat.

I found the best case, one that's rarely done mind you, is integrate the model into a program that has the ability to call a known database. With a properly trained model to format output in both natural language and use a given database for context calls, and concrete information, the qualitative performance leaps ahead by bounds. Problem is, that requires so much customization it pretty much ends up being something a capable hobbyist would do, it's just not economically sound for a business to adopt.

LLMs/"Vibe Coding" is probably a little bit more useful than the average intern with some tasks bumping up to an early career hire (what would historically be a Junior Engineer before title inflation/stagnation).

As in: it can generate code that might do what you want. But you need (actual) senior engineers to review the code thoroughly. And... how do people get the experience they need to do that?

Which basically results in turning everyone into a manager. Except your reports aren't humans and you don't get more pay. Instead your reports are vscode plugins. Which... sounds like absolute hell but I can get why the (wannabe) management class loves that.

I've found success using more powerful LLMs to help me create applications using the Rust programming language. If you use a weak LLM and ask it to do something very difficult you'll get bad results. You still need to have a fundamental understanding of good coding practices. Using an LLM to code doesn't replace the decision making.