It might not fit your work, but there are tons of areas where “good enough” can still provide a lot of value. I’m sure you’d be thrilled with a tool that could correctly tell you if Apple’s stock was going up or down tomorrow 70% of the time.

I work in a mail room sending hard copy letters to customers. If I got my job right only 70% of the time then I’d be causing massive privacy breaches daily by sending the wrong personal information to the wrong customers.

Would you trust an AI that gets your banking transactions right only 70% of the time?

No. I also wouldn’t use a hammer to cut a board in half - I’d grab a saw. Knowing how to pick the right tool is a fundamental part of being a good engineer. Sometimes 70% is unacceptable, sometimes it’s exceptional. LLMs are incredible technology, but also just another tool in the toolbox. Use them where they fit, not where they don’t.

Sure, though the marketing around LLMs is aimed at general purpose use. It’s up to the user to decide if it’s actually useful for their use case. Unfortunately, many use cases in business can’t tolerate high error rates.

> I don’t need a tool that’s right maybe 70% of the time (and that’s me being optimistic).

Where are you getting this from? 70%?