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The reason people are holding out is that the current generation of models are still pretty poor in many areas. You can have it craft an email, or to review your email, but I wouldn't trust an LLM with anything mission-critical. The accuracy of the generated output is too low be trusted in most practical applications.



Any email you trust an LLM to write is one you probably don't need to send.


Glib but the reality is that there are lots of cases where you can use an AI in writing but don’t need to entrust it with the whole job blindly.

I mostly use AIs in writing as a glorified grammar checker that sometimes suggests alternate phrasing. I do the initial writing and send it to an AI for review. If I like the suggestions I may incorporate some. Others I ignore.

The only times I use it to write is when I have something like a status report and I’m having a hard time phrasing things. Then I may write a series of bullet points and send that through an AI to flesh it out. Again, that is just the first stage and I take that and do editing to get what I want.

It’s just a tool, not a creator.


>> have something like a status report and I’m having a hard time phrasing things

I believe the above suggested that this type of email likely doesn't need to be sent. Is anyone really reading the status report? If they read it, what concrete decisions do they make based on it. We all get in this trap of doing what people ask of us but it often isn't what shareholders and customers really care about.


Considering that I do get questions and comments about the projects, yet, people are reading this.


Google (even now) wasn't absolutely accurate either. That didn't stop it from becoming many billions worth.

> You can have it craft an email, or to review your email, but I wouldn't trust an LLM with anything mission-critical

My point is that an entire world lies between these two extremes.


Google became a billion dollar company creating the best search and indexing service at the time and putting ads around the results (that and YouTube). The didn't own the answer of the question.


I would say that anything you write can come back to you in the future, so don’t blindly sign your name on anything you didn’t review yourself.


Why don't you give actual concrete testable examples back with evidence where this is the case? Put your skin in the game.


A support ticket is a good middle ground. This is probably the area of most robust enterprise deployment. Synthesizing knowledge to produce a draft reply with some logic either to automatically send it or have human review. There are both shitty and ok systems that save real money with case deflection and even improved satisfaction rates. Partly this works because human responses can also suck, so you are raising a low bar. But it is a real use case with real money and reputation on the line.


Keyword is "draft". You still need a person to review the response with knowledge of the context of the issue. It's the same as my email example.




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