bad news "AI bubble doomers". I've found the LLMs to be incredibly useful and reduce the workload (and/or make people much, MUCH more effective at their jobs with the "centaur" model).
Is it overhyped? FUCK Yes. Salespeople Gotta Always Be Closing. But this is NOTHING like the moronic Segway (I am still bitter about that crap), Cryptocurrency, which is all grifters and gamblers and criminals end-to-end, and the first dot-com bubble where not NEARLY enough people had broadband or even internet access, plus the logistics systems to support shipping products was nowhere REMOTELY where it is today.
If you are expecting this "AI bubble" to pop anytime soon, uh.. you might be waiting a bit longer than you think? Overhyped, yes, overbuilding, sure, but not remotely a true bubble any any of the same senses of the three examples I listed above 👆. There's something very real, very practical, very useful here, and it is getting better every day.
If you find this uncomfortable, I'm sorry, but I know what I know, and I can cite several dozen very specific examples in the last 2-3 weeks where it saved me, or my team, quite a bit of time.
@codinghorror “I can cite several dozen very specific examples in the last 2-3 weeks where it saved me, or my team, quite a bit of time.”
Please do, if you can. Because most time I’ve tried to use LLMs for work the error rate ends up costing me MORE time than I would have spent without, and most AI boosters are short on specifics. We just had a presentation at my job on how we all need to be using AI with no case studies of how it’s actually been useful so far.
@sethrichards here's one: a friend confided he is unhoused, and it is difficult for him. I asked ChatGPT to summarize local resources to deal with this (how do you get ANY id without a valid address, etc, chicken/egg problem) and it did an outstanding, amazing job. I printed it out, marked it up, and gave it to him.
Here's two: GiveDirectly did two GMI studies, Chicago and Cook County and we were very unclear what the relationship was, or why they did it that way. ChatGPT also knocked this out park and saved Tia a lot of time finding that information out, so she was freed up to focus on other work.
I could go on and on and on. Email me if you want ~12 more specific examples. With citations.
But also realize this: I am elite at asking very good, well specified, very clear, well researched questions, because we built Stack Overflow.
You want to get good at LLMS? learn how to ask better questions of evil genies. I was raised on that. 🧞
@codinghorror @sethrichards I see, everyone else is using it wrong... Tools this bad/difficult should not be being presented how they are. People are not going to invest days in prompt engineering before asking a generic LLM for medical advice.
@relistan @codinghorror @sethrichards I'm fairly sure I could learn Xcode that well without boiling an ocean tho
@falken @codinghorror @sethrichards learning XCode? I’m not even using it, that’s the tip of the problem. Go from zero to shipping 5k lines of production code + tests in a week on an existing project that you have very little context on. But, the environmental impact right now is ridiculous. Many of the companies doing stupid stuff will go out of business. Hardware will get better fast. I am convinced about the utility. But we’ve got to rapidly remove the downsides or it won’t work long term.
@falken @codinghorror @sethrichards the tool over-hype masks the huge underlying utility. If you think of it as a tool that you need to learn to use and not your “AI co-worker” or other hype-fueled nonsense, it is quite productive. Example: I am not an iOS engineer but I’m a principal engineer. With me directing Claude Code, reviewing its work, setting code standards, and asking for refactors, I produced thousands of lines of well-factored, tested code iOS code that passed review and shipped.