I doubt GP is suggesting ‘go ahead and be negligent to feedback and guardrails that let you course correct early.’

Plugging the Cynefin framework as a useful technique for practitioners here. It doesn’t have to be hard to choose whether or not rigorous planning is appropriate for the task at hand, versus probe-test-backtrack with tight iteration loops.

Comments URL: https://news.ycombinator.com/item?id=45730757

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Or put differently: it’s a request, given limited resources let’s expend effort on a fairer society, not one with longer lived people.

Where I live, if an engineer signs off on a bridge design and the bridge personally collapses, they are personally liable for harm done to folks on the bridge. As far as I’m aware software engineering does not have something like that.

edit: I don’t have personal experience around spending limits but I vaguely recall them being useful for folks who want to set up AWS resources and swing for the fences, in startups without thinking too deeply about the infra. Again this isn’t a failure mode unique to LLMs although I can appreciate it not mapping perfectly to your scenario above

edit #2: fwict the LLM specific context of your scenario above is: providing examples, setting up API access somehow (eg maybe invoking a CLI?). The rest to me seems like good old software engineering

> That’s exactly what it means to hit a wall, and exactly the particular set of obstacles I described in my most notorious (and prescient) paper, in 2022. Real progress on some dimensions, but stuck in place on others.

The author includes their personal experience — recommend reading to the end.

To dig up the lede: LLMs are proving useful in some instances, consider staying abreast of developments here to find ways to do a better job as time goes by. The exact nature of “better job” and the timeframe along which that reveals itself are left as exercises for the reader

https://7powers.com/

Having your likeness used to express an opinion that is the opposite of your own is nasty too. You can produce the kind of thing that has no courtesy, no grace, no kindness or care for the people around you.

The mass extraction and substitution of art has also caused a lot of unnecessary grief. Instead of AI enabling us to pursue creative work… it’s producing slop and making it harder for newbies to develop their craft. And making a lot of people anxious, fearful, and angry.

And finally of course astroturfing, phishing, that kind of thing has in principle become a lot more sophisticated.

It unnerves me that people can pull this capital lever against each other in ways that don’t obviously advance the common good.

Also there are scenarios where wiring up exhaustive cases would be tedious or require clever use of a vim macro, that a call to AI tends to do in slightly less time but much less mental overhead - allowing me to move on with less fatigue. Overall I cover more ground this way.

It tends to excel when I’ve structured code in a way that’s easily copyable or extensible, such that I can ask the AI to replicate pattern A but for API B. Again this saves me dropping into a low level understanding of an API integration unless I absolutely need to. I tend to check if I need to based on test cases, observability, and performance monitoring —- all the same shit I’d usually use to determine whether or not I should edit the code manually anyway.

Overall, obvious net benefit when used prudently. I’ve seen juniors use AI to write messy code that’s challenging to debug, understand, and maintain. It really is just another tool. You can use it to make your life easier or you can use it to make your life harder.