zlacker

>>LucidL+(OP)
My anxiety about falling behind with AI plummeted after I realized many of these tweets are overblown in this way. I use AI every day, how is everyone getting more spectacular results than me? Turns out: they exaggerate.

Here are several real stories I dug into:

"My brick-and-mortar business wouldn't even exist without AI" --> meant they used Claude to help them search for lawyers in their local area and summarize permits they needed

"I'm now doing the work of 10 product managers" --> actually meant they create draft PRD's. Did not mention firing 10 PMs

"I launched an entire product line this weekend" --> meant they created a website with a sign up, and it shows them a single javascript page, no customers

"I wrote a novel while I made coffee this morning" --> used a ChatGPT agent to make a messy mediocre PDF

>>pizzat+ua
At the end of the day, it doesn't really get you that much if you get 70% of the way there on your initial prompt (which you probably spent some time discussing, thinking through, clarifying requirements on). Paid, deliverable work is expected to involve validation, accountability, security, reliability, etc.

Taking that 70% solution and adding these things is harder than if a human got you 70% there, because the mistakes LLMs make are designed to look right, while being wrong in ways a sane human would never be. This makes their mistakes easy to overlook, requiring more careful line-by-line review in any domain where people are paying you. They also duplicate code and are super verbose, so they produce a ton tech debt -> more tokens for future agents to clog their contexts with.

I like using them, they have real value when used correctly, but I'm skeptical that this value is going to translate to massive real business value in the next few years, especially when you weigh that with the risk and tech debt that comes along with it.

>>jimbo8+Ru
Imo getting 70% of the way is very valuable for quickly creating throwaway prototypes, exploring approaches and learning new stuff.

However getting the AI to build production quality code is sometimes quite frustrating, and requires a very hands-on approach.