This is the classic example of “I want it to do everything. But it didn’t do what I wanted. So obviously it’s not helpful.”
It doesn’t solve /all/ problems. And some models are better than others at certain tasks. You see people talk about PRDs and they say “I got Claude to create a PRD and it sucked” but you sit them down with o3 and generate the same PRD and they are like “oh wow this is actually pretty decent”.
But difficult to help over HN. As a sort of related example. Back in May I had a requirement to ingest files from a new POS system we didn’t currently support. The exports we got are CSV but based on the first char decides the first type of line that needs to be parsed and how many commas will be in that data set line.
I used o3 and explained everything I could have how the file worked and how it should parse it into a generic list etc. got it to generate a basic PRD with steps and assertions along the way.
I then fed this into cursor using Claude sonnet 4 with the csv files asking it to look at the files and the PRD and asked it if there was anything that didn’t make sense. Then asked it to begin implementing the steps 1 by 1 and letting me check before moving onto the next step. Couple of times it misunderstood and did things slightly wrong but I just corrected it or asked Claude to correct it. But it essentially wrote code. Wrote test. Verified. I verified. It moved on.
Typically in the past these tasks take a few days to implement and roll out. This whole thing took about 1 hour. The code is in the style of the other parsers with the exception that it optimised some parts and despite being a bit more complicated runs faster than some of our older parsers.
While most of my usage is around programming. We also use AI for marketing, customer leads, I have scheduled tasks to give me summaries of tickets from the support system to know what should be prioritised for the day. So even tho AI doesn’t solve all programming issues we get value in almost all aspects of the business.