[Seattle3503]

> The project falls apart because Product drops the ball, but Engineering is the team at the end of the funnel, so the blame naturally tends to land on them. Product’s output is often hidden, and it’s easy for them to say, “Well, we did our part. Engineering just didn’t deliver.”

I've seen this get worse with LLMs. I've had specs that were wholly or in significant part generated by ChatGPT, but they look detailed so the are plausible workslop. I've been given a spreadsheet with nonsense items "Implement adaptive intent-driven workflows across user touchpoints" (I generated this example with GPT).

When I asked what any of it meant I was met with silence. Later through the grapevine I hear the requirements were generated by ChatGPT and the guy responsible for them doesn't understand the system at all. But guess who is responsible for delivery?