And then someone copy pastes it into Claude and now those inaccuracies become part of the code and tests.
It's the equivalent of writer's block and is why a common advice given to writers is to put anything they can onto the page then edit it later.
The PM has historically often not had a detailed enough mental model of the implementation to spot the hard parts in advance or a detailed enough mental model of the customer desires to know if it's gonna be the right thing or not.
Those are the things that killed waterfall.
You can use LLM tools to help you improve both those areas. Synthesizing large amounts of text and looking for inconsistencies.
But the 80th-percentile-or-lower person who was already not working hard to try to get ahead of those things still isn't going to work any harder than the next person and so won't gain much of a real edge.
Normally waterfall works where the scope is extremely-well defined and articulated in design plans. Which shortens dev time because prior to AI code was mostly deterministic. Here we have to do waterfall level of documentation while iterating on a non-deterministic solution (code gen) to non-deterministic requirements (per usual).
It's bonkers.
I still think the technology is cool though.
And to answer the questioner.. Have you worked with a PM? Most of the ones I've worked with try to be simultaneously in charge yet not responsible for anything. Validating something implies skill and responsibility.
We see it with code too right? It’s harder to review code than to write it.
On top of that the LLM can work so fast that the amount of things that need validating grows!
This is where humans get lazy and the problems come in IMO. Whether its a PM not validating their ticket, or a dev doing a bad code review.
Add on to that that the incentives currently are to move fast and trust the AI.
It becomes clear to me that a lot of that review work either won’t be done at all, or won’t be nearly thorough enough.
Reviewing code is harder than reviewing text because code does something and has interdependencies and therefore must be correct in its function, do not mix the two. This is like saying an editor reviewing an article or novel is harder than actually writing the novel which is blatantly incorrect.
Hahahahahaha. Sorry, I couldn't help myself; this reads like satire. The answer is "real life experience says otherwise".
If your technology relies on humans using it in ways that go against the ways they are inclined to use them, then that is an issue with the technology.
Are advanced calculators bad because a student could use the CAS to ace calculus homework, exams or the SAT without actually learning the material?
Is copy/paste bad because a person could use it to copy/paste code from one place to another without noticing some of the areas they need to update in the new location, adding bugs and missing a chance to learn some more subtleties of the system?
Is Git bad because a manager could use it to just measure performance by number of lines of code committed instead of doing more work to actually understand everyone's performance?
Many tools can be used lazily in ways that will directly work against a long term goal of improving knowledge and productivity.
This isn’t actually an argument for or against anything, I don’t know why people say this. It is entirely possible that people are using this brand new, historically unprecedented tool wrong.
Cars have been a huge success in spite of requiring people to learn a bunch of new things use them.
Some people are lazy, plain and simple. If they want to blindly accept what the LLM tells them without critical analysis and review then that's on them.
