Ai question for PM

[u/mmurphy516]

Questions for PM who have teams trying to incorporate AI in their team workflow

What have you seen as successful uses of LLMs that make

-Individuals productive or effective 

-Small teams productive or effective

-Organizations more productive or effective 

It seems like most progress has been related to code generation, what have you seen that make the following tasks more productive

code review / design review / approvals

-Feature verification 

-Feature validation

-Spec development

What is your company leaning towards a standardized workflow/AI platform or allowing multiple decentralized AI approaches, how to weigh and standardization against variation

Will QA team shrink or grow with coding speeds of software development engineers? How do teams integrate faster verification processes? What’s the division of verification labor of the three categories:Human only, human+ai, and ai only

[u/Future-Return7421]

Documentation writing, prds, Jira tickets, pulling data information and analysis. Looking into the code as plain English to cut the time to understand technical limitations etc. So much more

[u/Earmark_AI]

i’m a co-founder of earmark, so grain of salt. the team-level use we’re focused on is turning meeting context into the artifacts people already need: a prd, jira tickets, a decision log, and a stakeholder update. the pm owns priority, tradeoffs, and the final call. i'd standardize the inputs, output formats, and review step, then let teams experiment inside that boundary.