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Given your DA experience and IT knowledge, AI Product Management is a solid career choice! You'd be bridging the gap between tech and business, defining the vision and strategy for AI-powered products. A typical day involves collaborating with engineering, sales, and marketing, understanding customer needs, and analyzing the market6. Essential skills include a strong understanding of AI technologies, excellent communication, and the ability to translate complex problems into simple solutions. Above all, I think what's key is adaptibility, as this field evolves more rapidly than anything else in the world right now.
Such a GPT answer lmao
I'd be pretty happy if my (still people minded) PMs had DA backgrounds. Measurable results are the main overlooked piece in all this gen AI stuff, especially since it's expensive to be doing. Related, it helps a to understand variability is results, that things are often not point estimates.
Assuming by IT you mean tech support/system admin, not tech in general... Habits from IT experience will be useful in tracking things as a PM. There might also be some minor portal setup stuff, but that's pretty simple; for example, you may need to roll some demo for the team if you want to intro some data labeling platform into the workflow. Normally a dev would help you do the setup with hosting whatever internally if that becomes relevant.
The jd itself sounds like a mix of GPU capacity planning, procurement, and generically helping find data. For capacity, you'll realistically need to work with the DS or MLE folks; I don't think it's really realistic to assume PMs know this stuff beyond input and output token counts and TPS. But if you can, and you probably can since you understand distributions and making metrics, then all the better!
Like I said first, I'd be pretty happy with a people forward DA as a PM. You should apply.
I would argue that in addition to measurable results being overlooked, the overall effort to think through how gen AI is changing the requirements of humans; we plug stuff in that helps create results faster, but still fail to educate users on how they have to further supplement or validate results. take the GenAI in performance feedback for example. it may help to quickly write statements and is an improvement over people who didn’t enter anything before, but it misses the mark on some of the most critical elements of effective feedback in terms of offering specificity, or focusing on specific behaviors. The intent may be that the content is a starting point and that people will adapt the information, but the reality is many just call it good enough and check the box. Doing something that offers little value faster is of overall very limited organizational benefit.
Product or sales would actually be a good choice as well. Technical sales people are taken much more seriously