Good PM's are extremely good at understanding users, and use soft-skills to make the rest of the org focus on users more. I've worked with a couple, and they've added an enormous amount of value, sometimes steering teams of dozens of engineers in a more productive direction.
The problem is, it's hard to measure how good a PM is, even harder than for engineers. The instinct is to use product KPI's to do so, but especially at BigTech company, distribution advantages and traction of previous products will be the dominant factor here, and the best way of raising many product KPI's are actually user-hostile. Someone who has been a successful FAANG engineer who goes to a startup might lean towards over-engineering, but at least they should be sharp on the fundamentals. Someone who has been a successful FAANG PM might actually have no idea how to get PMF.
> Here's what to do instead: Find your most socially competent engineer, and have them talk to users a couple times a month
This is actually a great idea, but what will happen is this socially competent engineer will soon have a new full-time job gathering those insights, coalescing them into actionable product changes, persuading the rest of the org to adopt those changes, and making sure the original user insights make it into the product. Voila: you've re-invented product management.
But I actually think it's good to source PM's from people who've been engineers for a few years. PM's used to come from a technical background; Google famously gave entry-level coding tests to PM's well into the '10s. I dunno when it became more fashionable to hire MBA's and consultants into this role, but it may have been a mistake.
> Voila: you've re-invented product management.
This is a names vs. structure thing. For a moment, taboo the term product manager.
What I'm suggesting is a low risk way to see if an engineer has an aptitude for aligning the roadmap with what the users want. If they aren't great at it, they can go back to engineering. We also know for sure that they are technically competent since they are currently working as an engineer, no risk there.
The conventional wisdom (bad meme) is going to the labor market with a search term for people who claim to know what the users want, any user, any problem, doesn't matter. These people are usually incompetent and have never written software. Then hiring 1 and potentially more of the people that respond to the shibboleth.
If you want the first case, then you can't say "product manager" because people will automatically do the second case.
> What I'm suggesting is a low risk way to see if an engineer has an aptitude for aligning the roadmap with what the users want. If they aren't great at it, they can go back to engineering. We also know for sure that they are technically competent since they are currently working as an engineer, no risk there.
It doesn't have to be the most socially competent engineer to gather feedback. Having the engineering team sit with the target users gives so much insight into how the product is being used.
I once worked on an administrative tool at a financial institution. There were lots of pain points, as it started as a dev tool that turned into a monstrosity for the support staff. We asked to have a meeting with some reps who were literally 2 floors below us. Having the reps talk as they worked with the tool in real time over 1 hour was worth more than a year's worth of feedback that trickled in. It's one thing to solicit feedback. It's another to see how idiosyncrasies shape how products get used.
Putting on a PM hat is something I've been doing regularly in my engineering career over the last quarter century. Even as a junior (still in college!) at my first job I was thinking about product, in no small part because there were no PMs in sight. As I grew through multiple startups and eventually bigger brand name tech companies, I realized that understanding how the details work combined with some sense of what users actually want and how they behave is a super power. With AI this skillset has never been more relevant.
I agree your assessment about the value of good PMs. The issue, in my experience, is that only about 20% (at most) are actually good. 60% are fine and can be successful with the right Design and Engingeering partners. And 20% should just be replaced by AI now so we can put the proper guardrails around their opinions and not be misled by their charisma or whatever other human traits enabled them to get hired into a job they are utterly unqualified for.