Sherwin Wu: evaluation

Transcript context

…It's definitely changed less than an engineer. There's no Codex for managers just yet. However, I use Codex quite a bit for some of the more managery tasks that I do. I'd say a couple things are changing. There are like some trends. So I don't think it's changed that much yet, but I see trends, and I think if you play it out, you can see where a lot of this is going. One thing that's becoming increasingly clear is Codex really empowers top performers to be a lot more productive. And I think this is maybe true for AI more broadly across society, which is the people who really lean in or the people who have high agency or will really get good at these tools, will kind of supercharge themselves. And so I'm kind of noticing this now as well, which is like the top performers kind of end up being a lot more productive. And so you see a broader spread in team productivity in this way. So one thing that I've always done as a management philosophy is to spend actually the majority of my time with top performers, just like make sure they're unblocked, make sure they're happy, make sure they feel productive and they feel heard. I think this is even more true in an AI world where your top performers are going to just really be shooting ahead using these tools. I think one example is the team that's maintaining a 100% Codex generated code base, just letting them rip and see what's happening there. It is something that's paid dividends. So I think that's kind of one trend that I'm seeing where spending even more time with top performers for managers I think is likely going to continue. The other thing is, so this is more an observation, but my sense is with a lot of these AI tools available to managers, so less like writing code, but just things like ChatGPT with organizational knowledge, like being able to do research and understanding organizational context a lot better. Another good example is we're doing performance reviews right now and it's actually really easy to use ChatGPT with internal knowledge hooked up to GitHub and our Notion Docs and Google Docs to get a really good sense of what this person has done over the last 12 months and writing a little deep research report for it. My sense is I think managers will be able to manage much larger teams in this world, kind of like how software engineers are managing 20 to 30 Codexes. My sense of these tools will allow managers, people managers to be higher leveraged and it will allow them to manage teams of way more than the current best practice of, I think it's like six to eight for software engineering. You kind of see this applied to the non-engineering domains like support or operations where previously the size of a support team might be limited, but as you can pass off more things to agents, you can actually do more work and also manage more people this way. I think the same thing might happen for people management as well, especially in tech companies. And we're already seeing this. nts, you can actually do more work and also manage more people this way. I think the same thing might happen for people management as well, especially in tech companies. And we're already seeing this. There's some teams where there are EMs managing quite a few people and they're doing it pretty adeptly because of some of these tools where they can get higher leverage and understand what their team's doing, understand organizational context a little bit better and operate in that way. I love this advice that the way you described it is you've always leaned into top performers and spent more time with them, unblocked them, make sure they're happy. The way Marc Andreessen was just on the podcast, the way he phrased it is AI makes good people better and it makes great people exceptional. And what you're saying here is just doing this more and more is probably the right move, spending more time with the best people on your team to unblock them, make sure they have everything they need.…

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