Microsoft plans around seasons, not fixed roadmaps

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 30:32

   So let me ask you actually about that. So planning right now is just crazy. How does anyone plan a roadmap when there's just like, OK, GPT-5 is out? OK, great. uh what what what works for you for setting an actual a roadmap and a strategy for your team like how far out do you plan how often do you have to rethink everything i mean i'll caveat this by saying like everyone's just figuring it out and it's a lot harder to figure it out when you're a larger organization than when you're you know much smaller and you get to kind of uh you know run something yourself and there's pros and cons to both so here's what we do we uh the company um historically at least in our product teams had kind of semesters that they planned again. So I think that as every six months, there's kind of a strategy with back, look forward,

2. 31:14

   all of those things. I think that's very valuable. I think like the idea of six months though, and really understanding what's changing out in front is truly challenging to kind of have a overbaked situation. And so we kind of think about it as, you know, what season are we in? And so a season, which is very uncomfortable, can be denoted by a set of secular changes that are happening in the industry or that are happening from customers. And so, you know, you can think about season one might have been like, you know, the prototyping of AI and kind of the early GPT work. And then it was all around models and reasoning models. And now it's the advent of agents. And so that can last a year, that can last six months, that can last three months, but like grounding everybody on the thing.

3. 32:00

   ethos of what are the secular changes? What are the customer problems we need to solve? What does winning look like? So everybody has that shared sense. What is the North Star metric is something that we do. The second thing that we do is that we have kind of loose quarterly OKR. So like, OK, if we believe that, what do we need to do next quarter to actually put ourselves on a path to that? And then from there, you know, teams are operating in squads and they're kind of setting out, you know, four to six week goals that they're trying to go after for problem areas to go ladder up to that, you know, and especially as a platform for the company and the platform for our Azure customers with AI, I will say we go through lots of changes to that all the time. And I think we have to just have an openness that that is the business that we're in. I think the other thing

4. 32:48

   is just like we try to leave slack in the system, not just for the unplanned, but for the slope, I think that we have to continuously be thinking about how we're going to disrupt the platform in our thinking and what we need to be investing in to make that possible. And so we try to do a little bit of both. This is awesome. So what I'm hearing here is there's this concept of seasons and everyone's aligned.

5. 33:11

   Okay, this is time for agents. This is what's happening right now. We're going to center around our strategy around agents. And then there's these loose quarterly OKRs you plan for three months roughly, and then you leave some slack in the system for things to change. Yes. Is the current season Agents? How would you describe what season right now? Yeah. OK. It's Agents. OK. The Rise of Agents. The Rise of Agents. That sounds like a Terminator movie. Do you have a sense of what the next season might be? Is there any like, oh, this might be coming next? Gosh, I don't. But I think that, look, like we have, you know, more than 15,000 agents that are deployed on our service today. At least at the Azure service, there's a bunch of other platforms in the company. And I would just say that I think that we should

6. 33:59

   really focus on making sure that we have all of the alignment, accountability, observability, evals to making those agents like great. I think that Manus's breakthrough in the space was that they could like do these tool calling loops and have agents kind of do longer running tasks that really no other platform was able to do. I think stuff like that is critical. Memory is critical. Like there's still a bunch of building blocks that I think like are leaving agents incomplete in the wild that I think we have to really sweat the details on before we move on.

7. 34:36

   So it's just like agents till the end of time until super intelligence and then we're just