00:26:22 · Dan Rogers
[00:26:22] S0: Yeah. Know. So it's a great question. Question I ask myself quite a bit actually. The way I make peace with it both for myself and then how I kind of... Mainly for myself and then I'll describe for the team. So for myself, it's very much control what you can control. It's very much a be very peaceful about are you doing the right things? Are you following the right processes? Are you building a high performance team? Are you are you building the right products? Is roadmap headed right direction? So you can... Think you can create a great internal story for yourself about whether you're doing the right things. I watch tennis, I don't know if you watch tennis, but I just watched the US Open and a lot of the tennis players that don't break through in the grand slams you know, to still tell themselves a story about are they doing the right things? Are they doing the right motions? If so, that's great. Then that alone is great. And you saw, you know, someone that just haven't haven't won in ten years, just won two grand slimes in the last three months. But because they, you know, had that mental mindset of celebrating the actions, celebrating the journey, and the outcome will follow. If you're, you know, confident and have that self belief and know that you are doing the right things, the outcome will come. So I think that's the internal, you know, maybe talk track. Vis a vis the company, it's about finding those wins that may or may not be in the short term stock related. Over the medium term and long term, I think, you know, stock does become a great barometer. In short term, can be, as you say, very affected by macroeconomic circumstance. So you need another barometer. Stock price alone is not enough, and so you have to create those parameters. What are the things you are going to celebrate this quarter? And so today as an example is a big celebration day for us. It's a big launch day. It's really the launch of moving from what was collaborative work management to agentic work management. That is a major milestone that we are going to be partying a lot around today. It's a big deal for us. And we know that that is a landmark for us doing the right things. And you know, how that gets represented in the stock market, you know, on a given day, who knows? But we know we're doing the right things and we're doing the right things for our customers.
00:28:34 · Guillaume Moubeche
[00:28:34] S1: I forgot which investor was saying that, I think it was someone at Sequoia, but they were saying like, when they look at a company, they always ask themselves if any of the frontier model is getting better, is that company more valuable or less valuable? I think like on your side, you've integrated with many models, etcetera, but how exactly like do you like build kind of your moat around, you know, like this model that can get updated and at the same time also bring more value to your customer?
00:29:10 · Dan Rogers
[00:29:10] S0: Yeah, it's interesting. I'm glad that someone from Sequoia said it, because I say the same thing. I think that's really the, you know, the say is the test is like, the models will get better, and is that a good thing for you? And so the way I kinda think about it is in the next phase, the piece that AI is gonna be doing, yes, they're gonna be generating very impressive answers. Right? And they're gonna be generating very impressive code and that's great. But the models are becoming somewhat interchangeable. The value that's gonna be created is turning that intelligence into action inside those workflows in a company. So for an AI agent to be useful in enterprise, they need first and foremost context. So it's like, what's the company trying to achieve? Who owns that? How has this been done in the past? What's already been decided? Which systems do I need to work with? Are there any rules of the road I need to follow? Which knowledge base should we use? Which teams do I need to involve? Then it needs a harness, so context plus harness. Harness is this kind of coordination work, is taking action, involving those right people, making sure the sequencing is right, making sure that it's all governed, observable, and trainable, and improvable. So the enduring value for Asana and for enterprise AI is not gonna be in the raw output of the models, which is going to get better and better. It's actually how do you turn that intelligence with the harness into repeatable, useful, accountable process that makes the work flow. And so for me, it's a very easy answer to that question, which is Asana is on the right side of this equation. As the models get better, we will get better. And you see that in the performance every day of, you know, our AI teammates. You see it in the performance every day of our AI chief of staff and slew of new products that we've launched today for IT service management, which we call ASM, for r and d teams, which we call command, for client delivery teams, which are calling Asana client management. We have created bespoke solutions for them. There is the workflow and the harness against the things that they care about, the jobs to be done that they care about the most. And as the models get better, all of those solutions are gonna get better.
00:31:29 · Guillaume Moubeche
[00:31:29] S1: And do you feel like with the open source models getting like closer and closer to the frontier lab, that the LLMs in general, like are gonna become a commodity and that price will eventually go down? Or do you feel like eventually like companies like OpenAI and Anthropic, because they have such a also like high valuation and necessity to increase their revenue, like they're not gonna be able to drive the cost down to a certain extent, and they will have like to maybe like diversify a little bit like their source of revenue. So how do you see it like from a strategical perspective, like do you feel Anthropic and OpenAI can eventually become competitors? Or do you think that, you know, like with all the open source model, you'll be able, as you mentioned earlier, to eventually like switch when needs to be and that's it.
00:32:26 · Dan Rogers
[00:32:26] S0: Yeah, maybe I'll answer it a few ways. So the cost per given quality is already going down dramatically. And so then I think for us, you know, the model is like the fuel in the car. And so you want the most performant fuel for a given price. And so you can change the fuel, you can go to a different gas station, change the fuel type. That's really how we think about it. And so for Asana, our equation is going to be not just what's the cheapest model because we want the highest quality outcome for our customers too. So for a given quality, what's the right mix of models? Some models are gonna be better at some task types, some models are gonna do other task types. So that stratification of models, almost like the, I guess, you know, the gatekeeping of this model goes to this, I think is gonna be a real competency for many companies. And on the kinda who wins maybe question that you had there, you know, I think there's room for all of the players, and we actually have different relationships with all of the players. You know, with Anthropic as an example, where they're really becoming strong distribution for us, it is a way that people are going to discover Asana as well. And, you know, some and many of these companies that you're mentioning are Asana's customers in turn because they also need to coordinate their human agent teams, and they find us to be the best multiplayer coordination ledger. So I mean, times for us. The great part about where Asana sits is it doesn't really matter to us which model prevails as long as the cost quality keeps improving of those models.
00:34:00 · Guillaume Moubeche, Dan Rogers
[00:34:00] S1: Makes a lot of sense. I like how on every question I ask you, always go back, you know, to the same principle of making your customers happy. Like I'm simplifying obviously, but I think it's great and it's super important like to go back to that foundation and that essence of highest quality possible for our customers, and then we'll deal in the background with the rest. [00:34:22] S0: Yeah, know, if I think if that's your North Star, a lot of decision making becomes very easy. [00:34:27] S1: Yeah. And as a CEO, I'm sure like in the last eighteen months, you've had like also like ups and downs. I was wanting to ask you, what was the hardest time for you or like problem that you had to solve since you joined? [00:34:41] S0: I think the piece I love is suspending, it's almost like you've gotta have this mastery of your own mind. So suspending everything that you know in order to stay clean and let the mind absorb new things. And so I think it's very easy to, I love kind of what your Jeff Bezos quote is, I need to look that one up. But it's very easy to let your past successes dictate your future. And I'm very mindful of not allowing that to be the case. So I almost have to have a, certainly in the beginning, a bit of a ritual of casting aside everything I knew and then really being very curious with myself about how I was reacting to things or how I was interpreting things.