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CRAFTED. is a show about great products and the people who make them. Top technologists reveal how they build game-changing products — and how you can, too. Honored twice by The Webby Awards as a top tech podcast, CRAFTED. is hosted by Dan Blumberg, an entrepreneur, product leader, and former public radio host. Listen to CRAFTED. to find out what it really takes to build great products and companies.
[00:00:00] Paige Costello: We're dogfooding stuff that is quite profound in terms of its implications for moving work forward together.
[00:00:09] Dan Blumberg: That's Paige Costello, the head of AI and co head of product at Asana. And on this episode, we're exploring what it means to ship products with AI, how AI will change the way work gets done, and how to organize your teams for success in this brave new world.
[00:00:25] Paige Costello: Because it's not deterministic, and you could ask the same question ten times and get ten different answers, that means that what you're shipping is going to be different every time someone uses it.
[00:00:38] Dan Blumberg: Asana is a work management platform used by thousands of large and very large enterprises. And Paige will tell us how Asana ships and measures the success of AI powered features that aim to take the drudgery out of work.
[00:00:51] Paige Costello: So we'll say like 80 percent of this was AI and I added my 20 percent just so people realize.
[00:00:57] Dan Blumberg: Plus Paige's thoughts on the future of product [00:01:00] management.
[00:01:00] Paige Costello: Now it will be more about like thinking, creativity, customers.
[00:01:04] Dan Blumberg: And her hope that these new tools enable us to get out of the building more.
[00:01:08] Paige Costello: It's so amazing what you can witness when you're in someone's space.
[00:01:13] Dan Blumberg: Welcome to CRAFTED., a show about great products and the people who make them. I'm Dan Blumberg, I'm a product and growth leader, and on CRAFTED., I'm here to bring you stories of founders, makers, and innovators. that reveal how they build game changing products, and how you can too.
[00:01:29] Dan Blumberg: CRAFTED. Is produced in partnership with Docker, which helps developers build, share, run, and verify applications anywhere, without environment confirmation or management. Docker's suite of development tools, services, and automations accelerate the delivery of secure applications. Learn more at Docker.Com
[00:01:48] Dan Blumberg: And CRAFTED. is produced by Modern Product Minds, where I advise companies on product discovery, growth, and experimentation. Learn more and sign up for the CRAFTED. newsletter at modernproductminds.com
[00:01:59] Dan Blumberg: [00:02:00] So I want to talk about AI and sort of two vectors: one is how you ship with AI and also I'm interested in what the customer facing AI experiences are. Maybe we could start with that. Could you walk us through a recent launch of an AI-powered tool?
[00:02:17] Paige Costello: Yeah, absolutely. So something we launched is status reports that can be written with the help of AI.
[00:02:25] Paige Costello: And status not just on your projects, but also on portfolios of projects and also on goals. And what's important here is knowing that like, people care a lot about sharing a good, high quality status update to their stakeholders, and Asana is used for visibility into progress. So this is at the core heart of what people are trying to achieve with Asana.
[00:02:47] Paige Costello: And so effectively, we created a feature where you can just draft the status update with AI. And in that, it's very clear about the progress that's made, what the blockers [00:03:00] are, what the next steps, it links to the milestones, it cites work and progress that individuals have made, you can go review the citations, and it's really astonishing how high quality the output is.
[00:03:13] Paige Costello: Then we evolved this at the portfolio level, because like, It's one thing to do it at a project where you're looking at the tasks and the comments and the back and forth there. Then to look across many projects in like a whole division or department. To do a status update on that is another level of complexity.
[00:03:31] Paige Costello: Internally we use AI status reports all the time and we write at the bottom what percent of our update was done with AI. So we'll say like 80 percent of this was AI and I added my 20 percent just so people realize that these are being generated with the help of AI, because even internally, people are still astonished by the quality and the output of, of this work.
[00:03:54] Dan Blumberg: If this feature is, is widely used, it presumes that all the data that is necessary is in Asana, [00:04:00] right? And so, cause I, I know the feeling of like, you know, some executive sees that your project is like, in yellow, you know, or God forbid it's in red, right? But it might be because, you know, you're blocked by some third party that you have no control over and like, and if that data is not in the thing that's making the summary, that, that could cause a problem.
[00:04:17] Paige Costello: Yeah. That's actually related to the fact that we don't detect the color. So we could predict, like, is this yellow, is this green, or is this red, but that is one of the things that we've kept our fingers off of and said, you, as the owner of this body of work, know best if the, like, maybe all the milestones are actually green, but you're going to mark it yellow because you're still feeling nervous about the launch because you think that scope might change, right?
[00:04:45] Paige Costello: And so, like, just because everything's green doesn't mean the whole body of work is green. And so that, that's a nuance. But I think it's, it's lost if we put too much in the hands of, of what we can automate. And so that's very, very top of mind for us.
[00:04:59] Dan Blumberg: Yeah. [00:05:00] Yeah. When I was at LinkedIn, I was on a team that was trying to get out of yellow.
[00:05:02] Dan Blumberg: And for a little while we called ourselves in chartreuse, uh, as a nice hybrid there of yellow and green,
[00:05:08] Paige Costello: lime green!,
[00:05:09] Dan Blumberg: yeah, exactly. We're making progress. We're going to get there. Um, at a few points in my career, I've been a part of either new product groups. Uh, or I've been part of the core product group while there's this new product group over there and we get a little jealous of them because they get to play with the fun stuff.
[00:05:23] Dan Blumberg: And I'm curious how Asana has organized itself and how you recommend or how you're observing your clients, how they're organizing around AI. Is it something that you recommend being diffuse and every team is using AI in lots of ways and the prototypes and you know a thousand flowers are blooming or is it best to have a central group that's doing it?
[00:05:44] Dan Blumberg: I'm sure the answer is it depends but I'm curious how you think about this this question.
[00:05:48] Paige Costello: I'd say it's pretty hard to take a scaled R& D function and just tell them everyone's doing it now because there's what you can do to become. [00:06:00] good at using LLMs in building a feature or like playing with it and understanding the capabilities.
[00:06:06] Paige Costello: And that's a whole nother thing to, to ship it to customers at scale and really maintain it and think about which models are you using? How are you evaluating quality, et cetera, et cetera. At Asana, we decided that like that zero to one gear shift was too much to demand of all of our teams at once. And we could go further faster by.
[00:06:25] Paige Costello: Selecting a group of teams, telling them that they're now the organization and they need to figure out the foundations and fundamentals for how we use a I to ship the sauna and use LLMs to make our customers more successful, and that meant that we were able to have clear focus, outline our strategy, be very intentional and then pull in other teams with very clear asks.
[00:06:50] Paige Costello: And then pull in other teams over time where they're more set up for success because they know, like, when I'm shipping, what do I need to ask myself instead of everyone [00:07:00] going to legal and saying, Can I do this? What about this? We're like, Whoa, don't go to legal. Here's the things you need to know. If you have anything that's not on this list, talk to this person and all requests funnel through them.
[00:07:11] Paige Costello: It just makes everyone faster and smarter together. And we're really happy with that choice. But it does mean that It feels a little bit like, Oh, what's the AI org doing? And so it takes a lot more work to do enablement and, um, kind of connect the dots on our strategy because our product strategy for Asana and our AI strategy are not different.
[00:07:34] Paige Costello: And so that's a little tricky for people to understand because it could be really easy to assume that there are two different strategies. There's one company strategy and we're, we're just assisting the organization to deliver on that.
[00:07:45] Dan Blumberg: Yeah. I've been a part of a couple of different teams where the mission of the team was to put ourselves out of business.
[00:07:50] Dan Blumberg: So when I first joined the New York times, I was on the mobile product team. Right. And like we needed to have a team who only thought about mobile and that team doesn't exist anymore at the times or probably most places, right. There are a [00:08:00] few, you know, there's, there's definitely specialists in Android or iOS, but you don't have a mobile strategy that's different from your web strategy.
[00:08:05] Dan Blumberg: Like you have a strategy. And so I imagine AI will be the same thing. I'm curious if there are. What markers you'd look for to say, you know what? This is no longer a special thing. This now can be diffuse, uh, among all teams.
[00:08:18] Paige Costello: Yeah. I think it's just, uh, a team sees the opportunity to apply LLM capabilities to what they're trying to do to solve a customer's problem, and they can just figure it out, like they're like, oh, I just use this and that and like we do some prototyping on prompt and I really like this output and now I know how to roll it out and I have confidence that I'm doing it within the expectations of how we ship enterprise software.
[00:08:44] Paige Costello: And that there just are, um, I was picturing like a, a bowling alley with the guardrails on. It's like everyone just, no matter what the skill is, can be successful. Because that is, is [00:09:00] what we need to have where people can initiate and execute to completion successfully.
[00:09:06] Dan Blumberg: Where do you think AI is going to change the role of, let's start with product folks, but it could be knowledge workers more generally, where is it going to change their jobs the most?
[00:09:15] Paige Costello: Yeah, I think AI is going to take a lot of the tedious tasks out of work. I do believe that the work PMs will do will need to continue to focus on need finding and really doing like hands on user research, because as much as you can do lit review style research much more quickly than you ever could before, the quality of the insight will vary.
[00:09:41] Paige Costello: And so PMs are still going to be responsible for. Like sniffing out what the best opportunities are and like being surprised by being really close to customers and watching them do their work, use the tools, et cetera. Um, I think also that PMs are going to have to figure out how to get [00:10:00] comfortable with security.
[00:10:01] Paige Costello: With the stochastic outcomes of AI powered features, because what will happen is all of our software solutions are going to be much more personalized. And so reading an A/B test isn't going to be so straightforward because everyone had a different experience. And so that's what we're going to do.
[00:10:19] Paige Costello: Figuring out how to define quality, how to evaluate what you're shipping, um, is going to be a really new and interesting challenge as all products become more underpinned with LLM technology.
[00:10:32] Dan Blumberg: Can you expand on that some more? What you mean by getting used to the stochastic nature of AI? And because I know, I know that's like, it's, some people see it as a bug.
[00:10:39] Dan Blumberg: Some people see that as a feature. And I'd love for you to expand on why that's something we have to understand to use it well. Yeah.
[00:10:46] Paige Costello: Yeah. Yeah, absolutely. So because it's not deterministic and you could ask the same question 10 times and get 10 different answers, that means that from a product perspective, what you're [00:11:00] shipping is going to be different every time someone uses it.
[00:11:03] Paige Costello: And your ability to evaluate the success or quality of that will be determined. Even more complex than it is today. I think it's, it's hard actually to like read between the lines today. We can know if something wins or something loses. We can know if the results are neutral. But why is missing? So the quant versus qual is how we are trained to think about our releases.
[00:11:26] Paige Costello: But when you think about the future of what LLMs do to our technology, we're putting in customers hands. We need to get more creative about like articulating what success looks like, and that actually is going to be built into how we ship. So at a framework level, you can expect teams to start building with different quality suites than we built with before, where PMs are going to be responsible for articulating the success criteria for really checking that the prompt is working as you'd expect most of the time.
[00:11:57] Paige Costello: And so getting a lot closer to the [00:12:00] actual implementation. And the performance at that level, as opposed to, you know, the highest level outlining or specking of the work and then reviewing results weeks later.
[00:12:11] Dan Blumberg: Is there a specific way that that played out with the launch of, say, the smart status that we were just talking about?
[00:12:15] Paige Costello: Yeah, absolutely. At the very beginning, our PMs were truly going through spreadsheets and, and runners and saying like, Oh, What were the answers and how would we say that that was successful and grading them on like answer quality, answer accuracy, and each feature had different things that we would be looking for in the output, like what we needed from a status update is different from what we needed from a task summary.
[00:12:41] Paige Costello: Say if you had a task with 50 comments and you said, tell me what's the back and forth, what's this all about? The result on that is going to be different intentionally than the result on like a project summary or a status on a goal. And so each of those required like [00:13:00] very careful thinking on the part of the PM about like, what does good look like here?
[00:13:04] Paige Costello: And how do we build that into the system? And then we eventually like net, there are now, startups trying to do this. I believe that the model companies are probably going to try to build their own, probably fit for purpose evaluators for each model. But if you're at a company like Asana, where we're using models from Anthropic, models from OpenAI, and we want to maintain flexibility about what our customers need and want to work with and the quality of those outputs that requires a lot more of thinking about our frameworks and and our layer of how we engage with that to make sure that what we're putting in customers hands is really the best we can put forward.
[00:13:46] Dan Blumberg: This gets a little bit meta, but are you experimenting with one model, checking another model and all the time you, you mentioned like the human qualities of the PM looking at the output of, is this a good status report or not? Can you also then, or maybe you already have built [00:14:00] a model that takes that product sense for lack of a better term for it and looks at the model output that gave the status update.
[00:14:07] Paige Costello: Yes, we've created numeric scoring and categories and then built that into how we ship so that a PM doesn't have to use a spreadsheet. Yeah. And that's, that's changed almost every three months since we started working more heavily here.
[00:14:26] Dan Blumberg: I hosted a panel recently, an episode of CRAFTED.,. all about the title was from prototype to production.
[00:14:31] Dan Blumberg: And it was all about ways, you know, engineering leaders, product leaders are, are prototyping with AI. And then some of the questions that come up as you decide, like, can we scale this? And those questions might be costs. They might be legal. They might be, does it work? Is it predictable enough, keeping in mind that it's never going to be truly predictable.
[00:14:48] Dan Blumberg: And I'm just curious if you could give some of the consideration set that you have, questions you ask when deciding, does this generative AI powered prototype, you know, is it ready to ramp? Is it [00:15:00] safe to ramp? Is it not going to cost us an arm and a leg if people use it at production scale, et cetera.
[00:15:05] Paige Costello: I think a good portion of the value of a prototype is just doing the prototype, and you can very quickly find that you get to 70 percent way faster than you would with traditional product development.
[00:15:17] Paige Costello: But taking something from 70 percent to 100 or production ready takes way longer than you expect. And so it's a bit counterintuitive and challenging to get into the, into the flow with working with AI bringing that to customers. I would say that The biggest way that we find we have confidence in that is just rolling out to ourselves, dogfooding, rolling it out to an alpha group, rolling it to a beta group and then rolling it to production and having a really systematic feedback loop for.
[00:15:52] Paige Costello: Evaluating quality from the customer's perspective. And so we do have a thumbs up, thumbs down. We, uh, um, do quite a bit to [00:16:00] evaluate is the feature at a certain level of threshold for its value that it's creating before we ship.
[00:16:07] Dan Blumberg: I'd love to dig into more of how you're using AI internally, whether you're launching any kind of feature, just what, what are some of the ways that it's really accelerating product squads?
[00:16:16] Paige Costello: So Asana employees use AI in a few different ways. One is they're using AI through Asana, because we very heavily dog food our product for all work. We don't use email. We exclusively use our product. The next zone where I would say we use it is like, People are using ChatGPT or Cloud4Work, like, they're definitely going straight to the model consoles.
[00:16:40] Paige Costello: We also have a lot of internal projects that are using AI and embedding it in Asana that we're very excited about. If you think about the way work moves forward, it's not linear. You might work on a project and then get feedback on it, and then you need to consolidate that feedback and [00:17:00] do a rev on it.
[00:17:01] Paige Costello: We're really Playing with internally all sorts of workflows that use a I to identify what's missing or what could happen next like that moving through the system and preference for how work happens is really core to how Asana is built and how it works today. And so while Our existing AI features are primarily, um, at the other work level.
[00:17:27] Paige Costello: Right now, we're exploring, um, and building quite a bit around, like, how scaled work management happens with AI at its center. And we're dogfooding stuff that is quite profound in terms of its implications for moving work forward together between humans using AI in the context of Asana and just reducing the amount of tedious work that happens around, um, like bug triaging, for example, or preparing for a phone call with a [00:18:00] customer.
[00:18:00] Paige Costello: These are the sorts of things that with AI, uh, you can do it much more. Efficiently and with much more confidence. And Asana gives a place where that can be done in a way that's structured, reviewable. Um, and that's, that's really exciting.
[00:18:16] Dan Blumberg: You said some of this will lead to really profound use the word profound changes.
[00:18:21] Dan Blumberg: I love it. You can unpack a little bit of what you have in mind when you say that.
[00:18:24] Paige Costello: Yeah, this goes a little bit to the experience for everyone can be different. But when you think about custom workflows, Every organization has probably figured out their own like bug process, right? That same process for like work intake for a brand campaign or a marketing campaign.
[00:18:46] Paige Costello: Every company has things that are similar but different. And so doing these custom workflows across groups, across teams, today happens With a lot of elbow grease, like people [00:19:00] write scripts and they like connect systems together and they're hard to change and they're hard to evaluate and they require people to say like, Oh, this bug doesn't have enough information.
[00:19:12] Paige Costello: Can you like help us reproduce and give us an image about it? Like it's really manual. Um, and so what's exciting is when you take automation or workflow processing and you put. AI within it, you're able to make that whole process make more sense. You're able to move things through that system more quickly.
[00:19:35] Paige Costello: Um, you're able to even review what's not working about the system. So we're going to be in a position to say like, Okay, this step is a bottleneck. Only half of what's coming in here is ready to be actioned on. Like you should change the form that's upstream of this so that you get better results and you're not slowing your teams down.
[00:19:56] Paige Costello: And that's the exciting part is I think [00:20:00] No one wants to be doing this flavor of work. It is what's required to do the fun stuff about work and, um, creating really custom AI powered business processes that move work forward in complex organizations faster is going to create so much value for so many customers around the world.
[00:20:20] Paige Costello: And I mean, our customers, but I also mean their customers. And so that, that feels really exciting.
[00:20:26] Dan Blumberg: That also sort of gets to the sort of scary part. You mentioned that a lot of this takes a lot of elbow grease, you know, humans have elbows and if an automation is just doing it, right. So the question here though, and that's a big issue, right?
[00:20:37] Dan Blumberg: That automation for, you know, centuries has displaced people's jobs. What are some of the new skills new jobs that people should be preparing themselves for now?
[00:20:47] Paige Costello: Yeah, I believe that we'll still work like there will be a good portion of people that still work just as As many hours in the day, they'll be just doing different things during those hours um, [00:21:00] because And the human appetite to make an impact and do good work is, I think, core to many people who have jobs in product.
[00:21:10] Paige Costello: And so when I reflect on like what new jobs will exist or what will people need to do, it's more about. Using AI to be higher impact individual and to work smarter and to work faster and work more creatively and unlock things that you would have had to work through three people to do, and it would have taken a week to be able to do that in 10 minutes.
[00:21:32] Paige Costello: is not really a job change. It's an acceleration of the type of work that you hoped you had signed up for at the beginning. Uh, I do think there will be new jobs like AI ethicists and like people who are responsible for like how AI is used in rolled out companies. But from a like core product role, I think that PMs will continue to be valuable, but maybe spend less time on parts of the job that [00:22:00] were more about writing in detail, and now it will be more about like thinking creativity, customers, and spending time in terms of the quality of the output.
[00:22:09] Dan Blumberg: Yeah, I interviewed Janna Bastow recently, the founder of Mind the Product and of ProdPad, we're talking about this exact same topic and joking that like AI is going to do everything and like we can put our feet up and like that's never proven to be the case with any new technology. Humans like find a way to work more.
[00:22:24] Dan Blumberg: But she also said AI is going to take a lot of the repetitive jobs away from from product folks, and it's going to enable them to get out of the building more. At least that's her hope. That's her dream. She's like, or they might just make more excuses for not getting out of the building and do something else.
[00:22:40] Dan Blumberg: And so I'm curious if, uh, if you think that's truly the unlock that gets product folks to even more so, you know, talk to customers, do the things that, you know, humans are truly outstanding at, uh, or, or do, do we find new excuses to not do so?
[00:22:55] Paige Costello: I can only hope that's when the job is that it's most fun and it's most [00:23:00] impactful.
[00:23:01] Paige Costello: So I can only hope so.
[00:23:02] Dan Blumberg: I don't know if there's a customer interview or an experience you had where you said that's the most fun part. I'd love if you could share why is that the most fun part? What is it that like got you to feel that way?
[00:23:12] Paige Costello: Yeah, absolutely. One customer interview I had, uh, at Intuit, I was looking at how our invoicing worked and invoice design and customization and how people were billing their customers for the work that they were doing.
[00:23:27] Paige Costello: And I went to a, an autobody shop and I watched them invoice and I looked at their paperwork, the way they were printing invoices, what they were trying to achieve, and there's nothing quite like standing next to someone and seeing. is happening. So it's like, Oh, is that thing on the wall actually how you're clocking in and how employees are managing time?
[00:23:50] Paige Costello: What are you doing here on, on the desktop? What, what time of day are you doing this? Like, Oh, what's this thing on your desk? How are you like, are you doing that as well? Why? [00:24:00] And so there's so much that's outside of what you can record. record in a, like, user testing session. I think a lot of people are like, oh, if I just like have someone play with this flow and I record their reactions to it, that's good enough.
[00:24:13] Paige Costello: And I think that's so, uh, limiting. It's just such a narrow view into how people are interacting with your tool in the context of their ecosystem of daily work. And so that, that's a memory I have that really stands out. I think also. What people say and what people do is so different and you can't tell that very well.
[00:24:36] Paige Costello: Uh, when you're doing a video recording of, of them engaging.
[00:24:40] Dan Blumberg: Totally. It's funny. You mentioned, uh, an auto mechanic. I was at my auto mechanic last week and he uses sticky notes to organize his work and he wrote a bunch of things down and then he, I forgot how it came up, but he showed me his system, which is, he has like, you know, Sticky notes for cars that just came in, cars that are in progress, cars that are waiting for [00:25:00] the customer to phone call, cars that are done.
[00:25:02] Dan Blumberg: And he, and he literally picks up the sticky notes and moves it over and then moves it over. And I was like, you have a Kanban board. And he had no idea what that is. And I was like, it's actually a car thing. It came out of Toyota like years ago. It's actually, it's actually like we use it in technology now.
[00:25:13] Dan Blumberg: And he was curious about it. I don't know if he's your target customer with Asana, but he's using a very similar process. And I loved, I love seeing it just laid out right in front of me there.
[00:25:21] Paige Costello: It's so amazing what you can witness when you're in someone's space. And so I couldn't agree more that I hope our PMs get out of the building.
[00:25:32] Dan Blumberg: When you appeared on Lenny's podcast, you mentioned you were building a PaigeBot. And I'm curious how page bot is doing. What can she do? What can't she do? And what do you really wish page bot could do?
[00:25:46] Paige Costello: Oh, man. Um, I have a board admission on that. Mostly because it was mostly for playing, just to see what is possible, what, what context you can give an LLM, what you can [00:26:00] ask it, what, what output you can give out.
[00:26:02] Paige Costello: I'm finding that I'm writing a ton of docs and working with my teams about our product direction and that is taking so much headspace that is more at the intersection of like, Where is the market? What are Asana's unique capabilities and what can we create for our customers that is beyond most people's wildest dreams?
[00:26:27] Paige Costello: And that's what we're It's just taking so much headspace. I would say I'm not playing with my own bot at the moment
[00:26:36] Dan Blumberg: What what if you were?
[00:26:38] Paige Costello: Yeah,
[00:26:38] Dan Blumberg: what do you wish PaigeBot could do or if not PaigeBot per se? But what do you wish I do for you that it's not doing for you today, but you think it could in the future
[00:26:47] Paige Costello: Yeah, it's, it's a bit meta because Asana works on work management and enterprise work management and solving the problems that knowledge workers have around cross functional [00:27:00] work and the plan and having shared purpose and being able to visualize progress.
[00:27:06] Paige Costello: And a lot of those problems are problems I myself work on. want AI to solve. There are so many problems that are going to get solved really quickly around, um, having AI be like a great EA or chief of staff and support you in like your meeting rescheduling and like preparing for a meeting and knowing what's on, um, On deck that could be moved or like relative priority across people and groups.
[00:27:34] Paige Costello: But I, I think some of the biggest problems are really like what's most important, um, to be doing and how to work across people and, and how to stay organized and on top of what's happening. And so that's, that's really what I want AI to solve.
[00:27:53] Dan Blumberg: Last question. I love stories of I did X and I never thought I would apply it to my work and, you know, [00:28:00] in the, in the world of product or AI.
[00:28:01] Dan Blumberg: And I'm curious if there's a, an experience from, you know, whatever number of years ago that is, is, is helping you be better at your job that you never would have predicted would, uh, would do so.
[00:28:11] Paige Costello: I have a liberal arts degree, and I think having the critical analytical thinking as your foundation is just something that scales to all sorts of interactions around thinking about problems, around prioritization, around trade offs, around, um, what's happening in the world.
[00:28:30] Paige Costello: And it's, it's been so useful, uh, to me in my career and just in my daily life.
[00:28:37] Dan Blumberg: So I'm going to bring this all full circle here. I'm a fellow liberal arts, uh, college major, uh, with AI, we're not going to be like, Ooh, you don't have an engineering degree. That'll be, that'll be less of a thing. I think going forward, you agree with that?
[00:28:50] Paige Costello: I do. I mean, it's
[00:28:51] Dan Blumberg: self serving for us supposed to say that, but like, but, but like the critical skills you talked about are, are even more important now. Uh, whereas, you know, [00:29:00] like learn to code is probably still important, but a little less so than it was a couple of years ago, I think.
[00:29:05] Paige Costello: Yeah. And those become more accessible over your entire career journey, whereas that like foundational ability to challenge and think and be creative is, is going to become more, more of an asset because you're going to be able to do more things that you wouldn't You would have needed a degree to engage in at even a cursory level before.
[00:29:28] Dan Blumberg: Awesome. Paige, thank you so much. I really enjoyed this conversation. I also will say thank you as well. I am nowhere near your target customer. I don't have 120, 000 employees, not even close, but I have used Asana since like 2011 as a personal task management tool. So it's, uh, it's something I use every day and I appreciate the work that you and your team are putting into it.
[00:29:48] Paige Costello: Wonderful. Well, if you haven't played, I know you've played with it lately, but I, I also have used it in past jobs and the difference in what the product looks like now from what it looked [00:30:00] like when many people gave it a try is quite exciting. I'm, I personally worked on like rolling out the goals product.
[00:30:07] Paige Costello: So we support OKRs. have been really focused on, like, the, the intersection between strategy and execution. It's been really fun to expand what it's able to do.
[00:30:21] Dan Blumberg: That's Paige Costello, the head of AI and co head of product management at Asana. I'm Dan Blumberg, and this is CRAFTED., a show about great products and the people who make them. CRAFTED. is produced in partnership with Docker, which helps developers build, share, run, and verify applications anywhere without environment confirmation or management.
[00:30:41] Dan Blumberg: Docker's suite of development tools, services, and automations accelerate the delivery of secure applications. Learn more at docker. com. Docker dot com special thanks to Artium where I launched CRAFTED.. Artium is a next generation software development consultancy that combines elite human craftsmanship and [00:31:00] artificial intelligence.
[00:31:01] Dan Blumberg: See how Artium can help you build your future at Artium.
[00:31:07] Dan Blumberg: And CRAFTED. Is produced by Modern Product Minds, where I advise companies on product discovery, growth, and experimentation. Learn more and sign up for the CRAFTED. Newsletter at modernproductminds. com. Please share CRAFTED. With a friend, and if they don't remember to subscribe, leave them a sticky note.
[00:31:25] Paige Costello: Oh, what's this thing on your desk?
[00:31:27] Paige Costello: Are you doing that as well?