It's Friday: Juan and Tim rant about AI, Agents, and the Uncomfortable Truth About Data's New Center of Gravity

Hey everyone. it's your special edition rant Friday rants of cataloging cocktails with beers cheers beers and although I want to say beers and BS but we're not BS beers and no BS how's it going Juan? great Friday it's hot already I wonder how long we'll be able to do this outside it's becoming summer there's a couple of inside places here at Lazarus what are you drinking? Oh, it's hot. They're prodigal pills. Prodigal pills. This is great. They're classic ones. I'm drinking the Covenant Kulsch. Oh, that's how they're good. Yeah. Well, cheers. Cheers. All right. So, what's on our mind? What's on your mind today, Friday? Well, first thing is you were at the TED conference. Was that last week? That was last week, yeah. Yeah. So I just I just published a post, my kind of summary of kind of on the AI sides. And in a in a nutshell, kind of everybody's thinking just because AI is all over the place. So many people are constantly here. Oh, this is like electricity, like these innovations happen. And we've had all so the jobs will be lost, but jobs will be gained. We've seen this over and over. Everybody's saying this. I agree with that. Yeah. But I think what people were saying that are actually not acknowledging the speed that this is happening. And this is the unprecedented thing. Yeah. It's not like overnight, like click your fingers and everybody had electricity. It took a long time. But here, overnight, there is this stuff happening with AI. And literally, we're starting to go see a bunch of layoffs and things are changing. Or at least the layoffs, people are blaming it on AI. so so but either way right yeah yeah so i think what i found interesting is ai is doing so many amazing things and like i we are definitely going to cure cancer a bunch of diseases in our lifetime like that's happening like it's just amazing that what we're seeing with stuff like imagine the impact on research yeah i mean just like imagine having your generative models that you can instead of like typing it returns human language it's actually going to type in and it's going to return me molecular cellular language stuff that we don't humans don't understand and that's how we're going to be able to kind of figure out the next possible things we're going to go test out for diseases like that's happening but then we can use ai for doing like more crazy surveillance stuff and things like there's this whole spectrum of things that can happen but what i really found interesting this is kind of the thought that i'm kind of constantly going through my head right now what i want people to think about is how ai is really is a forcing function for us to really rethink what humanity means. And I think we're advancing, we're starting to think about what are the things that we weren't doing before, we can do now because of AI, and how that combines with other things we do makes us more human or reconnects to stuff that we've been losing because we're focusing so much on AI. A couple of examples. It's like the thing that comes to mind, And I don't know if people have been looking at AI videos and music and art. So there's one artist called Kelly Bosch. And when you see her videos, it's surreal. It's like, how were you able to go create this stuff? And what she was saying is she's an artist. And AI has helped her tap into some creativity that she never even thought in her lifetime she was able to go do. so the people are so i think this is the opportunity to really start thinking about stuff that we have never ever thought about now that's still about creativity you're and you're you're providing uh uh things to humans that were that were entertainment to humans that's what's connecting connecting to us and at the end of the day you're like finding things that ai is helping us but it's in combination with other human things which the combination of the two things are going to make us super super powerful and and happier in a way too yeah uh the problem is if we just isolate ourselves just to the AI part. And I think this is the time we should start thinking about it. Yeah, no, I think that's super interesting. I mean, those are some of the positive things that can help, right? Like being more creative, being more productive. And one interesting thing I saw in your write-up was, you know, this gets a little more philosophical, kind of the nature of consciousness and what makes us human. And I, you know, I think for the last few years and longer, right, we've been talking about like, oh, like the singularity and like artificial general intelligence and artificial super intelligence is like as it becomes so smart it's just gonna you know become conscious right um but it's interesting to see that some of these folks at ted and you know elsewhere are talking about like hey intelligence and consciousness are not the same thing and uh just because something is smarter doesn't mean that it becomes all of a sudden self-aware right so it's and i find that interesting and it it forces us to think a little bit about what does it mean for us to be humans like is it just that we're intelligent that makes us human or is it the fact that we have feelings or that you know you know we have to eat and we have to pee and we you know like you know that makes us human like yeah it's interesting i think part of it also it goes back to this it's the social connections and the social connection it's being able to understand other people and and hear them and saying oh i i understand your worries and i'm listening to you um so i think that that that that's where this is the opportunity to really start thinking about kind of okay all this happening right now but like wait how am i going to take all this ai everything's happening with ai what are the what are the things that we really want to accomplish as humanity and combine these two things together to say oh here's how we all really kind of unleash the best out of us there's gonna be bad things that's gonna happen too but i think the rational optimist to me is that there's gonna be more positive than negatives around that um where there's a lot of things we're not prepared we're not prepared for a lot lot of stuff i think we need to prepare ourselves super fast like like education needs to change like the way the way we do education today there's one and done like oh you go to school and then you go to work and it's it like you need to we need to reskill ourselves all the time like if these systems get powerful powerful what we're doing today like you don't have to do that anymore then there's the next thing we need to go work on so we need to be we need to be able to kind of train ourselves and what are the systems that enable us to go train ourselves and so forth yeah yeah how do you constantly be learning and as ai gets better or things get more automated that you were like, okay, you were doing that, but now that's automated. Okay, now you move on to the next thing. What's the next thing, yeah. And that's constantly going to keep happening right now. And it's going to be faster and faster. And it means that things like college, like going to college for four years and picking your career for the rest of your life, right? It's going to start to become, like, is that really the thing, right? And I think that's where we need to rethink about. We rethink the entire educational system, like even the incentives, because if you look at universities and how the systems that incentivize them is enrollment. Oh, enrollment is going up. But we should be really as keeping track of the outcomes. Like, okay, these students enrolled and what are they able to go do afterwards? Yeah. Right. So I think a lot of that is happening. And we're also entering, we do the analogy with like YouTube, right? So we're entering this, what we're calling, I'll call it the post-YouTube era, which is before YouTube, you can only look at videos and movies by trained filmmakers. but then suddenly with YouTube anybody can become a content creator and people are doing that and now with AI with agents and stuff like before only software engineers could build software now anybody can build software yeah right and and there's a place for that you don't need to learn Photoshop anybody can create an image right so so I think we're entering we're entering that new world and I think that's uh we've seen this stuff too right so but I mean it's much at a it's at a much faster scale for that so was there was there anything that you saw Ted that changed your perspective about the world of data? No, I think this was, or was it more validation? This was, I mean, this was more about kind of focusing more on the humanity. So for me, what I'm thinking about when people work in data is what are the, what are, what are your special, what's your special sauce that you can now augment a lot with, with AI that you can focus on. So I think is I tell people like right now is super important to be able to go focus on almost like pick your basket where you want to put your eggs in. Like focus on a particular industry and a particular domain that you want to kind of learn more. I think it goes back into Bill Gurley was saying this. It was like continuous learnings. People get fascinated about the topic. Like those are the ones who really shine and have that continuous learning. So like take your data expertise and be able to apply it into a particular domain where you find fascinating yourself. and then you take that fascination with your expertise and I think that's going to supercharge you. So I think those are, and again, AI is a fantastic way to go to learn more, use that as sort of advantage. Yeah, and if you become obsessed about something or interested in something, you can dig into it and become productive in it a lot faster right So it interesting Well a lot of things So I post there kind of our takeaways there Yeah so check out Juan post about TED And then I know one other big topic that we've been talking about this week is how is the world of data kind of evolving, right? And in a world where AI really is at the front, is at the fore, right? How does that change the way that we approach our data architectures, the way that we approach what our data teams are focused on. So why don't you talk a little bit about what you're thinking there? So we gave a talk at a customer invited us to give a keynote at their summit where we're presenting kind of our point of view of we've lived in this world where everything has been data at the center. so data is the new oil we need to be data driven and democratize data big data put all the data together the data literacy right and and all these topics have been at the board level yes what are we doing about data now obviously all that's shifting now what are we doing for ai and then what has been the thing in the last couple months is like everything is now knowledge and context and those have been kind of the center of of of where all our world is and our And what we've been arguing is like we need to kind of this Copernicus shift was like, wait, we're not saying that isn't important, but the real center of the world where data orbits around and knowledge orbits are in contact is really about the work that needs to be done. Because at the end of the day, why do you do data? Why do you put all this context together? Why are you why are you doing all these governance? Why are you generating all these insights? but so you can do your work right it's and and work is at a high level i need increased revenue reduced risk right and reduce costs mitigate risk all that stuff but very specifically there's decisions that need to be made like i as the salesperson needs to be able to get all their data in person right before that call so they can have every there is a an it issue that's happening we need to be able to resolve that because they need to get risk run that customers are complaining about something how can we deflect those issues as fast as possible and so forth like that's the type of work and you need to be able to bring in the right data, bring in the right context over to be able to make the decisions to do that work. And I think that's the shift that we need to go have. But I think also it's kind of like cautious right now. Everybody's talking about context and I'm like seeing things like, Oh my God, with agents, we can now generate all this context. We generated a million different descriptions of things. And I'm like, okay, quantity versus quality, my friends. Like what the heck? We can tag the shit out of stuff now. Yes. And so what, What is the outcomes you're driving to? What is the work that is going to be accomplished because you're able to go do all that type of stuff? And I think that is the shift that we need to go have. And I think people are having these conversations and people are realizing, yes, that that should be the focus. But then when the rubber hits the road, the question is, wait, but how do I get there? What is the maturity step to get there? If I finally get my data lake in place, now you're telling me we've got to move our, you're moving my cheese again. Well, I think this is very uncomfortable, this idea for data people. I think maybe a little less uncomfortable for like a data leader. Like I hear more and more data leaders talking about like, we've got to get in line, you know, we've got to get aligned with the business. We've got to drive decisions. We've got to drive impact and action, right? But like, I think especially for data teams, there's, you know, we just finally, like we did this whole big data thing. We did this data lake and the data lake house and everything like that. And like our machine learning, all this like happened and like our surface area expanded so greatly from just like, it used to just be like reporting in a database, right? So the surface area, and we finally kind of got it under control, right? We're like, okay, it's not a data lake. It's a data lake house, right? It's not a data swamp. It's a data mesh. It's, you know, we're going to create this fabric, and we're going to have these data products, which could be APIs, could be data sets, right? And we're going to have some dashboards that we own centrally, and semantics we own centrally, but there's going to be some that the business, but we're going to call that, you know, raw or bronze, and the good stuff, the stuff that we manage is going to be called gold, right? And so we finally kind of got it under control. We have a scheme here. And you're like, wait a second. You're telling me that none of that matters? Well, no. So I would say that all of that. I'm being a little bit facetious here. But you're telling me that all that matters is I have to help the business decide how to sell more and how to cut costs? Yes, that's what I'm saying. But I also have to acknowledge. But I don't know about that, so. But we have to acknowledge, depending on your organization, right? Yeah. how big an organization is. They can have so many different levels that people who are working at the data, they are so disconnected to them, right? And that's something we have to acknowledge. Nevertheless, I do believe that this is kind of a leadership, leadership needs to run to be able to make sure that those connections all the way from the boots on the ground who are actually doing the work, understand how this all gets connected to the, at the end, the objectives and the business value. So that's one thing that leaders need to be able to connect the dots all the way up. But I think what's important is like, everything that's happening is a foundational work. And one thing that I'm now just thinking about, we can use this time to riff, is what is the next step after a medallion? Or I put my data in, I'm able to go clean it up, and I have my gold, I have my dashboards. Okay, so what's next? And I think, I mean, I've had some unclear thoughts right now, but I think that's what we need to start thinking about more. It's like, what is the, let's call it the Medellin architecture 2.0, which I would believe that it's like, it's going to be more about driving insights to action. So it's like, okay, you put all this data together and you have, you're generating these insights and analytics. What are you doing with that? Right. And I think that's one thing, driving insights to action. Another thing is about more on the contextualization is like, there's multiple versions of the truth. How are you managing all those different versions? Because these agents will need to be able to have that context to understand how to make those decisions and how to act. Go back to insights to action. And then I think another aspect there is like the feedback loop. I think when you look at data architectures in general, they lack a feedback loop. And I think now is a time where if we're going to unleash things to go see, just go do it on your own, agent. I still think keep track of what you're doing and get feedback around that stuff. And if humans are too much involved, that's feedback too. They need to go saying, all these humans are about to go say, accept, accept. You can probably at least that more. So I think that's kind of where my mind is heading with this. So in this world, you probably have a new kind of data product, right? Where it's more of an action product or something like that, right? So there's something around how you start to close the loop with the business. and then there's something around observability of outcomes right and that and I you know I know this is something that we talk a little bit that's starting to get a little bit hyped around context graphs and decision traces and things like that that like seeing how the data is being used and implemented and just did it result in a success did it result in a failure they're required did it did you try to do something autonomously but it failed and it required a human to get involved. It was a human escalation and then they had to make a decision. What was the thing that the human did? What was their choice that they did that had to override that? That this context ends up becoming really useful to see how you're closing the loop with actually having an impact with the business. So here's a comment right now I just got up is, I wonder how 8 billion AI bots will react. And so if I start thinking about it, if we start unleashing all of these agents and people can go create anything in a way couldn't that be the the analogy is like oh you can hire whoever you want because you need all this help well let me go hire a bunch of people to go do all these little tasks that i need to go do and i technically have to don't have to pay them right i mean pay my token and stuff but i'm like not really hiring them so then you can just hire a bunch of people, hire a bunch of agents to go to your things. And you can so easily co-create more and more and more. At what point is that like not sustainable? And we actually need to put the guard, the guard, I mean, and I think this is why we talk about, not to get sales here, but we talk about RAI control time because you want to be able to control these things, right? Because businesses are reinventing themselves because they need to be able to have all these agents, but we are going to be releasing more and more agents. And at some point I think this is going to be an interesting thing with organizations that they're going to some people were like yes let's go let's let it rip and then we're going to have these eight billion bots doing things and how are they going to be acting and stuff so i don't know i think that there's the other aspect i was thinking about this week was if you start defining these agents because now these agents are like you find these skills and stuff right so you start to put a lot of your context your semantics and stuff inside those skills and then you'll have different skills and different agents. And so typically you're putting your business logic inside those agents. How do we know that they're not contradicting with somebody else? And how does an agent know that they should be able to go interact with other things that have similar stuff? I mean, in a way, this is not analogous. This is analogous to like, Oh, I decided to put some business logic in this application that I created. I have multiple applications and I don't, and the only way to understand what this stuff actually does is kind of dive it into the into the business life that I put inside my applications we doing the same thing with agents because agents at the end of the day is a software it a software program so we just it just the bar to entry is so low that now before you to build an application you have to you have to have software engineers you have to pay all this money for a sass anybody can do that but now with with great powers come great responsibility I mean, in a world where resources are no constraint, then all sorts of weird things happen, right? You can build whatever you want. You can build unlimited dashboards, unlimited data lakes, unlimited... I was talking to a CDO this week, and this person was saying, I mean, yeah, we have a lot of resources, which is also a problem because then we get to do a lot of things that actually when you have more constraints, like actually like, oh, we shouldn't be spending all this money. Like we're more constrained, forces us to kind of think more strategically, more objectively about what needs to happen. Yeah. I mean, you get these sorts of organizational design problems, which, you know, I think just since we're kind of ranting and going in all sorts of different directions there, you know, I've been thinking a lot of like when I was in college, I studied a lot around organizational design. And I've been thinking lately that a lot of the organizational design concepts apply to bots, to agents, right? Where you need hierarchy. Who's in charge? You need policy. What's your gurgling? You need purpose. What is the goal? You need to update the purpose on a regular basis. We talk about quarterly or annually. right but like but you don't want to update it every day because then you create confusion so it's interesting now you're saying it's like the eight like these agents like inside their prompt and their skills you need to give them your okr yeah and so i think this is fascinating because i think in this world of like unlimited resources i think there are there's like a part of us that believes like maybe it will be like ants and it'll just like magically swarm but i my hypothesis is that it's actually that, you know, when we look at like organizational design, and we look at OKRs, and we look at bureaucracy process, right, we usually look at those things. And we think that those those things are unfortunate, kind of broken byproducts of humans. But what if those aren't broken byproducts? What if actually they are, even though they frustrate us, they are very important and they're actually um a feature of complex multi-agent systems just happens that usually the agents are humans in the past i don't know this is i i find this fascinating that you might you might need to have a board of agent directors that tells your ceo agent what to do and you know make sure that you have proper agent stakeholders that are providing their voting yeah Anyways, it gets it's very interesting. I think we need to be careful to like not think about the just because we do this with humans is also what we should also do that. Oh, totally. You shouldn't just copy paste. Right. But. But I think that, you know, things like Open Claw. Right. And then people are like, oh, I can unleash an army of agents and then an army of stupid happens. By the way, the Open Claw's founder, Peter, was at the TED. right yeah his talk is available so you want to hear the history how that started go watch that's a great talk that's fascinating you'll have to watch that um but you know some of this organizational design stuff may actually be it's a row yeah and i think is uh also in a way is it means that we are treating these agents ai as as if it were another yeah our colleagues, right? What is it? I just wonder how we need to find that balance of like, I mean, we don't know what that balance is. We're going to go find that out. Right, we're going to figure that out. And the answer is probably going to be it depends, right? Of course it is. It's going to be hybrid. Human organizations, right? In some cases, it's better to have a flat organization, right? In some cases, it's better to have a hierarchical organization. So, I mean, like, when does it make sense to have one or the other? When it's very clear what the goal is, and you just need to have really concerted coordination, well, it's better to have a hierarchical organization. If you need high creativity, well, then it's better to have an agency. It's better to have a flat organization, right? And what's going to be really interesting now that you say about coordination is coordinating between humans is super freaking hard. Yeah, it's messy as hell. And then there's all – so for things that are very objective and still need high coordination, that's exactly the type of stuff that humans shouldn't be involved because there's a very clear objective that needs to be done. It's not subjective. We need to go do. There's a lot of things that need to go pass around because of the systems, how things are just set up. That's something that they just should be able to go deal with very nicely. But the moment that something gets very subjective, and I think it goes back into probably an 80-20 rule, which is like 80% will be things that are, it's okay it's not going to be mission critical it's not not mission critical it's like it's not uh it's we need we're open to creativity we're open to this agency if you're for a 20 like oh this must be this way right that's for regulatory purposes financial reasons like it has to be this way so that may that may be more constrained around things but for an 80 it may be like yeah if humans if we don't even trust humans perfectly with this stuff we'll just put some agents to it too and we'll see what happens I don't know is it going to be better? I don't know I think it goes back to my earlier points I think this is how this is what helps us regain our humanity I don't want to be able to go I don't want to do those boring tasks let me go focus on the ones that are actually going to be more fruitful and I'm going to be more not just passionate, but like I'm going to be more fascinated about things. Yeah. And so to tie this back a little bit to the comments about like work being at the center and work and how does work kind of play into the data stack and the future of data architecture? I think there are some things that are maybe a little bit more non-controversial, maybe hard but non-controversial like for example decision intelligence right is a field that's been around for a while um which is something that i i personally don't understand more i'm actually curious i'm actually curious for data folks listening like how much have you all been uh looking into learning about decision science decision intelligence yeah so i think that's something we're all as an industry gonna have to learn more about i think that's even though some people would say like oh man yeah you know that's hard or it's gonna it's gonna take some time but But I think that's kind of non-controversial, like the decision pieces, right? Something that is more, I think, open is that, you know, for the last several years, especially the last few years, I'll pick on catalog because, you know, cataloging cocktails here. You know, one of the ways that we've talked about taking action with metadata is we talk about active metadata. And usually active metadata is you take the metadata and you want to tie it back somehow. and that tying it back usually is some kind of a point-to-point connection right and so um you know well i want to take that metadata and i want to push it back into snowflake or i want to take that metadata and i'm going to have a program that looks for issues and if there's an issues it's going to push some information back into my you know my service now or my salesforce or something like that right so that was kind of like it was more of a point-to-point thing more recently now we have this idea of catalog as kind of a context layer mcp let those semantics and the information about your catalog be available to agents that's kind of self-service um but like what else does work look like when it's doing work like for example do you do we need to start thinking about there being a bunch of agents and those agents are using our data products they're using the context that we're providing are those agents are those agents consumers are they are the agents data products themselves so my immediate thought goes back to our librarian friends and i think that we'll need to have the reference librarian right the agents that will be able to do these types of reference interviews to be able to say like so agents are trying to do things because here's the thing come to the library yeah and part of that library will have some agents that will i mean we'll try to get those information needs and now if if if people are creating these agents right and they'll say well was this agent created with a with a fixed objective or did somebody put in a on a created object an agent that was kind of loose what they're going to go do so even that is like how unclear or clear is it that you're trying, what you're trying to go do. So you need to be able to kind of have those back and forth. So first job of the reference librarian is to, is to understand the true information needs. Yeah, the true information need. Because at the end probably the, like where is the original input coming from? Like it may be coming from a human right If it is coming from a human maybe that is something that is ambiguous itself You want to be able to kind of understand what is the actual need So I don know where I going with this but I don know The librarians are always on my mind. But I think there's a lot to learn. When we think about how the data stack's evolving, right? You need the reference librarian. I think that's something that is very inspiring to think about, to take their approaches and how, combine all this stuff that's happening at the end of the day like what i mean about work is like you're you're at an organization and there's objectives that your organization was trying to accomplish i mean and these are and these this is a human thing right that's why humans get together to build a company so there's a human there's goals that are established by people and and yeah part of that we live in a capitalist world we want to make money and save money a lot of stuff so these objectives need to be defined and but and then all these work that needs to happen. We need to take decisions to make that work happen such that we can accomplish those objectives of that organization. So I think like the more we get to wonder, and I think this kind of elevates back to our, our, our humanity is like, we get to get focused more on the, why are we all here together to make at this company, at this organization, what is the goal of organization we're trying to go do? And let's make sure that we're optimizing for that. While there's all this stuff in the bottom that happens underneath the hood, which that stuff should be automated. It should be automated. It should be autonomous and stuff. And it enables us to go focus on other things that really makes us, again, makes us human. Like, again, human companies are human endeavors. Companies are not, they're human beings who decide that we have all this interest together and like, hey, let's work together to make this goal. And that's a company. And I think we should be, this is the opportunity to focus on this. You said that you're a techno optimist. And I was cool with everything you said until this last part here. Why? Just the companies are a human endeavor. I think that we're going to see companies that are completely agentic endeavors. But they're going to be there. Or the three humans and 10,000 agents. Well, I think that's true. I think it's already happening. I guess the human endeavor is for humans. The whole open claw thing is already kind of showing this. I mean, if you look at the, look at Peter's talk, he talks about how like somebody was making beer and dot, dot, dot. They like started a company, started a website to go sell the beer because they didn't make too much beer. And obviously the agent did all that by himself. But it all started with people getting together to make beer. But there's, I think, I think it all starts with humans. Okay. Okay. I think the agency is like, goes back to the inspiration, hey, you could do this. And you're like, yeah, or I don't care, but go do it anyways for me. Maybe. That's interesting. I was watching a video of, I forget who it was. I'm sure some people listening may know. But he's like a really senior engineer architect at a company. he was being interviewed by I forget it was 60 Minutes or something like that like a news group and they asked him so in this world of AI you're using AI to code everything I was like yeah I use 100% of my code is developed by AI now and then they said well what's your job he's like he thought about it for a second my job is to have taste and to have discernment of what is impactful and what is not. I love that. Basically, that's what he said. It was like, ah. That's the human endeavor. That is the reconnecting to humanity because that's the stuff that you really enjoy. I have that taste of how much things should be done. It could be this way. It could be this way. It could be that way. What looks bad. I made a preference for this. I thought about there's a reason how i how i did this right i mean it's like architecting and think about it like there is some imagination humans are always be there to humans are problem solvers we that's what we always that's what we do right uh we'll always be uh we enjoy it we'll always enjoy entertainment uh humans may be doing entertainment machines we do enter but we always want what we seek entertainment so i mean i think it goes back to like ai is helping us we get to focus more on our problem solving we get to focus more on on finding our joy and things we get to have more fun but we also remember that that work is there's a purpose like we work not just for a paycheck i mean in idealistic role like people need to work i mean it's right but also work is a purpose there's hopefully you find a you find a passionate fascination for something yeah i think that the the the non-silver lining is is that as as certain jobs change then maybe you don't like the way your job is evolving you know like you and me tend to be we're a little bit more social we're a little bit more um orchestrators thought leaders right um some people really like coding I guess we'll just see how things go here you get to be an architect a code architect and I think this is going to be an interesting statement I'd argue that people who quote unquote like to code are really they like to solve problems and they're the architects and coding is just a manifestation of like okay figure it out let's go implement that solution but there is more fascination into doing the problem solving before actually writing the code. And then the moment, the thing is that when you write the code, you bring down your level of abstraction to something more specific. And something that you thought that you understood and you thought you solved, the moment you turn it into code, you realize it doesn't work. And then you're like, oh, wait, I didn't really understand that problem very well. That's why I couldn't, that's why the code is not working. or it's inefficient and then you find the next problem to go solve. So. So, yeah. A good comment there. Taste, taste everything. Maybe that's circling back to the beginning. That's maybe what it is to be human. Is to have good taste. Taste. Yeah. Taste on what's good, what's impactful. Also, what tastes good? Yeah. What was it? I finished my beer. So then we have a patient because I think this must have tasted better than mine. What else should we hit today? This has been a long rant. Yeah. What else was on your mind? Well, in a week and a half, we got the Knowledge Conference. Yeah, it's all right. So we'll be in Las Vegas. So Las Vegas, for folks who are coming to the ServiceNow Knowledge Conference in Las Vegas, join us. If you're on the fence, it's going to be worth it. I mean, all the content, all the keynotes and also Idris Elba and Backstreet Boys at the Sphere on Thursday. I'm most excited for DJ Idris. He's actually a professional DJ. I didn't realize that. I learned because of this. And for those who don't know, Idris Elba is kind of like our spokesperson for ServiceNow. He's the CEO. Yeah, he's the CEO of the pretend ServiceNow company. So it's funny. So that's it. And then the following week, I will be in Gartner, which is going to be really weird because the first time I go to a Gartner without you, this is going to be my 10th, I think our 10th Gartner. Yes. And they're not going to be there. Yes. I'll be home. And then we're going to be, that's our sixth year anniversary of our podcast. Yeah. So we'll have to do it hybrid style. And then, okay. So. But that'll be cool. And for folks listening, I'm hosting a dinner at Gartner with the one and only Sanjeev Mohan, who cannot replace him. but he'll That's all right. Sanjeev, I'm cool with you being stand-in, Tim. You can be backup, Tim. So we do that. So if data leaders are listening, please let us know if you want to come. Unfortunately, I won't be at the Knowledge Graph conference because it's the same week that is that Knowledge Conference for Service Now. So that's unfortunate. Too much knowledge that week. And then the following week, I'll post about this soon. I'm doing a little bit of a road show in EMEA, I'll be in Vienna, Munich, Frankfurt, and Zurich. So that's going to be the week after Gartner. So I'll post about it. So I'd love to catch up with folks. Yeah. And I'll leave one kind of call to action with our community, which is that Juan and I are thinking a lot about what can we do next to really help the data community, to feedback to the data community? you know should we should we be doing more like digital event kinds of things should we you know be organizing more on community are there some existing communities that we should be leaning more into so you know hey just ping me ping huan curious about your thoughts on like what's what's what's some cool stuff that we can get more involved with or involved in or start and organize around yeah all right cheers everyone cheers thanks for your Friday.