Lenny's Podcast

Everyone’s shipping more. Does any of it matter? | Claire Vo

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Completo 23:57 min youtube 2026 Semana 39 24 Sep 2026 🇪🇸 ES
TL;DR
Resumen de investigación

Lo útil de este vídeo

Metodologías

Reemplazar la lista de funciones por un ciclo de convicción y evidencia

Define la dirección que se quiere seguir y qué evidencia confirmaría o refutaría esa convicción; usa una fábrica para probarla rápidamente con la realidad y asigna recursos según lo aprendido.

La ponente · 15:41

  1. Definir la dirección y la convicción sobre el futuro.
  2. Establecer de antemano qué evidencia confirmaría la apuesta y qué evidencia haría detenerla.
  3. Construir con rapidez para contrastar la convicción con clientes y la realidad.
  4. Asignar inversión, esfuerzo y tokens según lo aprendido.

Persistir en el problema y revisar la solución

Mantén la convicción sobre el problema, pero cambia la solución cuando haga falta; evalúa si se está perseverando con criterio o si solo se sigue enviando porque hay tokens disponibles.

La ponente · 17:18

  1. Mantener el foco en el problema que se intenta resolver.
  2. Revisar la solución a partir de lo aprendido.
  3. Comprobar si se está perseverando en la convicción o moviendo el objetivo para justificar más envíos.

Comunicar el nivel de compromiso de cada función

Distingue entre una exploración inicial, un experimento que se mantendrá hasta resolverlo y una promesa estable en la que los clientes puedan confiar.

La ponente · 18:44

  1. Identificar si la función es una exploración, un experimento duradero o una promesa.
  2. Comunicar con honestidad el compromiso asociado a la función.
  3. Tratar como promesa aquello que los clientes ya pueden usar y sobre lo que pueden construir.

Diseñar una hoja de ruta basada en ambición y experimentos

Expresa el futuro que se busca, la evidencia de progreso y qué podría refutar la apuesta; enfoca el trabajo en experimentos grandes y rápidos, asumiendo que muchos no tendrán éxito.

La ponente · 19:58

  1. Describir el futuro que se cree que debería existir.
  2. Definir qué evidencia mostraría progreso y qué probaría que la apuesta es incorrecta.
  3. Probar apuestas ambiciosas en semanas, incluso si antes habrían tardado un año.
  4. Contar los experimentos grandes por mes y asumir que muchos no funcionarán.

▶ La hoja de ruta como artefacto en cuestión

La ponente saluda al público y recuerda que el año anterior declaró que la gestión de producto estaba muerta, aunque reconoce que se equivocó: sigue habiendo líderes y profesionales de producto. Dice que la disciplina ha cambiado desde la cumbre anterior y anuncia que esta vez cuestionará la hoja de ruta. La presenta como el artefacto que ha guiado carreras y equipos al indicar hacia dónde ir, qué viene después y qué importa; tras más de dos décadas en producto, cree que algunos podrían estar por escribir su última hoja de ruta.

▶ La capacidad de ejecución supera a la capacidad de descubrir

La ponente afirma que ahora envía más software que nunca y enumera agentes de programación, herramientas de desarrollo, modelos, contexto de clientes mediante API, CLI y MCP, skills y 40 bots Grock. Aun así, dice que se ha quedado sin buenas ideas: puede construir, pero no está convencida de que las ideas disponibles sean valiosas. Según ella, la ejecución ha superado su capacidad para descubrir productos significativos y comercializables. Contrasta esto con la escasez anterior de capacidad de ingeniería, cuando había más ideas y demanda que capacidad de entrega y el trabajo de producto consistía en priorizar, secuenciar y rechazar propuestas. Ahora percibe que su limitación principal es creer que algo merece construirse.

▶ Un producto construido sin convicción suficiente

La ponente se describe como partidaria de maximizar el uso de tokens y acelerar los envíos, pero cuestiona la distancia entre esa capacidad de construcción y la convicción de que el código importa. Cuenta que creó una idea de producto llamada product graph for chat PRD: un sistema que reuniría conocimiento de clientes y trabajo de la empresa, lo procesaría con Opus y lo pondría a disposición de agentes para apoyar decisiones y redactar PRD. Construyó un motor de insights, un grafo semántico, una wiki automática y funciones para que los agentes lo consumieran; el producto funcionaba y competía con ofertas del mercado. Sin embargo, le parecía poco diferenciado, dudaba del retorno y de la interfaz, y no estaba segura de que mereciera la atención de los clientes. La hoja de ruta ejecutó la apuesta, pero no puso a prueba ni reforzó su convicción. Mientras tanto, automatizó arreglos de clientes, abordó deuda técnica, reestructuró Chat PRD 70 veces y dejó de seguir incidencias para enviar PR. La fábrica de IA funcionaba, pero ella no sabía si el trabajo importaba.

▶ La ejecución barata todavía requiere criterio

La ponente dice que no está convencida de que todo lo construido haya importado. Revisa para qué servían las hojas de ruta: bajo escasez de ingeniería ordenaban la estrategia, las funciones, el esfuerzo, la secuencia, los hitos y los MVP. Esa escasez también impedía que algunas ideas de la parte inferior de la lista llegaran a construirse. Ahora, afirma, pueden ejecutarse incluso malas ideas; considera que la ejecución barata sigue necesitando criterio y anuncia tres trampas que asocia a combinar hojas de ruta con una capacidad de ejecución que parece ilimitada.

▶ Las trampas de backlog, paridad y abandono

La primera trampa es la del backlog: si existe una lista de peticiones, la IA puede construirla entera, pero vaciarla no equivale a avanzar en el negocio ni en los problemas de los clientes. La segunda es la paridad: competidores que consultan a los mismos clientes, extraen insights parecidos y llegan a productos y decisiones obvios similares; la ponente también alude a usar las mismas instrucciones para dar acabado a los productos. La tercera es la del abandono: se lanza algo, se observa una señal ambigua y se cambia de rumbo, sin aprender ni acumular mejoras. Aunque estas conductas parecen productivas —menos backlog, más funciones competitivas y más envíos—, según ella pueden acelerar el camino hacia la mediocridad. Llama «road map zero» a la situación en que cada función visible parece plausible y construible, por lo que la facilidad de construcción y el esfuerzo dejan de servir como proxies útiles para decidir qué importa; cuestiona que la priorización practicada hasta ahora siga siendo estrategia.

▶ Cambiar funciones por hipótesis que probar

La ponente considera peligrosas las hojas de ruta tradicionales cuando se ejecutan a velocidad de máquina: una fábrica de IA no distingue una apuesta trascendente de una idea, y la debilidad del criterio puede producir consecuencias antes. Propone preguntarse qué se cree con suficiente fuerza como para intentar demostrarlo. Sostiene que la restricción restante es la verdad obtenida en contacto directo con clientes: la IA no transforma una suposición no probada en un hecho. Recomienda clientes reales, datos reales, pruebas repetidas, una perspectiva propia y un estándar de calidad alto. La IA permite llegar antes a la realidad, pero eso aumenta la obligación de acudir al mercado y aceptar lo que revela. Para ella, las listas de funciones y fechas se vuelven peligrosas; el trabajo debe pasar de definir qué construir a definir qué probar.

▶ Convicciones duraderas y funciones desechables

La ponente propone empezar por definir la dirección y la visión de futuro, junto con la evidencia que confirmaría o refutaría la convicción. Hace falta una fábrica que permita construir con rapidez y contrastar las ideas con la realidad, y después asignar inversión, esfuerzo y tokens en función de lo aprendido. Resume el enfoque como convicciones duraderas y funciones desechables: mantener el rumbo sobre el problema, pero cambiar la solución sin ego. Distingue la terquedad útil —persistir en el problema y revisar la solución— de la terquedad perjudicial —seguir enviando cambios porque hay tokens y mover el objetivo—. Sugiere mantener rigor en calidad y aprendizaje, y no tratar todo envío como una promesa: puede ser una exploración, un experimento más duradero o una función ya estable en la que los clientes puedan confiar y sobre la que puedan construir. La solidez de la convicción y la duración del compromiso importan junto con el impacto estimado y la dificultad de construcción. Al volver al product graph, explica que lo dejó desactivado con una bandera de función porque no tenía suficiente convicción y no quería arriesgar la confianza del cliente.

▶ Hojas de ruta ambiciosas y experimentación

La ponente no propone dejar de planificar: quiere hojas de ruta centradas en la ambición, la evidencia de progreso, las condiciones que podrían refutar la apuesta y lo que justificaría dedicar más tiempo, tokens y atención de clientes. Contrasta los últimos 12 a 18 meses, enfocados en aumentar la velocidad de prototipos y PR, con lo que considera el reto siguiente: hacer apuestas ambiciosas y probar en dos o tres semanas ideas que antes podían tardar un año. Sugiere medir cuántos experimentos grandes se realizan al mes, asumiendo que muchos no funcionarán, en vez de centrarse solo en PR por empleado o ingresos por empleado. Su petición es abandonar las listas de funciones con impactos supuestos y fechas rígidas, elevar la convicción y la ambición, definir el éxito a uno o dos años y crear una fábrica capaz de sorprender al equipo. Acepta que se escriba y descarte código y pide mantener un estándar alto para la IA y los productos. Cierra invitando al público a escribir su última hoja de ruta y saluda a los asistentes.

Transcripción completa
[0:06] Good morning everyone. How's it going? Everybody excited to be here? >> Okay, for those of you that were in the Somebody texted me, they called it the How I AI sauna last night, the party we had. I told you all you need to hype me up this morning because I was out way past my bedtime, which is 8:15. I've got a little baby. Um but I am here prepared to do the thing that I do. So last year, last year I came here and I said product
[0:36] management is dead. I said that because as a product leader I like to make these big grand statements and then be proved completely wrong in the market. Just keeps me really honest. So product management is obviously not dead. There are so many amazing product leaders, product managers, product executives here in this room. But who's with me that between the last time we had Lenny's summit and now product management is completely different. Okay, got some hands. It's really different. And so last year I came for
[1:08] PMS that didn't work. Let's do it again. This year I'm coming for the road map. The Yeah, you're you're welcome. OKR's next and then my job is over. >> [laughter] >> So the road map has been the defining artifact of our industry, of our careers. It's supposed to tell us and our teams where we're going, what's next, and what matters. And I have been
[1:38] in product for over two decades. And I believe, fingers crossed, a lot of us in our room in this room are about to write our last road map. Before I go into why I think that, I want to tell you all I have a confession. I am shipping more than ever. I have access to the most intelligent coding agents in the world. I have the best developer tools anybody can ask for. I
[2:09] have super smart models. I've got customer context via API, via CLI, via MCP. all the letters I have. I write so many skills. And y'all, I counted yesterday. I have 40 Grock bots. I can build almost anything. And here is my true true confession. I am out of good ideas, y'all. I'm like straight up out of good ideas of things
[2:42] to build. I'm out. I can build. I just don't think any of it's a good idea. So, and and I'm not saying I don't have plausible requests. It's not that I'm saying I don't have things I could build. It's just that execution has outrun my ability to discover meaningful, meaty, my favorite word, commercializable products in the market. And this is a
[3:12] very different situation that I have been in than before. You know, it used to be that engineering capacity was the scarce resource. That was like I mean that's kind of why we exist honestly is like engineering capacity used to be the really scarce resource. We had way more ideas than people and we had way more demand than our ability to deliver against that demand. And the product
[3:42] manager, the products leaders job was to prioritize all those ideas, sequence them, and then spend like all our time in meetings and in Slack and in spreadsheets saying no. Saying no. PMs should say no more. we should have cut lines. It was like very aggressive like here's my cut line for the quarter. This is my priority list. This is my stack rank. And while the PM's job was to say no, it felt like engineering's job was
[4:12] to say like no, not like that. Not with all those features, not with perfect architecture. We can only do this much. And then it seemed like design's job was say to like no, wait for us, like please. And so everybody's like just constrained on this like precious engineering capacity. And so things got narrow narrow narrowed down till you only shipped a little bit of your road map. And now I feel like I have more [clears throat] execution capacity than like true conviction about what to
[4:43] build. So my bottleneck has moved from like building what what can I build to believing like what do I believe is actually worth building. And look, I am like the biggest token maxer on the planet. I'm like PR's up 3x. Like do it all. Ship, ship, ship. Agents everywhere. I don't need a PM. I don't need any specs. But like I think this gap between our building capacity and like true in our heart of hearts
[5:16] conviction like does any of this code matter is a much bigger problem than any of us are willing to admit. I think we're all getting a lot of pressure from the board, from the timeline, from each other, from our teams, from our bosses to move faster, to get leverage with AI, to like really lean in and show we're AI native. We can build in this new way. Claire said product management is dead. She showed all these scary circles. She said like ship to the moon. Do it, do it, do it. But like I do think none of
[5:47] us are I know this is a question I asked one who's who's shipping more than ever in the last year at their companies whose revenue is going up proportionate with the amount of PRs like that's the fundamental problem we're facing here and so I'm going to tell a story and like bring this home for you this like I have no good ideas and I don't know if they matter. Um so I had this idea for this thing called the product graph for chat PRD. It's like a It's a real product for product managers idea and it's not special because everybody's done it. But it's like we're
[6:18] going to suck in everything a company knows about customers, about what you're working on, blah blah blah blah blah. We're going to parse it. We're going to like slap, you know, opus on it and then it's all going to be available through agents and it's going to be awesome. It's going to make you be able to make these decisions better and build better products and of course write better PRDs. And so I built it. I built this like insights engine. I built this like very fancy semantic product graph. It like generates this auto wiki. Agents can consume it. It was like almost a
[6:48] oneshot. Not quite, but it was a pretty close oneshot. It worked. It looks pretty good. It was like feature forfeature matching competitors in the market. And I kind of just like every time I would build it, I would be like, "This just belongs in the trash. It belongs in the trash. All this work, all this amazing product belongs in the trash." And why? Because to me it was competitive, it wasn't differentiated. And so, you know, even though I had built this thing that like obviously had
[7:19] a market, people would probably want it, customers said it was interesting, like in my core, I felt like it wasn't worth my customers attention. I like the ROI was really shaky to me. I wasn't convinced on the interface. I was like, should this it it still had a web interface. I was like, should it be agent first? Is this the right thing? I wanted to build something surprising that competitors couldn't even imagine. And my big problem was that these tokens and this like road map that I had
[7:49] executed my bet, but it didn't really test or validate or strengthen my conviction. Meanwhile, I'm sitting on all this kind of like code to nowhere. I kept shipping more than ever. So, customer fixes were like automated. They would come in, they go to like one of my bots, and then they get fixed. Goals were like obliterating tech debt. I mean, I re rearchite rearchitected chat purity 70 times because I could. Um, we stopped tracking issues. We're like, we
[8:19] don't need issue tracking anymore. We're just going to ship PRs. This AI factory like manifested and started running itself. It did the thing that we all want it to do. It's magical. And here's the secret. I'm not sure any of it mattered. Like I'm not yet convinced that any of that mattered. And that really got me thinking. It got me thinking about what is product management? What is the purpose of building software? How do we
[8:50] make decisions? How do we prioritize? How do we allocate all these tokens? And I just kept going back to this idea of the road map. road maps made sense under engineering scarcity. They like laid out your strategy. They told you what features were you going to build. We had this thing called effort which was like more than me like voice noting you know Devon saying can you please build this and we thought a lot about sequencing and milestones and MVPs and
[9:24] scarcity helped us theoretically let's be honest it helped us theoretically filter out our bad ideas because the bottom of the list just never shipped. It never could. There were not enough engineers. There was not enough conviction across the organization. and said this like below the cut that's what we called it below the cut line never shipped and now we can ship all our bad ideas like congratulations to us cheap execution I think still
[9:56] needs judgment and I think we're seeing this moment where the road map plus like limitless or feeling like limitless execution capacity is creating three traps that I want to warn you about the first is the backlog track. So this is if you have a backlog, AI will build it. They will build every single thing. It will build every single thing on your list. And so I hear a lot about like, you know, I we're burned through our backlog. It's because all you have to do
[10:27] is slashgo build the backlog and it gets done. But the problem is clearing out requests or ideas does not mean meaningful progress against your business or even meaningful progress against a customer problem. The second thing is the parity trap. This is something I really felt in that story about the product graph. All your competitors are copying each other and they all are talking to the same customers and they're all sucking in the same insights and they're all arriving
[10:58] at the same obvious conclusion and building the same obvious product with the same obvious like run the taste skill. Run impeccable. Run whatever. Make it look good. Get rid of the m dashes. Get rid of the borders. Like we're all doing Can you tell I took max? Yeah. So we're all doing the exact same thing. And so this like parody trap where we used to have this like really interesting dynamic with competitors now it feels like it's evening out and again like this question about what Moes are and what differentiators are is a big
[11:29] one in my mind. And then the final kind of trap I see is the churn trap which is we ship something, we see noise and pick up or not because we can always ship something else, we abandon it and then we never really learn or compound on top of what we're shipping. And so all of these things from the inside feel very productive. Like my backlog's going down, my competitive features are going up. like we're shipping more than ever,
[11:59] but what I think this does is it just like accelerates our path to mid. And that's the thing I want to warn you about. And so this brings me to something that I'm really observing, which is this concept of road map zero. I don't mean like we've gone through the road map, although some people truly have road map zero, nothing on the road map anymore. What I mean is that every visible feature becomes both plausible
[12:29] and buildable. You don't have like an empty backlog. That's not what I'm talking about. It's just like everything on your backlog you can kind of do. And when everything on your backlog you can kind of do, what is the point of the backlog? I think buildability and effort stop being like this meaningful proxy for what matters and prioritization again kind of like why PMs exist as we've practiced it I think stops being strategy right like we've been doing these like rice prioritizations but when
[12:59] like many of those letters mean nothing anymore especially effort like why are we still pretending like prioritization is the right way to think about our products and this is why I think you know, road maps are over. They're dead. It's because I think they're really dangerous right now. I think an AI factory plus an old road map will get you to those three traps at machine speed. They will get you there fast because this factory really can't distinguish a truly consequential bet
[13:30] from an idea. And AI will make the consequences of this weak judgment show up at your front door faster. And so your bad ideas will become your problems quicker than ever. And so I don't think the road map is the right thing. I think the right thing is to ask yourself what do I believe strongly enough to go out and try and prove because the remaining constraint is not code. It's not building. It's not features. It is truth. It is like on the
[14:00] ground with our customers truth. AI cannot take an untested assumption into fact. No matter how many adversarial reviews you do, and I know you're doing them, you need real customers. You need real data. You need repeated tests. And then you need a very unique point of view and a very high unique quality bar. And what AI allows us to do is make faster contact with reality, which is great. We all want to make faster contact with reality. But that means you
[14:32] have a higher obligation to encounter reality in your minds. You have to both get into the market and accept what it is telling you. And this is going to feel really retro to people like, you know, me and they're a little older because we've been saying outcomes over outputs all the time, but yet this like central artifact, the road map still lists features and dates. And again, engineering scarcity once made that workable. But like I think road map zero makes those features and dates very
[15:02] dangerous for the reasons that I outlined. This feature list I say becomes ammunition for a very powerful slob cannon. And so what I think we need to do is move upstream from what we need to build to what we actually need to prove. And so here's how I would think about what we do instead of a road map. First we build our convictions. So what is the direction that we want to go and what do we believe the future looks like? Not in 3 months, 6 months, 9 months, in in a year, in two years.
[15:33] Where do we think all of this is going? I do think you need to determine what evidence would show you that your conviction is true. And you need to define that upfront. What would I need to see to prove that I'm doing the right thing? And what would I need to see to stop? You do need a factory. So I do love the factory. I'm saying that's dangerous, but I love something dangerous. You need your factory. You need the ability to build quickly to intersect reality very very fast. So I'm not saying get rid of it. I'm saying put it at the right place in the process.
[16:05] And then you need to allocate. You need to go through that cycle. And when you get into reality, you need to allocate your investment, your conviction, your effort, your tokens in the right direction. And what's interesting I think most about this new world we're about to move into is I think you need to have durable convictions but disposable features. And I was talking to Mara who is going to come on the stage later and she's like but Claire enterprises love feature road maps and I'm going to talk to some folks at the
[16:36] end of the day who have changed a lot of features around on us a lot of products around us and we as consumers at least some of us have accepted that level of churn. And so I think we're going to get into this place where customers, where teams are able to shift to, do I bet on these convictions? Do I bet on this team? Do I bet on this space? Do I bet on this vision? And I understand features need to come and go. They might be unique to me. They might be unique to a market. And so what you want to see is clear progress against your convictions,
[17:06] but zero ego about your solutions. And what this would look like, I think there's two ways this could go. You could be you have to be stubborn here with your durable convictions. But there's good stubborn and bad stubborn. Good stubborn is you like stay with the problem. You revise the solution. You know, you hold true what's going to happen even if the flavor of the week is trending. Bad stubborn is because you have tokens. You just move the goalpost. You're like, "Ah, we're close. We'll just ship again and ship again and ship again." And so I want you to think about
[17:37] what are my durable convictions? Am I being good stubborn? Am I being bad stubborn? And then how do you actually build into your system the ability to absorb disposable features and keeping rigor around quality and learning? And this is really scary, especially when it hits customers. But I think we're moving to a place where not everything we ship is a promise. And I I don't has anybody feeling come on. Like has anybody shipped some thank you right in the middle? Like you ship things and you're
[18:07] like this is a hypo this is like truly an experiment and I might get it wrong or the market might move underneath me or the technology might change, you know, tremendously. And so I do think we have to think about this idea of like not every ship is a process, a promise. And we used to do these road maps and I would like go hand on heart to go to market and I'd be like I swear on my children this feature will ship with these specific things on this specific date. You can definitely sell it in the contract like you know and make these
[18:37] promises. And now I think we have to really think how we communicate internally, how we communicate with customers. And so I think there's going to be everything from a probe. This is like kind of a bet. We're going to explore a little bit. Um to a more durable kind of experiment against your conviction. I think this is something we really believe in. We're going to stick with it till we get it right. And then there are promises. Promises are I have shipped something. Customers can rely on it. They can build their customers on it. We really believe and we'll keep
[19:07] compounding here. And I think you need to be honest about what your commitment is on any feature. I think that's almost the most um helpful lens on the new road map is like how strong is our conviction here and how durable is this promise versus like how hard is it to build and what is our estimated impact and while we do this I you know again you need to remember code is abundant customer trust is not. So going back to that product graph, that feature that I built over and over and over again until I felt conviction, it was feature flagged off
[19:37] because I just knew that as soon as I put this in front of a customer, they were going to build on it. They were going to use it. And if I didn't have conviction that it was right, I was really going to burn that customer trust. And that's something I thought about really deeply as I was rolling out this feature. So I do still think you need a road map, but I think that roadmap needs to be more about ambition. I think it needs to be bigger. I don't want to see onesie twoosies on your road map. I want to see the future you believe should exist. I want to see what
[20:10] evidence shows that we're making progress. What would prove us wrong? And then what earns more time tokens and customer attention. And I want to go back to ambition because I think the last 12 to 18 months as you know it was like you know the year of our claude and we were shipping everything and PMs were writing PRs and it was prototypes everywhere. I really think we're in a velocity game. We're in a inflect PRs straight up velocity game. If I can get
[20:40] prototypes to customers faster they can give me feedback faster. If I can hand things to customers or to engineering faster they can do PRs faster. my agents will take care of tech debt. My agents will take care of features. I think we're really in the last 12 to 18 months building up our muscle for true inflected velocity. I don't think that's the game next year. I don't think that's the game we should be playing for next year. I think next year is the ambition game. I think you should think like what huge swings can I make? What experiments
[21:11] can I run in two weeks, three weeks that would have taken us a year last time? and how do I build sort of this roadmap of very very very large investments in very very ambitious builds because I think that is more important than raw feature velocity and I don't think the road map as it is serves that goal you know I was talking to somebody and again going back to OKRs unfortunately not dead yet and she was like what should our OKRs be relative to our AI
[21:43] transformation like PRs revenue per headcount like what it should be like how many [snorts] huge experiments are you running a month like I don't care what the experiments are I don't know what they should be like how many big big swings are you taking a month with the presumption that most of them won't work out and I think that is just a very new way to think about how you build your road map and a very new way to think about how you do your product again it's big on the ambition and very
[22:13] fuzzy on the specifics So here is my ask slashgift to you all. Build your last road mapap. And I do not mean build your last plan. Of course not. I just mean like no more lists of ideas and features in spreadsheets where you guess impact and where you like put a date on them and then lock arms and say we'll never we'll never change anything because this is how we work. I
[22:43] just think that day is over. Instead, what I want you to do is truly raise your conviction, raise your ambition, come up with big ideas, define what success looks like in like a year or two. You're going to have to make some big guesses because I can't honestly tell what's going to happen in a week or two. I really think you want to get to a place where you have a factory that can surprise you. And so, you really want to be able to discard software and then hold your factory to a high bar. And
[23:13] look, you're going to write a lot of code and then you're going to trash it. Good. Your customers do not need trash products. Your AI is going to have better ideas than your team. Good. We need good ideas. And you need to hold that AI to a very, very high bar. And you're not going to be able to promise your team, your customers, what next year looks like. Good. Because it's probably going to be better than you can imagine right now. So, this is my ask to you. write your last road map I promise
[23:43] you is extremely fun on this other side. Enjoy the rest of your summit. I will see you later this afternoon and please come say hi. [applause]

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