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Julie Zhuo

@joulee • 227,635 subscribers

Founder @teamSundial. Angel investor. Author of "The Making of a Manager" https://t.co/6HwJhCW5Hi. Obsessed with systems. Design + data person.

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Taste is invisible until you try to write it down. This is probably my biggest lesson with AI building as of late. At Sundial, I get to work with really friggin' amazing analysts who know the art, and I see how much of our collective time now is now spent turning that art into playbooks or skills for an LLM. Encoding things like: "How would a great analyst actually look at this metric move?" or "What is ACTUALLY the interesting signal in this story versus noise?" or "How can we know if a product change actually moved the needle?" It's really humbling work! You write an instruction set. The LLM misses. You add more context. It still misses. You add even more. Now it's confused. You strip it back. Now it's too vague. You try a different framing. Better, but inconsistent. Works on Monday, fails on Tuesday. You go again. I've come to realize the gap between 70% quality and 95% quality is not 3 or 4 big things. It's more like 100s of small things. Which is exactly why you can't write an article about it, or copy it, or shortcut it! This gap *is* taste, quantified. The accumulated weight of a thousand small judgments you don't notice you're making, until you sit down to externalize them and realize you can't. Being good at something is not the same as being able to articulate why you're good at it. I now see two bottlenecks to making something better than today's generic AI: 1. Can you *see* what better looks like in the first place? 2. Even if you can see, can you *articulate* what that is in a way that the LLM can understand and systemize? #2 is now a new craft, the art of distilling the art. The people who can do it well are the ones building standout products.

Taste is invisible until you try to write it down. This is probably my biggest lesson with AI building as of late. At Sundial, I get to work with really friggin' amazing analysts who know the art, and I see how much of our collective time now is now spent turning that art into playbooks or skills for an LLM. Encoding things like: "How would a great analyst actually look at this metric move?" or "What is ACTUALLY the interesting signal in this story versus noise?" or "How can we know if a product change actually moved the needle?" It's really humbling work! You write an instruction set. The LLM misses. You add more context. It still misses. You add even more. Now it's confused. You strip it back. Now it's too vague. You try a different framing. Better, but inconsistent. Works on Monday, fails on Tuesday. You go again. I've come to realize the gap between 70% quality and 95% quality is not 3 or 4 big things. It's more like 100s of small things. Which is exactly why you can't write an article about it, or copy it, or shortcut it! This gap is taste, quantified. The accumulated weight of a thousand small judgments you don't notice you're making, until you sit down to externalize them and realize you can't. Being good at something is not the same as being able to articulate why you're good at it. I now see two bottlenecks to making something better than today's generic AI: 1. Can you see what better looks like in the first place? 2. Even if you can see, can you articulate what that is in a way that the LLM can understand and systemize? #2 is now a new craft, the art of distilling the art. The people who can do it well are the ones building standout products.

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Sundial has raised $23M to build the analytics platform for the AI era! Our work is personal to me (though many have asked: Why? Aren't you into intuition and taste and experience which is ultimately unmeasurable?) But hear me out: I love building, and I have a deep respect for it. Making something people love is one of the hardest and most humbling endeavors. The art comes down to making high-quality decisions, which comes from an obsession with the cliff’s edge between customer understanding and product capability. You need to know what’s working and what isn’t. That’s why data matters. Data is *information* about how reality works. At Sundial, we live by the mantra: diagnose with data; treat with design. What does masterful decision-making look like? It comes down to 3 things: 1. extreme alignment 2. shared curiosity to unpeel deeper and deeper layers of truth 3. urgent execution The very fact is that good intuition and taste comes from data internalized across many, many reps. Yes, reality is infinitely more complex than what can be measured. But measuring gives us a better grasp of reality. Alas, using data well is like learning a new language. It requires years of skill and context building. It's easy to misuse, whether misguidedly or intentionally. I know this all too well. Mastery requires everything from how to break down an ambiguous question, to fluently reading triangle charts and dense tables, to remembering the specific name of a specific column using a specific dialect of SQL. Too many people, like me, regularly feel frustrated by a) how long it takes to get answers b) how to draw the right interpretations c) how much noise I have to wade through to find actually actionable insights. Instead of greater confidence and quality, we get conflicting signals, cherry-picked facts, and analysis paralysis. Sundial is our attempt to solve those problems. We’re bottling up opinionated intelligence to guide decision-makers towards faster and more confident decisions. We envision a world where *everyone* can be their own expert analyst. Sundial uses AI and expert analytical techniques to make insights accessible to every decision-maker. Exemplary analysis takes the listener through a story. Data should speak the language of business, not the other way around. Sundial is also smart in the ways you’d expect of an AI-native tool. It’s not just about looking up data (“What’s India ARR last month?”), which has become table stakes; rather, Sundial can also tackle deep, complex analysis (”Why did ARR decline? What are my levers?”). In a crowded landscape of fragmented data tools—dashboards, notebooks, ETL systems—Sundial brings it all together into one intuitive platform. We believe this era of AI will see teams doing far more with less, and moving faster than ever before. Our mission is to build the data brain for the next generation of AI-powered companies. We're thrilled to be backed by dj patil at GPV—the first U.S. Chief Data Scientist and coiner of the term "data scientist”, alongside industry luminaries like Amjad Masad, tobi lutke, Fidji Simo, alex schultz 🏳️‍🌈, Shishir, Ruchi Sanghvi, Avichal - Electric ϟ Capital, Drew Houston, Howie Liu and firms including Sequoia Capital, Tribe Capital, Sunflower Capital, Unusual Ventures. The best part of building Sundial is the people we get to work with. Funding announcements are nice and all, but what really fuels us is the feedback and growth trajectory of our customers. There’s nothing better than working on interesting problems with people you like. Onward! (P.S. We’re hiring for AI engineers, data engineers, and data scientists in the Bay Area -- DM me if you resonate with our mission, love dissecting big problems down into smaller ones, and appreciate the consistent practice of craft.)

Sundial has raised $23M to build the analytics platform for the AI era! Our work is personal to me (though many have asked: Why? Aren't you into intuition and taste and experience which is ultimately unmeasurable?) But hear me out: I love building, and I have a deep respect for it. Making something people love is one of the hardest and most humbling endeavors. The art comes down to making high-quality decisions, which comes from an obsession with the cliff’s edge between customer understanding and product capability. You need to know what’s working and what isn’t. That’s why data matters. Data is information about how reality works. At Sundial, we live by the mantra: diagnose with data; treat with design. What does masterful decision-making look like? It comes down to 3 things: 1. extreme alignment 2. shared curiosity to unpeel deeper and deeper layers of truth 3. urgent execution The very fact is that good intuition and taste comes from data internalized across many, many reps. Yes, reality is infinitely more complex than what can be measured. But measuring gives us a better grasp of reality. Alas, using data well is like learning a new language. It requires years of skill and context building. It's easy to misuse, whether misguidedly or intentionally. I know this all too well. Mastery requires everything from how to break down an ambiguous question, to fluently reading triangle charts and dense tables, to remembering the specific name of a specific column using a specific dialect of SQL. Too many people, like me, regularly feel frustrated by a) how long it takes to get answers b) how to draw the right interpretations c) how much noise I have to wade through to find actually actionable insights. Instead of greater confidence and quality, we get conflicting signals, cherry-picked facts, and analysis paralysis. Sundial is our attempt to solve those problems. We’re bottling up opinionated intelligence to guide decision-makers towards faster and more confident decisions. We envision a world where everyone can be their own expert analyst. Sundial uses AI and expert analytical techniques to make insights accessible to every decision-maker. Exemplary analysis takes the listener through a story. Data should speak the language of business, not the other way around. Sundial is also smart in the ways you’d expect of an AI-native tool. It’s not just about looking up data (“What’s India ARR last month?”), which has become table stakes; rather, Sundial can also tackle deep, complex analysis (”Why did ARR decline? What are my levers?”). In a crowded landscape of fragmented data tools—dashboards, notebooks, ETL systems—Sundial brings it all together into one intuitive platform. We believe this era of AI will see teams doing far more with less, and moving faster than ever before. Our mission is to build the data brain for the next generation of AI-powered companies. We're thrilled to be backed by dj patil at GPV—the first U.S. Chief Data Scientist and coiner of the term "data scientist”, alongside industry luminaries like Amjad Masad, tobi lutke, Fidji Simo, alex schultz 🏳️‍🌈, Shishir, Ruchi Sanghvi, Avichal - Electric ϟ Capital, Drew Houston, Howie Liu and firms including Sequoia Capital, Tribe Capital, Sunflower Capital, Unusual Ventures. The best part of building Sundial is the people we get to work with. Funding announcements are nice and all, but what really fuels us is the feedback and growth trajectory of our customers. There’s nothing better than working on interesting problems with people you like. Onward! (P.S. We’re hiring for AI engineers, data engineers, and data scientists in the Bay Area -- DM me if you resonate with our mission, love dissecting big problems down into smaller ones, and appreciate the consistent practice of craft.)

128,084 просмотров • 11 месяцев назад

I see a lot of designers who want to stay "designers," like the role is some kind of warm, fuzzy blanket focusing purely on experience and aesthetics. But this is not how the best designers think. In my interview with Soleio on what separates top 1% designers from mediocre designers, he says it brilliantly: “If you delegate impact to PMs, you cannot ask for the title of excellent.” At the end of the day, it’s your job -- not your manager’s, not your PM’s, not your CEO’s — for your design work to change behavior positively for the user

I see a lot of designers who want to stay "designers," like the role is some kind of warm, fuzzy blanket focusing purely on experience and aesthetics. But this is not how the best designers think. In my interview with Soleio on what separates top 1% designers from mediocre designers, he says it brilliantly: “If you delegate impact to PMs, you cannot ask for the title of excellent.” At the end of the day, it’s your job -- not your manager’s, not your PM’s, not your CEO’s — for your design work to change behavior positively for the user

21,386 просмотров • 1 месяц назад

In an interview, what separates a top performer from an average one? Contrary to what everyone believes, it’s NOT about polish. Soleio looks for the opposite, and he's recruited the best of the best in the design world. Okay candidates tell tidy stories: the project was important, the team aligned, the solution emerged, and good things happened. It all sounds great! That's the problem. Excellent candidates remember the mess. They tell you what they tried that failed. What they were convinced of and had to abandon. Where they disagreed. What got cut and why. Soleio compares it to the old Hollywood saying: show me a happy set and I'll show you a bad movie. Great work leaves residual pain, and the pain is the more interesting story. The pain is specific. When someone has really lived inside a problem, they know the story. They know exactly where their contribution starts and someone else's ends. They don't dance around the work. So the next time you're interviewing, listen for the mess.

In an interview, what separates a top performer from an average one? Contrary to what everyone believes, it’s NOT about polish. Soleio looks for the opposite, and he's recruited the best of the best in the design world. Okay candidates tell tidy stories: the project was important, the team aligned, the solution emerged, and good things happened. It all sounds great! That's the problem. Excellent candidates remember the mess. They tell you what they tried that failed. What they were convinced of and had to abandon. Where they disagreed. What got cut and why. Soleio compares it to the old Hollywood saying: show me a happy set and I'll show you a bad movie. Great work leaves residual pain, and the pain is the more interesting story. The pain is specific. When someone has really lived inside a problem, they know the story. They know exactly where their contribution starts and someone else's ends. They don't dance around the work. So the next time you're interviewing, listen for the mess.

13,843 просмотров • 1 месяц назад

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