Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

A production issue shouldn't require a detective Yet that's how most observability works today Most observability tools just dump alerts. Duplicates, no context, and you still fix it yourself Nicolò Magnante (YC P26) and his cofounder Arseniy Shishaev (YC P26) - who spent years building part of Datadog's metrics...

davj's profile picture

David J Phillips

20,508 subscribers

40,983 görüntüleme • 1 ay önce •via X (Twitter)

Bilim & Teknoloji
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Superlog (Superlog (YC P26)) is the observability tool you're not supposed to open: a wizard sets up your logs, traces, alerts, and dashboards daily, and an agent investigates incidents and posts one mergeable PR per issue into Slack. Sign up here: Congrats on the launch, Nicolò Magnante (YC P26) and Arseniy Shishaev (YC P26)!
1:10

Superlog (Superlog (YC P26)) is the observability tool you're not supposed to open: a wizard sets up your logs, traces, alerts, and dashboards daily, and an agent investigates incidents and posts one mergeable PR per issue into Slack. Sign up here: Congrats on the launch, Nicolò Magnante (YC P26) and Arseniy Shishaev (YC P26)!

Y Combinator

36,108 görüntüleme • 2 ay önce

Most underrated skill today: Observability. I feel you can build a career just on this and have 2 decades of guaranteed money if you learn the skill well, and I'll tell you how below. Reality: Most teams I help look at me with dead eyes when I ask them about observability. That's sad, but it's the current state of the industry: • No tracing • No structured data • No way to understand what's happening when things break Outside of the most sophisticated companies, that's still where most teams are. AI is now writing a ton of code, and people are shipping this code to production. However important observability was before, it is 10x more important today. Believe me, you don't want to be the one pushing slop into production and then guessing how it works, with no way to understand what happens. Here is your first step: Honeycomb is running a FREE, 3-day virtual event focused entirely on observability. The event is running May 12-14. Did I mention it's completely free? Everything will revolve around observability for the agent era. Register here: Thanks to the Honeycomb.io System Status Updates team for partnering with me on this post.
1:33

Most underrated skill today: Observability. I feel you can build a career just on this and have 2 decades of guaranteed money if you learn the skill well, and I'll tell you how below. Reality: Most teams I help look at me with dead eyes when I ask them about observability. That's sad, but it's the current state of the industry: • No tracing • No structured data • No way to understand what's happening when things break Outside of the most sophisticated companies, that's still where most teams are. AI is now writing a ton of code, and people are shipping this code to production. However important observability was before, it is 10x more important today. Believe me, you don't want to be the one pushing slop into production and then guessing how it works, with no way to understand what happens. Here is your first step: Honeycomb is running a FREE, 3-day virtual event focused entirely on observability. The event is running May 12-14. Did I mention it's completely free? Everything will revolve around observability for the agent era. Register here: Thanks to the Honeycomb.io System Status Updates team for partnering with me on this post.

Santiago

19,983 görüntüleme • 2 ay önce

Today, we're making Error Tracking by Better Stack generally available. Sentry-compatible. AI-native. At 1/6th the price. Here's why we built it, and how to get the most out of it. What's wrong with error tracking today? Most teams use Sentry. It's solid! But at scale, the bills get brutal. Just 100M exceptions with 90 day lookback? ~$30,000 on Sentry. We charge ~$5,000 for the exact same thing. The math isn't subtle. And so most teams still end up sampling. Which means missing the exact exception that caused the outage. The bigger problem: errors are orphaned data. Your exception lands in Sentry. Your logs are in Datadog. Your traces are somewhere else. Root cause analysis becomes a multi-tab archaeology project at 3 am. We built error tracking natively inside Better Stack: the same platform where your logs, traces, metrics, uptime checks, and on-call schedules already live. Errors are just another signal. They belong together. The part that changes how your team works: Our AI SRE doesn't just surface errors. It fixes them. See a new exception? One click. The AI SRE analyzes the full context, from stack traces, environment variables, browser sessions, related logs and recent deploys, and opens a pull request. Not a ticket. Not a summary. A pull request with the fix. This is what happens when error tracking is fully integrated with the rest of your observability stack instead of bolted on separately. The AI has everything it needs to actually act. The migration is trivial: 1. Keep your existing Sentry SDK. Don't touch a single line of instrumentation code. 2. Point the DSN at Better Stack. 3. Done. Errors flow in. Your dashboards work. Your alerts work. 4. New exception appears. Click "Fix with AI SRE." Pull request lands in your repo. 5. Review, merge, close. That's the whole workflow. The AI angle is real, not a marketing badge. LLMs are genuinely good at fixing bugs if they have full context. The reason AI coding assistants sometimes frustrate engineers is incomplete information, not the model. We solve that by giving the AI SRE your entire telemetry stack as context. Stack traces, logs, traces, service maps, previous incidents and much more. All of it, in one place, at the moment it matters. Observability tools are only useful if you actually ingest all your data. At current prices of other tools, most teams can't afford to. Now you can, and your AI SRE can actually do something about it.
0:20

Today, we're making Error Tracking by Better Stack generally available. Sentry-compatible. AI-native. At 1/6th the price. Here's why we built it, and how to get the most out of it. What's wrong with error tracking today? Most teams use Sentry. It's solid! But at scale, the bills get brutal. Just 100M exceptions with 90 day lookback? ~$30,000 on Sentry. We charge ~$5,000 for the exact same thing. The math isn't subtle. And so most teams still end up sampling. Which means missing the exact exception that caused the outage. The bigger problem: errors are orphaned data. Your exception lands in Sentry. Your logs are in Datadog. Your traces are somewhere else. Root cause analysis becomes a multi-tab archaeology project at 3 am. We built error tracking natively inside Better Stack: the same platform where your logs, traces, metrics, uptime checks, and on-call schedules already live. Errors are just another signal. They belong together. The part that changes how your team works: Our AI SRE doesn't just surface errors. It fixes them. See a new exception? One click. The AI SRE analyzes the full context, from stack traces, environment variables, browser sessions, related logs and recent deploys, and opens a pull request. Not a ticket. Not a summary. A pull request with the fix. This is what happens when error tracking is fully integrated with the rest of your observability stack instead of bolted on separately. The AI has everything it needs to actually act. The migration is trivial: 1. Keep your existing Sentry SDK. Don't touch a single line of instrumentation code. 2. Point the DSN at Better Stack. 3. Done. Errors flow in. Your dashboards work. Your alerts work. 4. New exception appears. Click "Fix with AI SRE." Pull request lands in your repo. 5. Review, merge, close. That's the whole workflow. The AI angle is real, not a marketing badge. LLMs are genuinely good at fixing bugs if they have full context. The reason AI coding assistants sometimes frustrate engineers is incomplete information, not the model. We solve that by giving the AI SRE your entire telemetry stack as context. Stack traces, logs, traces, service maps, previous incidents and much more. All of it, in one place, at the moment it matters. Observability tools are only useful if you actually ingest all your data. At current prices of other tools, most teams can't afford to. Now you can, and your AI SRE can actually do something about it.

Juraj Masar

14,920 görüntüleme • 3 ay önce

Most companies don't realize they have a documentation problem until everyone already depends on it. Customers use it. New hires use it. Engineers use it. And when documentation falls out of date, the whole system starts working against itself People stop trusting what they're reading Teams lose context And nobody can fix it, because the problem is everywhere at once The longer it goes unfixed, the harder it is to untangle That's the opportunity Manicule saw They're building an AI-native DevRel company for developer tools - owning documentation, technical content, GEO, and distribution across social channels. The premise isn't that AI should replace expertise. It's that expertise should scale. Their AI agents audit and test at scale. Their humans own the architecture, the writing, and the creative direction. Every review improves the system Every project creates more context. Every iteration raises the bar What started as a highly manual business - helping developer companies create better technical content - has become a scalable AI-native operation Today, Manicule works with some of the fastest-growing developer tool companies - including Supermemory, Greptile, and Reducto - has scaled fast over the last few months, and has more demand than it can take on. Not because they publish more content. Because they help developer companies create content developers actually trust. 🎙️ Naman Bansal & Shreyans Jain , Co-founders Manicule (YC P26) on Fondo.com START Huge thanks to Numeral for making this episode possible!
1:45

Most companies don't realize they have a documentation problem until everyone already depends on it. Customers use it. New hires use it. Engineers use it. And when documentation falls out of date, the whole system starts working against itself People stop trusting what they're reading Teams lose context And nobody can fix it, because the problem is everywhere at once The longer it goes unfixed, the harder it is to untangle That's the opportunity Manicule saw They're building an AI-native DevRel company for developer tools - owning documentation, technical content, GEO, and distribution across social channels. The premise isn't that AI should replace expertise. It's that expertise should scale. Their AI agents audit and test at scale. Their humans own the architecture, the writing, and the creative direction. Every review improves the system Every project creates more context. Every iteration raises the bar What started as a highly manual business - helping developer companies create better technical content - has become a scalable AI-native operation Today, Manicule works with some of the fastest-growing developer tool companies - including Supermemory, Greptile, and Reducto - has scaled fast over the last few months, and has more demand than it can take on. Not because they publish more content. Because they help developer companies create content developers actually trust. 🎙️ Naman Bansal & Shreyans Jain , Co-founders Manicule (YC P26) on Fondo.com START Huge thanks to Numeral for making this episode possible!

David J Phillips

48,703 görüntüleme • 1 ay önce

AI shouldn't replace therapists. It should help them spend more time being therapists. Not because AI won't get smarter Because good therapy isn't just information It's trust It's compassion It's the human element. Most therapists spend only about half their time doing therapy The other half? Running the business Notes. Paperwork. Marketing. Insurance claims. Klarify automates the work around the session so therapists can focus on the work only they can do Today, more than 7,000 therapists use the platform The result is clear: they spend less time running a business, and more time doing the work only they can do 🎙️Moody Abdul, CEO & Co-Founder Klarify (YC P26) on Fondo.com START Huge thanks to Rippling for making this episode possible!
1:09

AI shouldn't replace therapists. It should help them spend more time being therapists. Not because AI won't get smarter Because good therapy isn't just information It's trust It's compassion It's the human element. Most therapists spend only about half their time doing therapy The other half? Running the business Notes. Paperwork. Marketing. Insurance claims. Klarify automates the work around the session so therapists can focus on the work only they can do Today, more than 7,000 therapists use the platform The result is clear: they spend less time running a business, and more time doing the work only they can do 🎙️Moody Abdul, CEO & Co-Founder Klarify (YC P26) on Fondo.com START Huge thanks to Rippling for making this episode possible!

David J Phillips

88,762 görüntüleme • 1 ay önce

Jordan Peterson: "If you can't fix your room, you can't fix your life" "Why should you even bother improving yourself? The answer is something like: so you don't suffer anymore stupidly than you have to. And maybe so others don't have to either. It's not some casual self-help doctrine. If you don't organize yourself properly, you'll pay for it. In a big way. And so will the people around you." Peterson continues: "You can say, 'Well, I don't care about that.' But that's actually not true, you do care about it. Because if you're in pain, you will care about it. It's very rare that you can find someone in excruciating pain who would say, 'Well, it would be no better if I was out of this.' Pain brings the idea that it would be better if it didn't exist along with it. It's incontrovertible." On how to start: "Look around for something that bothers you and see if you can fix it. You can do this in a room. Sit in your bedroom and think: 'If I wanted to spend ten minutes making this room better, what would I have to do?' You have to ask yourself that, it's a genuine question. And things will pop out. There's a stack of papers bugging you. Some rubbish behind your computer monitor you haven't attended to for six months. Cables tangled up." He explains why this matters: "If you were coming to see me for psychotherapy, the easiest thing would be to get you to organize your room. You think, is that psychotherapy? It depends on how you conceive the limits of your being. Start where you can start. If something announces itself as in need of repair that you could repair, fix it. Fix a hundred things like that, your life will be a lot different." On fixing what you repeat every day: "People tend to think of their daily routines as trivial. You get up, brush your teeth, have breakfast. Those probably constitute 50% of your life. People think, they're mundane, I don't need to pay attention to them. No, that's exactly wrong. The things you do every day are the most important things you do. Hands down. Just do the arithmetic." On staying within your competence: "Sometimes you don't know how to fix something. Imagine you're walking down the street and there's a guy who's alcoholic and schizophrenic and has been homeless for ten years. That's a problem. It would be good if you could fix it, but you haven't got a clue. You walk around that and go find something you could fix. Just because something announces itself as in need of repair doesn't mean it's you, right then and there, who should repair it. You have to have some humility. You don't walk up to a helicopter that isn't working and just start tinkering away." Peterson shares the key insight: "As soon as you give your mind a genuine aim, it'll reconfigure the world in keeping with that aim. That's actually how you see to begin with. You've all seen the video where you watch basketballs being tossed back and forth, and while you're doing that, a gorilla walks into the middle of the video and you don't see it. If you thought about that experiment for five years, that would be about the right amount of time to spend thinking about it." He explains what it reveals: "What it shows you is that you see what you aim at. If you can get one thing through your head, that would be a good one. You see what you aim at. One inference you might draw from that is: be careful what you aim at. What you aim at determines the way the world manifests itself to you. So if the world is manifesting itself in a very negative way, one thing to ask is: are you aiming at the right thing?"
6:59

Jordan Peterson: "If you can't fix your room, you can't fix your life" "Why should you even bother improving yourself? The answer is something like: so you don't suffer anymore stupidly than you have to. And maybe so others don't have to either. It's not some casual self-help doctrine. If you don't organize yourself properly, you'll pay for it. In a big way. And so will the people around you." Peterson continues: "You can say, 'Well, I don't care about that.' But that's actually not true, you do care about it. Because if you're in pain, you will care about it. It's very rare that you can find someone in excruciating pain who would say, 'Well, it would be no better if I was out of this.' Pain brings the idea that it would be better if it didn't exist along with it. It's incontrovertible." On how to start: "Look around for something that bothers you and see if you can fix it. You can do this in a room. Sit in your bedroom and think: 'If I wanted to spend ten minutes making this room better, what would I have to do?' You have to ask yourself that, it's a genuine question. And things will pop out. There's a stack of papers bugging you. Some rubbish behind your computer monitor you haven't attended to for six months. Cables tangled up." He explains why this matters: "If you were coming to see me for psychotherapy, the easiest thing would be to get you to organize your room. You think, is that psychotherapy? It depends on how you conceive the limits of your being. Start where you can start. If something announces itself as in need of repair that you could repair, fix it. Fix a hundred things like that, your life will be a lot different." On fixing what you repeat every day: "People tend to think of their daily routines as trivial. You get up, brush your teeth, have breakfast. Those probably constitute 50% of your life. People think, they're mundane, I don't need to pay attention to them. No, that's exactly wrong. The things you do every day are the most important things you do. Hands down. Just do the arithmetic." On staying within your competence: "Sometimes you don't know how to fix something. Imagine you're walking down the street and there's a guy who's alcoholic and schizophrenic and has been homeless for ten years. That's a problem. It would be good if you could fix it, but you haven't got a clue. You walk around that and go find something you could fix. Just because something announces itself as in need of repair doesn't mean it's you, right then and there, who should repair it. You have to have some humility. You don't walk up to a helicopter that isn't working and just start tinkering away." Peterson shares the key insight: "As soon as you give your mind a genuine aim, it'll reconfigure the world in keeping with that aim. That's actually how you see to begin with. You've all seen the video where you watch basketballs being tossed back and forth, and while you're doing that, a gorilla walks into the middle of the video and you don't see it. If you thought about that experiment for five years, that would be about the right amount of time to spend thinking about it." He explains what it reveals: "What it shows you is that you see what you aim at. If you can get one thing through your head, that would be a good one. You see what you aim at. One inference you might draw from that is: be careful what you aim at. What you aim at determines the way the world manifests itself to you. So if the world is manifesting itself in a very negative way, one thing to ask is: are you aiming at the right thing?"

Jaynit

68,550 görüntüleme • 3 ay önce

Peter Steinberger Quietly Started A Shift That Makes Claude 35x Cheaper To Run The way Claude Code talks to tools matters more than people think. Most use MCP, and it quietly eats tokens, it loads everything into context every time, even tools you never call. One benchmark: MCP burned 35x more tokens than a CLI on the same task. Peter Steinberger, the OpenClaw guy, got annoyed by this and started building lean CLIs himself. That kicked off a tool called Printing Press. You point Claude Code at any website, even ones with no API like ESPN or Craigslist, and it builds a small command tool for it in about 10 minutes. In one demo, a request pulled 132,000 tokens of raw data, but the tool processed it locally and only handed Claude a 2,000-token summary. The rest never touched the context window. It also comes with ~50 ready-made tools you can grab right away. To start, point Claude Code at the links from and ask it to set it up. Bookmark this.
14:45

Peter Steinberger Quietly Started A Shift That Makes Claude 35x Cheaper To Run The way Claude Code talks to tools matters more than people think. Most use MCP, and it quietly eats tokens, it loads everything into context every time, even tools you never call. One benchmark: MCP burned 35x more tokens than a CLI on the same task. Peter Steinberger, the OpenClaw guy, got annoyed by this and started building lean CLIs himself. That kicked off a tool called Printing Press. You point Claude Code at any website, even ones with no API like ESPN or Craigslist, and it builds a small command tool for it in about 10 minutes. In one demo, a request pulled 132,000 tokens of raw data, but the tool processed it locally and only handed Claude a 2,000-token summary. The rest never touched the context window. It also comes with ~50 ready-made tools you can grab right away. To start, point Claude Code at the links from and ask it to set it up. Bookmark this.

Ridark

32,351 görüntüleme • 19 gün önce

Asmongold explains the obvious reason Nick Fuentes doesn't lead with his extreme views on mainstream podcasts "Has it ever occurred to you that you don't come out swinging on day one with your most extreme viewpoints? You want to get people to start agreeing with you so they see you as reasonable. Then over time you move into the more extreme viewpoints and transition them to that. That's the way it works. That's what he's obviously doing." "How do you boil a frog? You don't throw it in a pot of boiling water. You put it in water and then you slowly turn up the temperature. That's what you do. How do you not understand this?"
1:01

Asmongold explains the obvious reason Nick Fuentes doesn't lead with his extreme views on mainstream podcasts "Has it ever occurred to you that you don't come out swinging on day one with your most extreme viewpoints? You want to get people to start agreeing with you so they see you as reasonable. Then over time you move into the more extreme viewpoints and transition them to that. That's the way it works. That's what he's obviously doing." "How do you boil a frog? You don't throw it in a pot of boiling water. You put it in water and then you slowly turn up the temperature. That's what you do. How do you not understand this?"

Asmongold Updates

29,766 görüntüleme • 13 gün önce

I solved building decks with AI agents — by giving them a CLI tool like Powerpoint or Google Slides. AI could already make a beautiful deck if you asked it to using Ant's pptx skill. The problem was working with it. If it made one alignment mistake, fixing it on one slide would break something on another, and it became a game of whack-a-mole. One time I spent two days playing AI roulette, hoping the next prompt would finally fix the thing, and ended up building the whole deck by hand because I was on a deadline. So I built Hands-on Deck. And the reason it works is that this isn't just a skill — this is PowerPoint. The actual application: PowerPoint, Google Slides, Keynote, whatever you use. This is that, but for an agent, presented as a CLI. Every gesture you make in a deck app maps to a command. Click a box and type, drag a shape from here to there, look at a slide – agent can do it all in a command. And that changes how the agent behaves. With this CLI it works and thinks like a designer — it looks, makes an edit, looks again, makes another surgical edit. Compare that to Anthropic's pptx skill, built on the idea that Claude is a great programmer: it literally writes code to manipulate the deck, hand-editing XML and hoping it doesn't break anything else in the middle. The real test isn't creating something once — it's whether it can make surgical edits like you want. That's what I did in this video walkthrough and my claude crushed it! Check it out for yourself. So decks can be built like a designer now — with real flavor and taste. If you spend hours every week on decks, this gives those hours back. You can install it as a skill in Claude Code, Codex, whatever you use. Works every harness that supports skills. Let me know if you make something cool with it.
21:00

I solved building decks with AI agents — by giving them a CLI tool like Powerpoint or Google Slides. AI could already make a beautiful deck if you asked it to using Ant's pptx skill. The problem was working with it. If it made one alignment mistake, fixing it on one slide would break something on another, and it became a game of whack-a-mole. One time I spent two days playing AI roulette, hoping the next prompt would finally fix the thing, and ended up building the whole deck by hand because I was on a deadline. So I built Hands-on Deck. And the reason it works is that this isn't just a skill — this is PowerPoint. The actual application: PowerPoint, Google Slides, Keynote, whatever you use. This is that, but for an agent, presented as a CLI. Every gesture you make in a deck app maps to a command. Click a box and type, drag a shape from here to there, look at a slide – agent can do it all in a command. And that changes how the agent behaves. With this CLI it works and thinks like a designer — it looks, makes an edit, looks again, makes another surgical edit. Compare that to Anthropic's pptx skill, built on the idea that Claude is a great programmer: it literally writes code to manipulate the deck, hand-editing XML and hoping it doesn't break anything else in the middle. The real test isn't creating something once — it's whether it can make surgical edits like you want. That's what I did in this video walkthrough and my claude crushed it! Check it out for yourself. So decks can be built like a designer now — with real flavor and taste. If you spend hours every week on decks, this gives those hours back. You can install it as a skill in Claude Code, Codex, whatever you use. Works every harness that supports skills. Let me know if you make something cool with it.

Nityesh

68,221 görüntüleme • 22 gün önce

“What did you think of Lando being booed at race because people and I've seen it online as well say he doesn't deserve the title because McLaren favored him over his teammate. Do you think that's total nonsense?” Jacques Villeneuve: “That's a little bit ridiculous. When there was some booing in some races, that was embarrassing. You should never boo a driver that's clean, doesn't do anything dirty, on track is respectful, and on top of it is super fast. What's wrong with people? That was embarrassing. And, had it been that Piastri was a second a lap faster than him and somehow Lando was winning because a lot of things were happening, his car breaking down every time, then you could start thinking, okay, that's really not cool. That's not fair. But that wasn't the case. And in the second half, Norris has been faster right at the beginning as well, last year as well. So there's this whole middle of the season where Piastri was driving a lot better than Norris and was getting the points. Norris had an engine blowing up, not Piastri. And so those fans, they don't look at that either. You have to look at the whole picture, at the whole season. And suddenly if your favorite is starting to go backwards, you just got to bite the bullet and accept it. Your favorite is just going backwards. That doesn't mean that the other one is treated better or the other one is undeserving just because the one you're a fan of is not winning right now. That’s really wrong. If you're a fan of the sport, then you have to be a fan of the sport and understand when your driver is maybe not cutting it at this point in time, even though he was before and he will in the future again. It's all a question of timing. But that's the price we have to pay now with social media and how big F1 has become. It's very passionate. The people are passionate and once, you know, fans come from fanatism, you stop thinking, when you get in that mindset and it happens to all of us. You want something so much that you get attached and you cannot - it's hard to start seeing reality. So you will try to mold the reality to your thought process and if your champion is not winning then it cannot be his fault. It has to be something from the outside. It has to be the team destroying his chance or not favoring and so on and so on and so on. But there's nothing concrete behind those comments. It's pure fandom and it'll always be like this. And ultimately it's not a bad thing. You know drivers at that - sportsman at that level have to grow a thick skin. If not, you don't deserve to be there. You just have to have a thick skin because they're all very happy to get the compliments. They love it when it's just positive, but it gets balanced out with negatives and you need to be able to take and accept the negatives as well. It goes both ways. You cannot have the good. You just have to be a thick skin and know that it's part and parcels of what's going on. And in one month, it will be forgotten and maybe everything will change and it be the other driver that suddenly will be criticized and so on. So, it's just that's just the way it is.”
3:10

“What did you think of Lando being booed at race because people and I've seen it online as well say he doesn't deserve the title because McLaren favored him over his teammate. Do you think that's total nonsense?” Jacques Villeneuve: “That's a little bit ridiculous. When there was some booing in some races, that was embarrassing. You should never boo a driver that's clean, doesn't do anything dirty, on track is respectful, and on top of it is super fast. What's wrong with people? That was embarrassing. And, had it been that Piastri was a second a lap faster than him and somehow Lando was winning because a lot of things were happening, his car breaking down every time, then you could start thinking, okay, that's really not cool. That's not fair. But that wasn't the case. And in the second half, Norris has been faster right at the beginning as well, last year as well. So there's this whole middle of the season where Piastri was driving a lot better than Norris and was getting the points. Norris had an engine blowing up, not Piastri. And so those fans, they don't look at that either. You have to look at the whole picture, at the whole season. And suddenly if your favorite is starting to go backwards, you just got to bite the bullet and accept it. Your favorite is just going backwards. That doesn't mean that the other one is treated better or the other one is undeserving just because the one you're a fan of is not winning right now. That’s really wrong. If you're a fan of the sport, then you have to be a fan of the sport and understand when your driver is maybe not cutting it at this point in time, even though he was before and he will in the future again. It's all a question of timing. But that's the price we have to pay now with social media and how big F1 has become. It's very passionate. The people are passionate and once, you know, fans come from fanatism, you stop thinking, when you get in that mindset and it happens to all of us. You want something so much that you get attached and you cannot - it's hard to start seeing reality. So you will try to mold the reality to your thought process and if your champion is not winning then it cannot be his fault. It has to be something from the outside. It has to be the team destroying his chance or not favoring and so on and so on and so on. But there's nothing concrete behind those comments. It's pure fandom and it'll always be like this. And ultimately it's not a bad thing. You know drivers at that - sportsman at that level have to grow a thick skin. If not, you don't deserve to be there. You just have to have a thick skin because they're all very happy to get the compliments. They love it when it's just positive, but it gets balanced out with negatives and you need to be able to take and accept the negatives as well. It goes both ways. You cannot have the good. You just have to be a thick skin and know that it's part and parcels of what's going on. And in one month, it will be forgotten and maybe everything will change and it be the other driver that suddenly will be criticized and so on. So, it's just that's just the way it is.”

naenia ¹ ⁶³

29,833 görüntüleme • 7 ay önce

anthropic's head of product just revealed how they're able to ship faster than any other AI company. their secret: "side quest maxxing." here's how it works: instead of long-term roadmaps, anthropic runs on unplanned afternoon experiments. anyone on the team gets full freedom to spend an afternoon prototyping an idea and show it to the team. you get to skip the approval process entirely. then, employees at anthropic try it. if they keep using it the next day and the day after that, it gets polished into a real feature. if nobody touches it again, it dies. that's the whole process. claude code on desktop started as one engineer's afternoon project. he wanted it to work on desktop so he built a prototype. people on the team started using it immediately. so they shipped it. the todo list feature started the same way. someone built it, the team adopted it internally, and it became one of the most-used parts of the product. plugins started when one engineer shared a spec with claude code and the prototype that came back was close to production-ready. went from idea to working feature in a single session. they also killed standup meetings. instead of telling people what you're working on, you just show a working demo. all walk no talk basically the team structure makes this possible. > designers ship code. > engineers make product decisions. > product managers build prototypes. everyone can take an idea from concept to working demo without waiting on anyone else. the biggest features at a $380b company came from afternoon experiments that nobody asked for. honestly this matches my own experience cooking with ai. some of the best workflows i use every day came from just fucking around. opening a session with zero intention and asking claude what it can do, or jamming on a random idea to see where it goes. if you're only using ai for tasks you already have in mind, you're missing the best part. open a session with no agenda. ask it to surprise you. try building something stupid. half the time it goes nowhere. the other half it becomes the thing you use most. you need to be sidequestmaxxing.
0:30

anthropic's head of product just revealed how they're able to ship faster than any other AI company. their secret: "side quest maxxing." here's how it works: instead of long-term roadmaps, anthropic runs on unplanned afternoon experiments. anyone on the team gets full freedom to spend an afternoon prototyping an idea and show it to the team. you get to skip the approval process entirely. then, employees at anthropic try it. if they keep using it the next day and the day after that, it gets polished into a real feature. if nobody touches it again, it dies. that's the whole process. claude code on desktop started as one engineer's afternoon project. he wanted it to work on desktop so he built a prototype. people on the team started using it immediately. so they shipped it. the todo list feature started the same way. someone built it, the team adopted it internally, and it became one of the most-used parts of the product. plugins started when one engineer shared a spec with claude code and the prototype that came back was close to production-ready. went from idea to working feature in a single session. they also killed standup meetings. instead of telling people what you're working on, you just show a working demo. all walk no talk basically the team structure makes this possible. > designers ship code. > engineers make product decisions. > product managers build prototypes. everyone can take an idea from concept to working demo without waiting on anyone else. the biggest features at a $380b company came from afternoon experiments that nobody asked for. honestly this matches my own experience cooking with ai. some of the best workflows i use every day came from just fucking around. opening a session with zero intention and asking claude what it can do, or jamming on a random idea to see where it goes. if you're only using ai for tasks you already have in mind, you're missing the best part. open a session with no agenda. ask it to surprise you. try building something stupid. half the time it goes nowhere. the other half it becomes the thing you use most. you need to be sidequestmaxxing.

Ole Lehmann

105,994 görüntüleme • 2 ay önce

🚨 launch alert 🚨 most SEO audit tools give you a tacky report and leave you stuck with jargon and numbers in red - they never tell you how to fix it so I built something different 👉 enter your domain and get a clean SEO report with a ready-to-use PROMPT you copy & paste straight into ChatGPT, Claude, or Cursor to fix everything get a full crawl across 8 SEO pillars - foundation, content, metadata, performance, crawl & index, media, architecture, and AI search readiness every issue is flagged, prioritized, and explained 100% free - no setup, just takes a few seconds go fix your SEO 💥 (600+ websites audited in the last 24 hours btw 👀)
0:26

🚨 launch alert 🚨 most SEO audit tools give you a tacky report and leave you stuck with jargon and numbers in red - they never tell you how to fix it so I built something different 👉 enter your domain and get a clean SEO report with a ready-to-use PROMPT you copy & paste straight into ChatGPT, Claude, or Cursor to fix everything get a full crawl across 8 SEO pillars - foundation, content, metadata, performance, crawl & index, media, architecture, and AI search readiness every issue is flagged, prioritized, and explained 100% free - no setup, just takes a few seconds go fix your SEO 💥 (600+ websites audited in the last 24 hours btw 👀)

Tibo

22,317 görüntüleme • 3 ay önce

I asked anamitra why every VC is starting an accelerator: "As more traditional venture funds become stage agnostic, they don't want to lose sight of the formation stage companies. If you lose that, then you become one of 20 VC's trying to invest in any one round. In the past, they've had seed programs for this. And Seed programs historically have been promoted by younger people at those funds, because they're closer to the metal. And seed funds have gone through cycles. They grow, and then they collapse when founders realize Seed deals at these stage agnostic fund don't convert. So they got disintermediated, and the best founders all go to the angels and the seed funds. And then they grow again, and then they collapse again. And every time, all the young people leave the big funds. And that has happened over cycles for a long time. The Series A funds have been trying to penetrate Seed for a long time. And even if you didn't have a good Seed program, you had YC, and Techstars, and all the other accelerators, which would give you great deal flow. And you could go to the demo days and pick up the good ones. And the cool thing, back in the day, was you didn't actually have to wait for the demo day. You could access the companies before demo day, and make the deals beforehand. Even if you wait until demo day, it's wasn't that bad. You could still get decent ownership at $15m or $10m post-money valuations. And then, YC made two changes to their program. One of the big changes that they made sure companies wait until demo day. And the second was introducing the $375k uncapped MFM SAFE. Which incentivized founders to raise their next round at as high a price as possible. So now, founders were incentivized to raise at demo day, and at as high a price as possible. What used to be $10-15m valuation, are now $20m, $25m, and even up to $40m. And so, many funds were who were reliant on deals from YC saw their entry prices suddenly shoot up. And the question for them became, what do we do? If your average entry point was $10 million on a YC deal, it suddenly went up to $40m. You basically cut your returns by 75%. So if your strategy was doing all these YC deals, and getting a 4x return on your fund, everything was good. Suddenly with the new entry prices, you're getting 1x on your fund. And that's not good. For founders, YC gives you a halo, some brand value. They do a ton of programming and help you learn about building a company. Every founder wants to be part of that. No question about it. Look at the roster of companies that they've invested in. At the same time, there are some founders who may want a better option. Who may believe that their company is worth more than $1.8 million. And they should have an option. So I think, investors saw that their entry prices at demo day were going up. And founders are entering these accelerators at $1.8m post. And investors thought, there has to be a price in the middle that we can offer and give founders another option. And that's why they've all started accelerators. And as a result, what's happening is founders now have more choice. So the question now becomes, what do the best founders decide to do? Now that they have more options, what are they going to pick? And so, it makes a lot of sense to me to see these other funds try their own programs. And if they are committed, and focused, and they're able to source and market well, they're going to do really well. As they do really well, that's going to create a positive virtual cycle for future founders to decide which one should they pick. And they'll all have better options. So it's just going to get more competitive. And I would argue, this might have all been started because of the change in the YC deal. If the deal hadn't changed, would we have seen so much downstream impact?"
7:49

I asked anamitra why every VC is starting an accelerator: "As more traditional venture funds become stage agnostic, they don't want to lose sight of the formation stage companies. If you lose that, then you become one of 20 VC's trying to invest in any one round. In the past, they've had seed programs for this. And Seed programs historically have been promoted by younger people at those funds, because they're closer to the metal. And seed funds have gone through cycles. They grow, and then they collapse when founders realize Seed deals at these stage agnostic fund don't convert. So they got disintermediated, and the best founders all go to the angels and the seed funds. And then they grow again, and then they collapse again. And every time, all the young people leave the big funds. And that has happened over cycles for a long time. The Series A funds have been trying to penetrate Seed for a long time. And even if you didn't have a good Seed program, you had YC, and Techstars, and all the other accelerators, which would give you great deal flow. And you could go to the demo days and pick up the good ones. And the cool thing, back in the day, was you didn't actually have to wait for the demo day. You could access the companies before demo day, and make the deals beforehand. Even if you wait until demo day, it's wasn't that bad. You could still get decent ownership at $15m or $10m post-money valuations. And then, YC made two changes to their program. One of the big changes that they made sure companies wait until demo day. And the second was introducing the $375k uncapped MFM SAFE. Which incentivized founders to raise their next round at as high a price as possible. So now, founders were incentivized to raise at demo day, and at as high a price as possible. What used to be $10-15m valuation, are now $20m, $25m, and even up to $40m. And so, many funds were who were reliant on deals from YC saw their entry prices suddenly shoot up. And the question for them became, what do we do? If your average entry point was $10 million on a YC deal, it suddenly went up to $40m. You basically cut your returns by 75%. So if your strategy was doing all these YC deals, and getting a 4x return on your fund, everything was good. Suddenly with the new entry prices, you're getting 1x on your fund. And that's not good. For founders, YC gives you a halo, some brand value. They do a ton of programming and help you learn about building a company. Every founder wants to be part of that. No question about it. Look at the roster of companies that they've invested in. At the same time, there are some founders who may want a better option. Who may believe that their company is worth more than $1.8 million. And they should have an option. So I think, investors saw that their entry prices at demo day were going up. And founders are entering these accelerators at $1.8m post. And investors thought, there has to be a price in the middle that we can offer and give founders another option. And that's why they've all started accelerators. And as a result, what's happening is founders now have more choice. So the question now becomes, what do the best founders decide to do? Now that they have more options, what are they going to pick? And so, it makes a lot of sense to me to see these other funds try their own programs. And if they are committed, and focused, and they're able to source and market well, they're going to do really well. As they do really well, that's going to create a positive virtual cycle for future founders to decide which one should they pick. And they'll all have better options. So it's just going to get more competitive. And I would argue, this might have all been started because of the change in the YC deal. If the deal hadn't changed, would we have seen so much downstream impact?"

The Peel

28,637 görüntüleme • 1 yıl önce

THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this
13:23

THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this

Yarchi

55,345 görüntüleme • 1 ay önce

"We treat software like it is so precious. And in the new world we're going to, it's going to be much more fungible. But that's the good news." Garry Tan on where the moats will be for future YC companies: "That's where taste, agency, and trust matter a lot. This is something that's only crystallized recently. We've been talking about agency and taste for the longest time. Agency is being able to prompt, and taste is being able to do evals." "Trust is the third thing. It's probably the most important. When you have an enterprise company that is selling to real businesses that are relying on you — that's your moat. Your moat is actually trust. They went through the effort to try you, get you onboarded, and incorporate you into how they work."
1:48

"We treat software like it is so precious. And in the new world we're going to, it's going to be much more fungible. But that's the good news." Garry Tan on where the moats will be for future YC companies: "That's where taste, agency, and trust matter a lot. This is something that's only crystallized recently. We've been talking about agency and taste for the longest time. Agency is being able to prompt, and taste is being able to do evals." "Trust is the third thing. It's probably the most important. When you have an enterprise company that is selling to real businesses that are relying on you — that's your moat. Your moat is actually trust. They went through the effort to try you, get you onboarded, and incorporate you into how they work."

TBPN

43,619 görüntüleme • 3 ay önce

Kareem believes capitalism rewards risk more than hard work or skill. He has a really unique way of defining risk and explains why most people never actually take any: "Capitalism rewards risk more than anything else. A lot of people think it's a meritocracy, but there are a lot of people working really hard and not making a lot of money. It doesn't just reward skill either. You can be eating a sword and not making as much as someone doing a YouTube video. A lot of people think they're taking risks, but aren't taking real risks. I talked to one founder who went to a good school, then YC, and he was telling me about his company. He said, 'We serve sales, and we serve recruiting.' I said, 'You have to pick one.' That's where you're actually providing value –– in committing yourself to serving some group of people in some specific way. My definition of risk is you need to genuinely not know what's going to happen, so you're going to discover something new. And it needs to be coupled with a high potential for shame. That's when you can take real risk. When you couple risk and courage, the next part is commitment. You actually need to follow through to see what ends up happening. You can't just quit in the beginning."
1:47

Kareem believes capitalism rewards risk more than hard work or skill. He has a really unique way of defining risk and explains why most people never actually take any: "Capitalism rewards risk more than anything else. A lot of people think it's a meritocracy, but there are a lot of people working really hard and not making a lot of money. It doesn't just reward skill either. You can be eating a sword and not making as much as someone doing a YouTube video. A lot of people think they're taking risks, but aren't taking real risks. I talked to one founder who went to a good school, then YC, and he was telling me about his company. He said, 'We serve sales, and we serve recruiting.' I said, 'You have to pick one.' That's where you're actually providing value –– in committing yourself to serving some group of people in some specific way. My definition of risk is you need to genuinely not know what's going to happen, so you're going to discover something new. And it needs to be coupled with a high potential for shame. That's when you can take real risk. When you couple risk and courage, the next part is commitment. You actually need to follow through to see what ends up happening. You can't just quit in the beginning."

Patrick OShaughnessy

96,049 görüntüleme • 1 ay önce

We’ve partnered with OpenAI to release Sweetspot (YC S23) directly within ChatGPT. Any ChatGPT user can now search over federal contract data - no paid tools required and no Sweetspot subscription needed. We built this on ChatGPT because access to basic federal data shouldn't cost thousands of dollars a year. is public information, and using AI to find the right opportunities shouldn't be a privilege. For Sweetspot customers, it gets even better. You can pull opportunity data straight from ChatGPT and start up your full workflow (qualification, analysis, proposal response) inside Sweetspot. Even if you’re not in government contracting, check it out and share it with your colleagues who are. It’s completely free! Link below.
0:30

We’ve partnered with OpenAI to release Sweetspot (YC S23) directly within ChatGPT. Any ChatGPT user can now search over federal contract data - no paid tools required and no Sweetspot subscription needed. We built this on ChatGPT because access to basic federal data shouldn't cost thousands of dollars a year. is public information, and using AI to find the right opportunities shouldn't be a privilege. For Sweetspot customers, it gets even better. You can pull opportunity data straight from ChatGPT and start up your full workflow (qualification, analysis, proposal response) inside Sweetspot. Even if you’re not in government contracting, check it out and share it with your colleagues who are. It’s completely free! Link below.

sachin

38,374 görüntüleme • 3 ay önce

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.
8:02

Alibaba just dropped a free AI that codes like a $150/hr developer. And it runs on your laptop. Qwen 3 Coder Next has 80 billion parameters but only uses 3 billion at a time. So you get massive model power with tiny model speed. The real kicker? It handles 256,000 tokens of context. That's your entire codebase. Every file. All at once. People are building 2D games in seconds. Full IDE integrations that write, test, and fix code automatically. Custom business tools without hiring devs. It works with OpenClaw, Claude Code, and every major coding tool. No complicated setup. Just download and go. Completely open source. Zero API queues. You own it. Your competitors are using this right now.

Julian Goldie SEO

30,259 görüntüleme • 5 ay önce

karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch
24:21

karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch

GREG ISENBERG

435,542 görüntüleme • 4 ay önce