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Why did Meta build its own internal developer tooling instead of using industry-standard solutions like GitHub? And what do their systems "Sandcastle," "Landcastle", "Butterflybot" and "Phabricator" do? Tomas Reimers, former Meta engineer and co-founder of Graphite , joins the show to talk about Meta's custom developer tools – many...

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Gergely Orosz

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37,722 görüntüleme • 1 yıl önce •via X (Twitter)

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Jason Ho profil fotoğrafı
Jason Ho1 yıl önce

@TomasReimers @withgraphite sounds like when he starts listing the fb internal tools

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ARK Electronics1 yıl önce

Excited about the latest tech for your drone product? Our NDAA-compliant, US-made flight controllers are designed to accelerate your path to market and provide a solid platform for developing your autonomous software. Check them out! #Drones #UAV #UAS #Robotics #MadeInUSA

Ardit Bajraktari profil fotoğrafı
Ardit Bajraktari1 yıl önce

@TomasReimers @withgraphite Worked there. Some internal tools are good, some are bad. Huge monorepos are a bad idea for many reasons. We had random merges in RL breaking code/builds in IG. Monorepos made sense in 2010, when the whole codebase was 3gb, and not now when it is 300gb+. Don't copy big tech

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tony grimes1 yıl önce

@TomasReimers @withgraphite NIH syndrome

Gergely Orosz profil fotoğrafı
Gergely Orosz1 yıl önce

If you listen closer, not really: Back in 2010, Facebook already had more than 1,000 devs. Git was barely coming around. GitHub was not even founded. And there were no tools for companies this size - and we've not even talked about build, experimentation etc. Especially not for one with this size of a monorepo! And today, Facebook serves closer to 3B people per day... again not something that there's vendor solutions for Sometimes you really are at the scale where either you build yourself, or you handicap yourself with tools that are not a fit

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MJ | The Waitlist Guy1 yıl önce

@TomasReimers @withgraphite if you want to talk to someone in the monorepo game... @victorsavkin should be first on your list. ex google engineer and co-founder of @NxDevTools.

Arnav Gupta profil fotoğrafı
Arnav Gupta1 yıl önce

@TomasReimers @withgraphite Haven’t listened to it yet - EdenFS not covered?

Jack Munro profil fotoğrafı
Jack Munro1 yıl önce

@TomasReimers @withgraphite Sounds like a krazam video

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Why is observability so hard to do well - and so expensive, in general? What is "Observability 2.0" and is Open Telemetry any good? In today's episode of The Pragmatic Engineer Podcast, we answer all of these with Charity Majors , co-author of the O'Reilly book "Observability Engineering," former engineer at Parse/Facebook, and cofounder and CTO at Honeycomb Watch it here: • YouTube: • Apple: • Spotify: • Summary and transcript: Brought to you by our wonderful sponsors - check out their offerings: • Sonar — Trust your developers – verify your AI-generated code. • Vanta — Automate compliance and simplify security with Vanta ---- Topics we cover in this episode: • What is observability? Charity’s take • What is “Observability 2.0?” • Why Charity is a fan of platform teams • Why DevOps is an overloaded term: and probably no longer relevant • What is cardinality? And why does it impact the cost of observability so much? • How OpenTelemetry solves for vendor lock-in • Why Honeycomb wrote its own database • Why having good observability should be a prerequisite to adding AI code or using AI agents • And more! --- My biggest takeaways: 1. The DevOps movement feels like it’s in its final days, having served its purpose. 2. Lots of people get dashboards wrong! Charity doesn’t think that static dashboards are helpful to engineering teams at all. In fact, misusing dashboards is one of the most common observability practices. 3. Observability will be especially important for AI use cases in these ways: a) o11y for LLMs: to get data on how they behave and to be able to debug behaviors. This is relevant for teams building and operating AI models. b) o11y for code generated by AI: the generated code should have the right amount of observability in place. Once the code is deployed to production, developers need to be able to get a sense of how the code is behaving there!
0:46

Why is observability so hard to do well - and so expensive, in general? What is "Observability 2.0" and is Open Telemetry any good? In today's episode of The Pragmatic Engineer Podcast, we answer all of these with Charity Majors , co-author of the O'Reilly book "Observability Engineering," former engineer at Parse/Facebook, and cofounder and CTO at Honeycomb Watch it here: • YouTube: • Apple: • Spotify: • Summary and transcript: Brought to you by our wonderful sponsors - check out their offerings: • Sonar — Trust your developers – verify your AI-generated code. • Vanta — Automate compliance and simplify security with Vanta ---- Topics we cover in this episode: • What is observability? Charity’s take • What is “Observability 2.0?” • Why Charity is a fan of platform teams • Why DevOps is an overloaded term: and probably no longer relevant • What is cardinality? And why does it impact the cost of observability so much? • How OpenTelemetry solves for vendor lock-in • Why Honeycomb wrote its own database • Why having good observability should be a prerequisite to adding AI code or using AI agents • And more! --- My biggest takeaways: 1. The DevOps movement feels like it’s in its final days, having served its purpose. 2. Lots of people get dashboards wrong! Charity doesn’t think that static dashboards are helpful to engineering teams at all. In fact, misusing dashboards is one of the most common observability practices. 3. Observability will be especially important for AI use cases in these ways: a) o11y for LLMs: to get data on how they behave and to be able to debug behaviors. This is relevant for teams building and operating AI models. b) o11y for code generated by AI: the generated code should have the right amount of observability in place. Once the code is deployed to production, developers need to be able to get a sense of how the code is behaving there!

Gergely Orosz

25,485 görüntüleme • 1 yıl önce

John Ousterhout is a legend in software design - and so a great person to ask: "How will AI coding tools change software engineering and design?" John is the author of A Philosophy of Software Design, taught software design at Stanford, (possibly the first and only software design class for university students) created the Tcl programming language - and currently is busy contributing to the Linux Kernel (!) In this episode of The Pragmatic Engineer, John joins me to talk about why design still matters and how most teams struggle to get it right. We dive into his book A Philosophy of Software Design, unpack the difference between top-down and bottom-up approaches, and explore why some popular advice, like writing short methods or relying heavily on TDD, does not hold up, according to John. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by our wonderful sponsors: •⁠ CodeRabbit — Cut code review time and bugs in half. Use the code PRAGMATIC to get one month free. •⁠ Modal — The cloud platform for building AI applications. Try it at --- Three of my takeaways from talking with John: 𝟭. 𝗧𝗵𝗲 𝗲𝘅𝗽𝗹𝗼𝘀𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝗰𝗼𝘂𝗹𝗱 𝗺𝗮𝗸𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘀𝗶𝗴𝗻 𝗺𝗼𝗿𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝘁𝗵𝗮𝗻 𝗯𝗲𝗳𝗼𝗿𝗲. Currently, AI coding tools and agents are akin to “tactical tornadoes” that code fast, fix issues fast… while creating new issues and adding tech debt. John doesn’t see the current tools being able to replace high-level design. And so software design could be more important than before – thanks to more code being written than before! 𝟮. 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘀𝗶𝗴𝗻 𝗶𝘀 𝗮 𝗱𝗲𝗰𝗼𝗺𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. How do you take a large system and divide it into smaller units that you can implement relatively independently? John believes that the most important idea for all of computer science is just this – decomposition. If you can break up complicated problems into smaller parts: you can solve so many problems! 𝟯. 𝗧𝗲𝘀𝘁 𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 (𝗧𝗗𝗗) 𝘄𝗼𝗿𝗸𝘀 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝗴𝗼𝗼𝗱 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘀𝗶𝗴𝗻. John firmly believes that TDD is counter-productive because it forces thinking about the small details before thinking about the high-level design. This observation could explain why TDD has not gained much traction in the last decade or so! ... and a plenty more more food for thought in our discussion!
0:56

John Ousterhout is a legend in software design - and so a great person to ask: "How will AI coding tools change software engineering and design?" John is the author of A Philosophy of Software Design, taught software design at Stanford, (possibly the first and only software design class for university students) created the Tcl programming language - and currently is busy contributing to the Linux Kernel (!) In this episode of The Pragmatic Engineer, John joins me to talk about why design still matters and how most teams struggle to get it right. We dive into his book A Philosophy of Software Design, unpack the difference between top-down and bottom-up approaches, and explore why some popular advice, like writing short methods or relying heavily on TDD, does not hold up, according to John. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by our wonderful sponsors: •⁠ CodeRabbit — Cut code review time and bugs in half. Use the code PRAGMATIC to get one month free. •⁠ Modal — The cloud platform for building AI applications. Try it at --- Three of my takeaways from talking with John: 𝟭. 𝗧𝗵𝗲 𝗲𝘅𝗽𝗹𝗼𝘀𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝗰𝗼𝘂𝗹𝗱 𝗺𝗮𝗸𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘀𝗶𝗴𝗻 𝗺𝗼𝗿𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝘁𝗵𝗮𝗻 𝗯𝗲𝗳𝗼𝗿𝗲. Currently, AI coding tools and agents are akin to “tactical tornadoes” that code fast, fix issues fast… while creating new issues and adding tech debt. John doesn’t see the current tools being able to replace high-level design. And so software design could be more important than before – thanks to more code being written than before! 𝟮. 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘀𝗶𝗴𝗻 𝗶𝘀 𝗮 𝗱𝗲𝗰𝗼𝗺𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. How do you take a large system and divide it into smaller units that you can implement relatively independently? John believes that the most important idea for all of computer science is just this – decomposition. If you can break up complicated problems into smaller parts: you can solve so many problems! 𝟯. 𝗧𝗲𝘀𝘁 𝗗𝗿𝗶𝘃𝗲𝗻 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 (𝗧𝗗𝗗) 𝘄𝗼𝗿𝗸𝘀 𝗮𝗴𝗮𝗶𝗻𝘀𝘁 𝗴𝗼𝗼𝗱 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘀𝗶𝗴𝗻. John firmly believes that TDD is counter-productive because it forces thinking about the small details before thinking about the high-level design. This observation could explain why TDD has not gained much traction in the last decade or so! ... and a plenty more more food for thought in our discussion!

Gergely Orosz

16,506 görüntüleme • 1 yıl önce

Why did Amazon move from being a monolith, splitting up into services, despite obsessing about response latency? Turns out it was "software physics:" the monolith crossed the 4GB size that could be deployed in one go. Steve Huynh (Steve Huynh) joins me on The Pragmatic Engineer Podcast to talk about this, and many more learnings about being a Principal Engineer at Amazon - the place where being promoted to this level might be more difficult than at other, similarly large companies. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more • Graphite — The AI developer productivity platform • Augment Code — AI coding assistant that pro engineering teams love
1:15

Why did Amazon move from being a monolith, splitting up into services, despite obsessing about response latency? Turns out it was "software physics:" the monolith crossed the 4GB size that could be deployed in one go. Steve Huynh (Steve Huynh) joins me on The Pragmatic Engineer Podcast to talk about this, and many more learnings about being a Principal Engineer at Amazon - the place where being promoted to this level might be more difficult than at other, similarly large companies. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more • Graphite — The AI developer productivity platform • Augment Code — AI coding assistant that pro engineering teams love

Gergely Orosz

79,836 görüntüleme • 11 ay önce

Here are a few things you probably did not know about Reddit's iOS and Android apps: they are ~2.5M lines of code each, with 500+ screens, and a total of 200 native mobile engineers work on the both of them (including a dedicated iOS and Android mobile platform team) But a few years ago, things looked very different - and Reddit quietly rebuilt their native apps from 2021. Today's conversation goes through what happened and how, with three engineers from Reddit’s mobile platform team who led this work: Lauren Darcey (Head of Mobile Platform), Brandon Kobilansky (iOS Platform Lead), and Eric Kuck (Principal Android Engineer) Watch or listen: • YouTube: • Spotify: • Apple: --- Brought to you by: • Graphite (we've moved to @graphite) — The AI developer productivity platform • Sentry — Error and performance monitoring for developers. Get 150k errors (three months of Team Plan) for free at --- Three of my takeaways from this episode: 𝟭. 𝗣𝗼𝗼𝗿 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗰𝗮𝗻 𝘀𝗹𝗼𝘄 𝗱𝗼𝘄𝗻 𝗮 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 – 𝘀𝗼 𝗽𝗮𝘆 𝗮𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻! One of the reasons Reddit started investing heavily in modernizing its mobile stack was that the “old stack” was slowing down developers. Reddit’s platform team got proof of this simply by asking native engineers about the biggest development-related challenges they face. 𝟮. 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗶𝘀 𝗵𝗮𝗿𝗱 𝘄𝗼𝗿𝗸. Advice from Brandon for anyone looking to work on a platform team: "You should try to work at a tech company for a year or two and actually see what happens after you ship a system — and then the assumptions change! You then have to figure out how to keep this thing going. You get a bunch of software design intuition because you have to like re-evaluate your assumptions for an incredibly long time. If you can do that, you're probably ready for platform stuff." 𝟯. 𝗚𝗲𝗻𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝘁𝗼𝗼𝗹𝘀 𝗳𝗲𝗲𝗹 𝗹𝗶𝗸𝗲 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝗻𝗼𝘁 “𝘁𝗵𝗲𝗿𝗲” 𝘆𝗲𝘁 𝘄𝗶𝘁𝗵 𝗻𝗮𝘁𝗶𝘃𝗲 𝗺𝗼𝗯𝗶𝗹𝗲. LLMs integrated into IDEs seem to be increasingly helpful with backend, fullstack, web and even cross-platform (React Native / Expo) projects. However, Reddit’s mobile team shared that they get a moderate boost from the Apple and Android Studio LLM additions. Native mobile development is distinctively different from web, fullstack and backend coding – and it seems that these IDEs with AI functionality have not done much to optimize for the expereince of native mobile engineers. Over time, this will likely change – but it’s a reminder that there are differences between fullstack, backend and native mobile development.(I wrote a book reflecting on more of the challenges unique to native mobile titled Building Mobile Apps at Scale)
1:02

Here are a few things you probably did not know about Reddit's iOS and Android apps: they are ~2.5M lines of code each, with 500+ screens, and a total of 200 native mobile engineers work on the both of them (including a dedicated iOS and Android mobile platform team) But a few years ago, things looked very different - and Reddit quietly rebuilt their native apps from 2021. Today's conversation goes through what happened and how, with three engineers from Reddit’s mobile platform team who led this work: Lauren Darcey (Head of Mobile Platform), Brandon Kobilansky (iOS Platform Lead), and Eric Kuck (Principal Android Engineer) Watch or listen: • YouTube: • Spotify: • Apple: --- Brought to you by: • Graphite (we've moved to @graphite) — The AI developer productivity platform • Sentry — Error and performance monitoring for developers. Get 150k errors (three months of Team Plan) for free at --- Three of my takeaways from this episode: 𝟭. 𝗣𝗼𝗼𝗿 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗰𝗮𝗻 𝘀𝗹𝗼𝘄 𝗱𝗼𝘄𝗻 𝗮 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 – 𝘀𝗼 𝗽𝗮𝘆 𝗮𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻! One of the reasons Reddit started investing heavily in modernizing its mobile stack was that the “old stack” was slowing down developers. Reddit’s platform team got proof of this simply by asking native engineers about the biggest development-related challenges they face. 𝟮. 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗶𝘀 𝗵𝗮𝗿𝗱 𝘄𝗼𝗿𝗸. Advice from Brandon for anyone looking to work on a platform team: "You should try to work at a tech company for a year or two and actually see what happens after you ship a system — and then the assumptions change! You then have to figure out how to keep this thing going. You get a bunch of software design intuition because you have to like re-evaluate your assumptions for an incredibly long time. If you can do that, you're probably ready for platform stuff." 𝟯. 𝗚𝗲𝗻𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝘁𝗼𝗼𝗹𝘀 𝗳𝗲𝗲𝗹 𝗹𝗶𝗸𝗲 𝘁𝗵𝗲𝘆 𝗮𝗿𝗲 𝗻𝗼𝘁 “𝘁𝗵𝗲𝗿𝗲” 𝘆𝗲𝘁 𝘄𝗶𝘁𝗵 𝗻𝗮𝘁𝗶𝘃𝗲 𝗺𝗼𝗯𝗶𝗹𝗲. LLMs integrated into IDEs seem to be increasingly helpful with backend, fullstack, web and even cross-platform (React Native / Expo) projects. However, Reddit’s mobile team shared that they get a moderate boost from the Apple and Android Studio LLM additions. Native mobile development is distinctively different from web, fullstack and backend coding – and it seems that these IDEs with AI functionality have not done much to optimize for the expereince of native mobile engineers. Over time, this will likely change – but it’s a reminder that there are differences between fullstack, backend and native mobile development.(I wrote a book reflecting on more of the challenges unique to native mobile titled Building Mobile Apps at Scale)

Gergely Orosz

67,199 görüntüleme • 1 yıl önce

What is it like to be a founding engineer at a startup, and how do you become one? Michelle Lim joined Warp as the founding engineer, and she's now a founder at Flint AI where she is hiring founding engineers. We talk through her journey and tactics helpful for anyone wanting to make an impact at a startup. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. •⁠ Linear ⁠ — ⁠ The system for modern product development. I really liked how Michelle was realistic how, as a founding engineer, you have two jobs at once: #1: Software engineering. Build the stuff you need to do #2: Everything else to help the business succeed, including lots of things that are not to do with software engineering! Do all of these once you did job #1 well. In return, you get to learn a lot on how a business is built - which will help you if and when you become a founder yourself! Thanks for the great convo, Michelle, and keep it up!
0:58

What is it like to be a founding engineer at a startup, and how do you become one? Michelle Lim joined Warp as the founding engineer, and she's now a founder at Flint AI where she is hiring founding engineers. We talk through her journey and tactics helpful for anyone wanting to make an impact at a startup. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. •⁠ Linear ⁠ — ⁠ The system for modern product development. I really liked how Michelle was realistic how, as a founding engineer, you have two jobs at once: #1: Software engineering. Build the stuff you need to do #2: Everything else to help the business succeed, including lots of things that are not to do with software engineering! Do all of these once you did job #1 well. In return, you get to learn a lot on how a business is built - which will help you if and when you become a founder yourself! Thanks for the great convo, Michelle, and keep it up!

Gergely Orosz

17,126 görüntüleme • 6 ay önce

AI is changing the software engineering craft. Anders Hejlsberg (Anders Hejlsberg) - creator of C#, TypeScript and industry legend - on why code review needs to get more enjoyable in response: #1 - AI is shifting the craft from writing code, to reviewing code: "In a sense, we're all turning into project managers. We can have an army of junior programmers, called agents, that will just spit out reams of code but someone's got to have the big picture and review all of that. And so, increasingly, our craft is going from one of writing the code, to one of reviewing the code and building the architecture of the code and overseeing the work. It's a different kind of craft. It's a different kind of enjoyment. I've always liked writing the code. To me that was the fulfilling part, seeing it work. In a way, AI robs a little bit of that, because I am less interested in reviewing code." #2 - The code review experience should be improved: "I think we could also make the process of reviewing code much more interesting than it is today. I mean, today, you see a list of diffs in alphabetical order and now it's up to you to make heads or tails of it. There are more pedagogical ways of presenting that. And you could have commentary generated by the AI that tells you what the changes are and whatever, and then tries to guide you along. So that symbiotic relationship, I think we need to work on that more and to keep the enjoyment in there."
2:04

AI is changing the software engineering craft. Anders Hejlsberg (Anders Hejlsberg) - creator of C#, TypeScript and industry legend - on why code review needs to get more enjoyable in response: #1 - AI is shifting the craft from writing code, to reviewing code: "In a sense, we're all turning into project managers. We can have an army of junior programmers, called agents, that will just spit out reams of code but someone's got to have the big picture and review all of that. And so, increasingly, our craft is going from one of writing the code, to one of reviewing the code and building the architecture of the code and overseeing the work. It's a different kind of craft. It's a different kind of enjoyment. I've always liked writing the code. To me that was the fulfilling part, seeing it work. In a way, AI robs a little bit of that, because I am less interested in reviewing code." #2 - The code review experience should be improved: "I think we could also make the process of reviewing code much more interesting than it is today. I mean, today, you see a list of diffs in alphabetical order and now it's up to you to make heads or tails of it. There are more pedagogical ways of presenting that. And you could have commentary generated by the AI that tells you what the changes are and whatever, and then tries to guide you along. So that symbiotic relationship, I think we need to work on that more and to keep the enjoyment in there."

The Pragmatic Engineer

38,880 görüntüleme • 28 gün önce

Will tools like Windsurf result in fewer software engineers? "It feels like it's people hating software engineers who say this" says Windsurf cofounder and CEO Varun Mohan In today's podcast episode, we go into the engineering challenges (and tradeoffs!) of building an AI-powered IDE like Windsurf and how Windsurf has changed how the Windsurf dev team (and non-developers!) write software. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • CodeRabbit — Cut code review time and bugs in half. Use the code PRAGMATIC to get one month free at • Modal — The cloud platform for building AI applications Get started at Three of my takeaways: 𝟭. 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗜𝗗𝗘𝘀 𝗺𝗮𝗸𝗲 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗺𝗼𝗿𝗲 “𝗳𝗲𝗮𝗿𝗹𝗲𝘀𝘀” 𝗮𝗻𝗱 𝗰𝗼𝘂𝗹𝗱 𝗿𝗲𝗱𝘂𝗰𝗲 𝗺𝗲𝗻𝘁𝗮𝗹 𝗹𝗼𝗮𝗱. I asked Varun how using Windsurf changed the workload and output of engineers — especially given how most of the team have been software engineers well before LLM coding assistants were a thing. A few of Varun’s observations: • Engineers are more “fearless” in jumping into unfamiliar parts of the codebase — when, in the past, they would have waited to talk to people more familar with the code. • Devs increasingly first turn to AI for help, before pinging someone else (and thus interrupting that person) • Mental fatigue is down, thanks to tedious tasks can be handed off to prompts or AI agents Varun stressed that he doesn’t see tools like Windsurf eliminating the need for skilled engineers: it simply changes the nature of the work, and can increase potential output. 𝟮. 𝗙𝗼𝗿𝗸𝗶𝗻𝗴 𝗩𝗦 𝗖𝗼𝗱𝗲 𝘁𝗵𝗲 “𝗿𝗶𝗴𝗵𝘁” 𝘄𝗮𝘆 𝗺𝗲𝗮𝗻𝘀 𝗱𝗼𝗶𝗻𝗴 𝗮 𝗹𝗼𝘁 𝗼𝗳 𝗶𝗻𝘃𝗶𝘀𝗶𝗯𝗹𝗲 𝘄𝗼𝗿𝗸. While VS Code is open source and can be forked: VS Code Marketplace and lots of proprietary extensions. For example, when forking VS Code, the fork is not allowed to use extensions like Python language servers, remote SSH, and dev containers. The Windsurf team had to build custom extensions from scratch — which took a bunch of time, and users probably did not even notice the difference! However, if Windsurf had not done this, and had broken the license of these extensions, they could have found themselves in legal hot water. So forking VS Code “properly” is not as simple as most devs would normally expect. 𝟯. 𝗖𝗼𝘂𝗹𝗱 𝘄𝗲 𝘀𝗲𝗲 𝗺𝗼𝗿𝗲 𝗻𝗼𝗻-𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗰𝗿𝗲𝗮𝘁𝗲 “𝘄𝗼𝗿𝗸 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲?” 𝗠𝗮𝘆𝗯𝗲. One of the very surprising stories was how Windsurf’s partnership lead (a non-developer) created a quoting tool by prompting Windsurf. This tool replaced a bespoke, stateless tool that the company paid for. Varun and I agreed that a complex SaaS that has lots of state and other features is not really a target to be “replaced internally.” However, simple pieces of software can now be “prompted” by business users. I have my doubts about how maintainable these will be in the long run: just thinking about how even Big Tech struggles with internal tools built by a single dev, and then when this dev leaves, no one wants to take it over.
0:36

Will tools like Windsurf result in fewer software engineers? "It feels like it's people hating software engineers who say this" says Windsurf cofounder and CEO Varun Mohan In today's podcast episode, we go into the engineering challenges (and tradeoffs!) of building an AI-powered IDE like Windsurf and how Windsurf has changed how the Windsurf dev team (and non-developers!) write software. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • CodeRabbit — Cut code review time and bugs in half. Use the code PRAGMATIC to get one month free at • Modal — The cloud platform for building AI applications Get started at Three of my takeaways: 𝟭. 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗜𝗗𝗘𝘀 𝗺𝗮𝗸𝗲 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗺𝗼𝗿𝗲 “𝗳𝗲𝗮𝗿𝗹𝗲𝘀𝘀” 𝗮𝗻𝗱 𝗰𝗼𝘂𝗹𝗱 𝗿𝗲𝗱𝘂𝗰𝗲 𝗺𝗲𝗻𝘁𝗮𝗹 𝗹𝗼𝗮𝗱. I asked Varun how using Windsurf changed the workload and output of engineers — especially given how most of the team have been software engineers well before LLM coding assistants were a thing. A few of Varun’s observations: • Engineers are more “fearless” in jumping into unfamiliar parts of the codebase — when, in the past, they would have waited to talk to people more familar with the code. • Devs increasingly first turn to AI for help, before pinging someone else (and thus interrupting that person) • Mental fatigue is down, thanks to tedious tasks can be handed off to prompts or AI agents Varun stressed that he doesn’t see tools like Windsurf eliminating the need for skilled engineers: it simply changes the nature of the work, and can increase potential output. 𝟮. 𝗙𝗼𝗿𝗸𝗶𝗻𝗴 𝗩𝗦 𝗖𝗼𝗱𝗲 𝘁𝗵𝗲 “𝗿𝗶𝗴𝗵𝘁” 𝘄𝗮𝘆 𝗺𝗲𝗮𝗻𝘀 𝗱𝗼𝗶𝗻𝗴 𝗮 𝗹𝗼𝘁 𝗼𝗳 𝗶𝗻𝘃𝗶𝘀𝗶𝗯𝗹𝗲 𝘄𝗼𝗿𝗸. While VS Code is open source and can be forked: VS Code Marketplace and lots of proprietary extensions. For example, when forking VS Code, the fork is not allowed to use extensions like Python language servers, remote SSH, and dev containers. The Windsurf team had to build custom extensions from scratch — which took a bunch of time, and users probably did not even notice the difference! However, if Windsurf had not done this, and had broken the license of these extensions, they could have found themselves in legal hot water. So forking VS Code “properly” is not as simple as most devs would normally expect. 𝟯. 𝗖𝗼𝘂𝗹𝗱 𝘄𝗲 𝘀𝗲𝗲 𝗺𝗼𝗿𝗲 𝗻𝗼𝗻-𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗰𝗿𝗲𝗮𝘁𝗲 “𝘄𝗼𝗿𝗸 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲?” 𝗠𝗮𝘆𝗯𝗲. One of the very surprising stories was how Windsurf’s partnership lead (a non-developer) created a quoting tool by prompting Windsurf. This tool replaced a bespoke, stateless tool that the company paid for. Varun and I agreed that a complex SaaS that has lots of state and other features is not really a target to be “replaced internally.” However, simple pieces of software can now be “prompted” by business users. I have my doubts about how maintainable these will be in the long run: just thinking about how even Big Tech struggles with internal tools built by a single dev, and then when this dev leaves, no one wants to take it over.

Gergely Orosz

34,355 görüntüleme • 1 yıl önce

Kubernetes is the second-largest open-source project in the world. What does it do—and why is it so widely adopted? Kat Cosgrove has led several Kubernetes releases and joined The Pragmatic Engineer podcast to share the history of Kubernetes, how it's built, when it is a good (or not so good) use case, and how you can contribute to it (and why it's a good thing to do for professional and career growth). Brought to you by •⁠ WorkOS — The modern identity platform for B2B SaaS •⁠ Modal — The cloud platform for building AI applications •⁠ Cortex — Your Portal to Engineering Excellence Watch or listen: • YouTube: • Spotify: • Apple: • Summary and transcript: Three of my takeaways from this great conversation: 𝟭. 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗵𝗲𝗹𝗽𝘀 𝘄𝗶𝘁𝗵 𝗺𝗮𝗻𝗮𝗴𝗶𝗻𝗴 𝗹𝗮𝗿𝗴𝗲-𝘀𝗰𝗮𝗹𝗲 𝗯𝗮𝗰𝗸𝗲𝗻𝗱 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀. Google originally built an in-house tool to manage the tens of thousands (then hundreds of thousands and later millions) of machines: this internal tool is called Borg. The roots of Kubernetes come from Borg: but Google has since donated the project to the Cloud Native Computing Foundation (CNCF) – and today, Kubernetes is the second largest open source project, after Linux. We previously did a deepdive on How Linux is built, and touched on Google’s SRE roots in What is Reliability Engineering? 𝟮. 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗶𝘀 𝗮 𝘃𝗲𝗿𝘆 𝘄𝗲𝗹𝗹-𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗮𝗻𝗱 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲𝗱 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 𝗽𝗿𝗼𝗷𝗲𝗰𝘁. The structure of the project and all processes are well documented. The project has around 150-200 maintainers, has a few dozen SIGs (Special Interest Groups) and releases run on a 14-16 week cycle. 𝟯. 𝗧𝗵𝗲 “𝗹𝗲𝗮𝗱” 𝗮𝗻𝗱 “𝘀𝗵𝗮𝗱𝗼𝘄” 𝗰𝗼𝗻𝗰𝗲𝗽𝘁 𝗶𝘀 𝗮 𝗰𝗹𝗲𝘃𝗲𝗿 𝗼𝗻𝗲, 𝘂𝘁𝗶𝗹𝗶𝘇𝗲𝗱 𝗯𝘆 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀. The Release Team within Kubernetes owns releases, and the Release Team has about 20-30 people participating in each release. More than of the members on the Release Team are “shadows” who get to learn on the job how a release is done – and, hopefully, in a release or two, become leads themselves!
0:55

Kubernetes is the second-largest open-source project in the world. What does it do—and why is it so widely adopted? Kat Cosgrove has led several Kubernetes releases and joined The Pragmatic Engineer podcast to share the history of Kubernetes, how it's built, when it is a good (or not so good) use case, and how you can contribute to it (and why it's a good thing to do for professional and career growth). Brought to you by •⁠ WorkOS — The modern identity platform for B2B SaaS •⁠ Modal — The cloud platform for building AI applications •⁠ Cortex — Your Portal to Engineering Excellence Watch or listen: • YouTube: • Spotify: • Apple: • Summary and transcript: Three of my takeaways from this great conversation: 𝟭. 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗵𝗲𝗹𝗽𝘀 𝘄𝗶𝘁𝗵 𝗺𝗮𝗻𝗮𝗴𝗶𝗻𝗴 𝗹𝗮𝗿𝗴𝗲-𝘀𝗰𝗮𝗹𝗲 𝗯𝗮𝗰𝗸𝗲𝗻𝗱 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀. Google originally built an in-house tool to manage the tens of thousands (then hundreds of thousands and later millions) of machines: this internal tool is called Borg. The roots of Kubernetes come from Borg: but Google has since donated the project to the Cloud Native Computing Foundation (CNCF) – and today, Kubernetes is the second largest open source project, after Linux. We previously did a deepdive on How Linux is built, and touched on Google’s SRE roots in What is Reliability Engineering? 𝟮. 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗶𝘀 𝗮 𝘃𝗲𝗿𝘆 𝘄𝗲𝗹𝗹-𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗮𝗻𝗱 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲𝗱 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 𝗽𝗿𝗼𝗷𝗲𝗰𝘁. The structure of the project and all processes are well documented. The project has around 150-200 maintainers, has a few dozen SIGs (Special Interest Groups) and releases run on a 14-16 week cycle. 𝟯. 𝗧𝗵𝗲 “𝗹𝗲𝗮𝗱” 𝗮𝗻𝗱 “𝘀𝗵𝗮𝗱𝗼𝘄” 𝗰𝗼𝗻𝗰𝗲𝗽𝘁 𝗶𝘀 𝗮 𝗰𝗹𝗲𝘃𝗲𝗿 𝗼𝗻𝗲, 𝘂𝘁𝗶𝗹𝗶𝘇𝗲𝗱 𝗯𝘆 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀. The Release Team within Kubernetes owns releases, and the Release Team has about 20-30 people participating in each release. More than of the members on the Release Team are “shadows” who get to learn on the job how a release is done – and, hopefully, in a release or two, become leads themselves!

Gergely Orosz

22,268 görüntüleme • 1 yıl önce

Great to have Graphite as a sponsor of the podcast: Graphite is the developer productivity platform that brings stacked pull requests (the workflow best-in-class companies like Meta, Google & Uber already use) to every software company at GitHub. It's awesome:
0:59

Great to have Graphite as a sponsor of the podcast: Graphite is the developer productivity platform that brings stacked pull requests (the workflow best-in-class companies like Meta, Google & Uber already use) to every software company at GitHub. It's awesome:

Gergely Orosz

20,919 görüntüleme • 1 yıl önce

One of the most tedious (but critical tasks) for software development teams is updating foundational software. It’s not new feature work, and it doesn’t feel like you’re moving the experience forward. As a result, this work is either dreaded or put off for more exciting work—or both. Amazon Q, our GenAI assistant for software development, is trying to bring some light to this heaviness. We have a new code transformation capability, and here’s what we found when we integrated it into our internal systems and applied it to our needed Java upgrades: - The average time to upgrade an application to Java 17 plummeted from what’s typically 50 developer-days to just a few hours. We estimate this has saved us the equivalent of 4,500 developer-years of work (yes, that number is crazy but, real). - In under six months, we've been able to upgrade more than 50% of our production Java systems to modernized Java versions at a fraction of the usual time and effort. And, our developers shipped 79% of the auto-generated code reviews without any additional changes. - The benefits go beyond how much effort we’ve saved developers. The upgrades have enhanced security and reduced infrastructure costs, providing an estimated $260M in annualized efficiency gains. This is a great example of how large-scale enterprises can gain significant efficiencies in foundational software hygiene work by leveraging Amazon Q. It’s been a game changer for us, and not only do our Amazon teams plan to use this transformation capability more, but our Q team plans to add more transformations for developers to leverage.
0:42

One of the most tedious (but critical tasks) for software development teams is updating foundational software. It’s not new feature work, and it doesn’t feel like you’re moving the experience forward. As a result, this work is either dreaded or put off for more exciting work—or both. Amazon Q, our GenAI assistant for software development, is trying to bring some light to this heaviness. We have a new code transformation capability, and here’s what we found when we integrated it into our internal systems and applied it to our needed Java upgrades: - The average time to upgrade an application to Java 17 plummeted from what’s typically 50 developer-days to just a few hours. We estimate this has saved us the equivalent of 4,500 developer-years of work (yes, that number is crazy but, real). - In under six months, we've been able to upgrade more than 50% of our production Java systems to modernized Java versions at a fraction of the usual time and effort. And, our developers shipped 79% of the auto-generated code reviews without any additional changes. - The benefits go beyond how much effort we’ve saved developers. The upgrades have enhanced security and reduced infrastructure costs, providing an estimated $260M in annualized efficiency gains. This is a great example of how large-scale enterprises can gain significant efficiencies in foundational software hygiene work by leveraging Amazon Q. It’s been a game changer for us, and not only do our Amazon teams plan to use this transformation capability more, but our Q team plans to add more transformations for developers to leverage.

Andy Jassy

998,416 görüntüleme • 1 yıl önce

Excited to share that I’ve joined Anomaly as founding designer. I’m thrilled to work with Jay dax Frank Wang and Adam — a team stacked with talent! I’ve always been fascinated by challenges that influence the way people work. Today, AI is reshaping software development at a pace we’ve never seen. From solo developers to global enterprises, the way we write code has shifted dramatically in the past year, and will continue to change in the years ahead. This is an opportunity for me to help shape these experiences for everyone, regardless of frameworks, IDEs, or tools. I want to explore how they’re adopted and how they can have the greatest impact. The team is hard at work on OpenCode — the open source AI coding agent for the terminal. With over 23K stars on GitHub, it’s already changing how thousands of developers write code every day. Follow OpenCode as we go beyond the terminal and design and build world-class AI developer experiences ✌️
0:25

Excited to share that I’ve joined Anomaly as founding designer. I’m thrilled to work with Jay dax Frank Wang and Adam — a team stacked with talent! I’ve always been fascinated by challenges that influence the way people work. Today, AI is reshaping software development at a pace we’ve never seen. From solo developers to global enterprises, the way we write code has shifted dramatically in the past year, and will continue to change in the years ahead. This is an opportunity for me to help shape these experiences for everyone, regardless of frameworks, IDEs, or tools. I want to explore how they’re adopted and how they can have the greatest impact. The team is hard at work on OpenCode — the open source AI coding agent for the terminal. With over 23K stars on GitHub, it’s already changing how thousands of developers write code every day. Follow OpenCode as we go beyond the terminal and design and build world-class AI developer experiences ✌️

David Hill

158,196 görüntüleme • 9 ay önce

A new way of working. And a scary one at that. Memory Store is one of a group of new kinds of AI-first companies that can turn you into a Fast Company. I’m using several of them on my desktop and they are a dramatically new way to work. It builds a memory for: 1. Your AI agents. 2. Any employee using it. 3. The company itself. I sit down with founder Diwank Singh Tomer, Diwank Singh Tomer, who both freaks me out as well as shows how AI can radically help workers as well as managers. First, why does it freak me out? Well, his AI watches nearly everything a worker does and keeps a “memory” of it. It watches your email. Your calendar. Your Slack. And a whole lot of other things. This can really freak out workers if “forced” on them. And leads to a whole new set of security issues companies need to consider before adopting these things. Such data about a company could give a competitor a HUGE advantage, if leaked. They would know how a company “thinks.” It really is a surveillance system for employees and the company itself. OK, now why would anyone ever use such a thing? Because it gives employees super powers. It makes them more productive. Shows workers a lot of things about themselves, and helps them work and stay on task. It also gives the company super powers. Institutional memory stays with the AI now, even if an employee dies or leaves. As companies move to “AI First” approaches, they will increasingly see the value in companies like Memory Store. It prepares employees for meetings. It helps them remember things. It shows them what they should be working on, and helps them do it. Memory Store builds a memory for: 1. Your agents. 2. Your company. 3. Yourself, or any employee on it. This helps all three work better together. Diwank Singh Tomer and I go in depth about what it does and how deeply it improves working at a company that deploys it. But to get the ultimate benefits you gotta convince your coworkers to use it. And your managers to approve it. Which means you have to get over your fears and get everyone you work with over theirs too. Which will be the challenge for Diwank. Luckily for him his first customers are raving about how good it is and how much his platform helped their companies. Increases sales. Makes teams more productive. Decreases errors and unnecessary costs. Which tells me everyone soon will be using systems like this. This is what the new way of working looks like. Once I got over my fears it sure is an amazing way to work. Will you try working this way?
52:08

A new way of working. And a scary one at that. Memory Store is one of a group of new kinds of AI-first companies that can turn you into a Fast Company. I’m using several of them on my desktop and they are a dramatically new way to work. It builds a memory for: 1. Your AI agents. 2. Any employee using it. 3. The company itself. I sit down with founder Diwank Singh Tomer, Diwank Singh Tomer, who both freaks me out as well as shows how AI can radically help workers as well as managers. First, why does it freak me out? Well, his AI watches nearly everything a worker does and keeps a “memory” of it. It watches your email. Your calendar. Your Slack. And a whole lot of other things. This can really freak out workers if “forced” on them. And leads to a whole new set of security issues companies need to consider before adopting these things. Such data about a company could give a competitor a HUGE advantage, if leaked. They would know how a company “thinks.” It really is a surveillance system for employees and the company itself. OK, now why would anyone ever use such a thing? Because it gives employees super powers. It makes them more productive. Shows workers a lot of things about themselves, and helps them work and stay on task. It also gives the company super powers. Institutional memory stays with the AI now, even if an employee dies or leaves. As companies move to “AI First” approaches, they will increasingly see the value in companies like Memory Store. It prepares employees for meetings. It helps them remember things. It shows them what they should be working on, and helps them do it. Memory Store builds a memory for: 1. Your agents. 2. Your company. 3. Yourself, or any employee on it. This helps all three work better together. Diwank Singh Tomer and I go in depth about what it does and how deeply it improves working at a company that deploys it. But to get the ultimate benefits you gotta convince your coworkers to use it. And your managers to approve it. Which means you have to get over your fears and get everyone you work with over theirs too. Which will be the challenge for Diwank. Luckily for him his first customers are raving about how good it is and how much his platform helped their companies. Increases sales. Makes teams more productive. Decreases errors and unnecessary costs. Which tells me everyone soon will be using systems like this. This is what the new way of working looks like. Once I got over my fears it sure is an amazing way to work. Will you try working this way?

Robert Scoble

24,964 görüntüleme • 1 ay önce

How to use GitHub Actions to build a pipeline that tests your code, trains a model, and publishes a new version of it. Bonus: I let GitHub Workspace Copilot do a lot of the work. (This is the best "AI developer" I've tested so far by a mile.) Here is the full video:
18:00

How to use GitHub Actions to build a pipeline that tests your code, trains a model, and publishes a new version of it. Bonus: I let GitHub Workspace Copilot do a lot of the work. (This is the best "AI developer" I've tested so far by a mile.) Here is the full video:

Santiago

147,981 görüntüleme • 1 yıl önce

Julie of KISS OF LIFE apologizes for the group’s racially insensitive birthday livestream on Instagram Live: “It’s nerve-wracking to talk about everything that is going on, but because we are a bit of a more mature group, it’s very important for us to take accountability for our actions, whether it is good or bad. We do realize that what we did was wrong and we spent a lot of time together on how to learn from this and move forward, trying to educate ourselves more so that something like this doesn’t happen again. I want to take this opportunity to apologize to the Black and Latino community. We do understand that we hurt and disappointed a lot of our friends. What we can promise is that we’re working hard to be better and show everyone our passion for music, in whatever genre it is.”
2:11

Julie of KISS OF LIFE apologizes for the group’s racially insensitive birthday livestream on Instagram Live: “It’s nerve-wracking to talk about everything that is going on, but because we are a bit of a more mature group, it’s very important for us to take accountability for our actions, whether it is good or bad. We do realize that what we did was wrong and we spent a lot of time together on how to learn from this and move forward, trying to educate ourselves more so that something like this doesn’t happen again. I want to take this opportunity to apologize to the Black and Latino community. We do understand that we hurt and disappointed a lot of our friends. What we can promise is that we’re working hard to be better and show everyone our passion for music, in whatever genre it is.”

Pop Base

5,898,467 görüntüleme • 1 yıl önce

More moves to AI-first living. Got the Genspark browser that just came out. One thing I notice is that I like having separate browsers working on different tasks. I'm not a big user of MCPs, since I'm not really a developer. Are you? They have a store of a bunch of MCPs available to use. Most of my AI work is research related, or answering emails and scheduling things, I'm focusing more of my effort there. Genspark has been shipping a ton of stuff the past few weeks, from ability to make slides to a new AI secretary that can schedule things, or help you answer your emails. First I looked at, "does it make sense to move over to this new way of working?" The problem with that is you gotta learn a new browser. Well, it looks like Google Chrome, except it has a prompt window. Click the icons underneath it and you will see you can add X, Notion, Google stuff like calendar and gmail, or a variety of others. But the real power is just talking to it. I asked it what kinds of tasks it can do, and it answered: "Just tell me what you want to accomplish! For example: "Research the latest developments in spatial computing and create a presentation" "Analyze my Gmail for any important emails from this week" "Find information about AI robotics companies and create a spreadsheet" "Generate a video about emerging tech trends" "Help me plan a trip to CES 2026" And so further into AI-first living I go. Have you tried it yet? What do you suggest I do next to use more AI to run my life and build my business? I have another browser tab building a video for me. What a beautiful time to be alive. Download it at:
1:09

More moves to AI-first living. Got the Genspark browser that just came out. One thing I notice is that I like having separate browsers working on different tasks. I'm not a big user of MCPs, since I'm not really a developer. Are you? They have a store of a bunch of MCPs available to use. Most of my AI work is research related, or answering emails and scheduling things, I'm focusing more of my effort there. Genspark has been shipping a ton of stuff the past few weeks, from ability to make slides to a new AI secretary that can schedule things, or help you answer your emails. First I looked at, "does it make sense to move over to this new way of working?" The problem with that is you gotta learn a new browser. Well, it looks like Google Chrome, except it has a prompt window. Click the icons underneath it and you will see you can add X, Notion, Google stuff like calendar and gmail, or a variety of others. But the real power is just talking to it. I asked it what kinds of tasks it can do, and it answered: "Just tell me what you want to accomplish! For example: "Research the latest developments in spatial computing and create a presentation" "Analyze my Gmail for any important emails from this week" "Find information about AI robotics companies and create a spreadsheet" "Generate a video about emerging tech trends" "Help me plan a trip to CES 2026" And so further into AI-first living I go. Have you tried it yet? What do you suggest I do next to use more AI to run my life and build my business? I have another browser tab building a video for me. What a beautiful time to be alive. Download it at:

Robert Scoble

84,349 görüntüleme • 1 yıl önce

Linear CEO Karri Saarinen says some companies are using "friction forms" to help engineers break through bureaucracy and get new AI tools approved faster: "There are a lot of companies where employees ask, 'Can I use agents?' and they say, 'No, you can’t.' And they don’t really have a reason for it, or they say, 'We have to evaluate it,' and that evaluation takes months." "This has to change. The industry is moving so fast, so you cannot have month-long, multi-month processes to evaluate every single new tool. I think the security standpoint is valid, but you have to figure out a new way to think about security and not just block new tools." "One hack I’ve seen at some companies is that they have this friction form. So engineers who feel friction and want to use new tools or AI file a friction form, and that escalates it to higher leadership. Then it makes an SLA that has to be resolved in a week or 10 days." "And so you force the hand of procurement, IT, and security people to do something about it. Because the incentive a lot of times in these jobs is that you don’t want to rock the boat, so you don’t want to change things if you don’t have to."
1:35

Linear CEO Karri Saarinen says some companies are using "friction forms" to help engineers break through bureaucracy and get new AI tools approved faster: "There are a lot of companies where employees ask, 'Can I use agents?' and they say, 'No, you can’t.' And they don’t really have a reason for it, or they say, 'We have to evaluate it,' and that evaluation takes months." "This has to change. The industry is moving so fast, so you cannot have month-long, multi-month processes to evaluate every single new tool. I think the security standpoint is valid, but you have to figure out a new way to think about security and not just block new tools." "One hack I’ve seen at some companies is that they have this friction form. So engineers who feel friction and want to use new tools or AI file a friction form, and that escalates it to higher leadership. Then it makes an SLA that has to be resolved in a week or 10 days." "And so you force the hand of procurement, IT, and security people to do something about it. Because the incentive a lot of times in these jobs is that you don’t want to rock the boat, so you don’t want to change things if you don’t have to."

TBPN

15,799 görüntüleme • 2 ay önce

What do you do for a living today? AI and intelligent robots will increasingly take over many tasks from humans. And they will do it better, faster and cheaper. Yes, yours too. Many people will work much less or not at all in normal jobs. And earn less or even nothing. What will you live on then? And how will our companies survive when their customers don't have the money to buy their products and services? This is the key question for your financial future! We will take a look at three scenarios for the future of our life and the economy. If AI and robots work for us on a large scale, our future could be great. However, it could also turn out quite differently. We could also wake up in a horror scenario. Because we have a huge and catastrophic flaw in our economic system that could lead to disaster in a world of AI and robotics. Correcting this mistake is the biggest challenge. What the flaw is and how we can fix it, you'll learn in this video.
25:39

What do you do for a living today? AI and intelligent robots will increasingly take over many tasks from humans. And they will do it better, faster and cheaper. Yes, yours too. Many people will work much less or not at all in normal jobs. And earn less or even nothing. What will you live on then? And how will our companies survive when their customers don't have the money to buy their products and services? This is the key question for your financial future! We will take a look at three scenarios for the future of our life and the economy. If AI and robots work for us on a large scale, our future could be great. However, it could also turn out quite differently. We could also wake up in a horror scenario. Because we have a huge and catastrophic flaw in our economic system that could lead to disaster in a world of AI and robotics. Correcting this mistake is the biggest challenge. What the flaw is and how we can fix it, you'll learn in this video.

Dr Pero Micic

12,010,084 görüntüleme • 1 yıl önce

Steve Jobs on how he learned to run a company: Question: "You're 21. You're a big success. You know, you've just sort of done it by the seat of your pants. You don't have any particular training in this. How do you learn to run a company?" Steve Jobs: "You know, throughout the years in business, I found something, which was that I always ask why you do things. And the answers you invariably get are, oh, that's just the way it's done. Nobody knows why they do what they do. Nobody thinks about things very deeply in business. That's what I found. I'll give you an example. When we were building our Apple I's in the garage, we knew exactly what they cost. When we got into a factory in the Apple II days, the accounting had this notion of a standard cost, where you'd kind of set a standard cost and at the end of a quarter you'd adjust it with a variance. And I kept asking, well, why do we do this? And the answer was, well, that's just the way it's done. And after about six months of digging into this, what I realized was the reason you do it is because you don't really have good enough controls to know how much it costs. So you guess, and then you fix your guess at the end of the quarter. And the reason you don't know how much it costs is because your information systems aren't good enough. But nobody said it that way. And so later on, when we designed this automated factory for Macintosh, we were able to get rid of a lot of these antiquated concepts and know exactly what something cost to the second. So in business, a lot of things are, I call it folklore. They're done because they were done yesterday and the day before. And so what that means is if you're willing to sort of ask a lot of questions and think about things and work really hard, you can learn business pretty fast. It's not the hardest thing in the world. It's not rocket science. It's not rocket science."
2:06

Steve Jobs on how he learned to run a company: Question: "You're 21. You're a big success. You know, you've just sort of done it by the seat of your pants. You don't have any particular training in this. How do you learn to run a company?" Steve Jobs: "You know, throughout the years in business, I found something, which was that I always ask why you do things. And the answers you invariably get are, oh, that's just the way it's done. Nobody knows why they do what they do. Nobody thinks about things very deeply in business. That's what I found. I'll give you an example. When we were building our Apple I's in the garage, we knew exactly what they cost. When we got into a factory in the Apple II days, the accounting had this notion of a standard cost, where you'd kind of set a standard cost and at the end of a quarter you'd adjust it with a variance. And I kept asking, well, why do we do this? And the answer was, well, that's just the way it's done. And after about six months of digging into this, what I realized was the reason you do it is because you don't really have good enough controls to know how much it costs. So you guess, and then you fix your guess at the end of the quarter. And the reason you don't know how much it costs is because your information systems aren't good enough. But nobody said it that way. And so later on, when we designed this automated factory for Macintosh, we were able to get rid of a lot of these antiquated concepts and know exactly what something cost to the second. So in business, a lot of things are, I call it folklore. They're done because they were done yesterday and the day before. And so what that means is if you're willing to sort of ask a lot of questions and think about things and work really hard, you can learn business pretty fast. It's not the hardest thing in the world. It's not rocket science. It's not rocket science."

Founder Mode

32,217 görüntüleme • 4 ay önce

Satoshi Roundtable is later this week. Tech Talk Tuesdays in Dubai asked me about the upcoming event: “My hope is that have for this week is that we embrace what this industry is all about. It’s not about Blackrock, or CBDCs or the filthy broken fiat system - it’s about an alternative to that. A lot of people can point to many broken things in our world. And the root of what is broken is because of the broken money system. The money system is broken. There is death and destruction because of a broken money system and what this technology represents is something different than that. It’s an alternate to that. And that’s what makes it unique and that’s what makes it valuable.”
1:09

Satoshi Roundtable is later this week. Tech Talk Tuesdays in Dubai asked me about the upcoming event: “My hope is that have for this week is that we embrace what this industry is all about. It’s not about Blackrock, or CBDCs or the filthy broken fiat system - it’s about an alternative to that. A lot of people can point to many broken things in our world. And the root of what is broken is because of the broken money system. The money system is broken. There is death and destruction because of a broken money system and what this technology represents is something different than that. It’s an alternate to that. And that’s what makes it unique and that’s what makes it valuable.”

Bruce Fenton

11,176 görüntüleme • 4 ay önce