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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...

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Gergely Orosz

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79,836 次观看 • 1 年前 •via X (Twitter)

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No project has gotten more traction in such a short time than by Peter Steinberger 🦞 But how is he building it? Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Statsig — ⁠The unified platform for flags, analytics, experiments, and more. Join us at The Pragmatic Summit I’m hosting with Statsig, on 11 February: • Sonar – The makers of SonarQube, the industry standard for automated code review. Join me online at the Sonar Summit, on 3rd March: • WorkOS – Everything you need to make your app enterprise ready. If you're in SF on 9 February, stop by at the WorkOS AI Night with The Pragmatic Engineer (free to register):
1:08

No project has gotten more traction in such a short time than by Peter Steinberger 🦞 But how is he building it? Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Statsig — ⁠The unified platform for flags, analytics, experiments, and more. Join us at The Pragmatic Summit I’m hosting with Statsig, on 11 February: • Sonar – The makers of SonarQube, the industry standard for automated code review. Join me online at the Sonar Summit, on 3rd March: • WorkOS – Everything you need to make your app enterprise ready. If you're in SF on 9 February, stop by at the WorkOS AI Night with The Pragmatic Engineer (free to register):

Gergely Orosz

225,804 次观看 • 5 个月前

How is AI changing software development? Martin Fowler (Martin Fowler) says AI is the biggest shift in the field since high-level languages appeared (ones like Fortran or C, offering a new abstaction level to code at, versus Assembly). We also talked about where GenAI works well, thoughts on refactoring, software architecture and more. I very much recommend checking out the whole episode: • YouTube: • Spotify: • Apple: Brought to you by: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. Check it out: •⁠ Linear ⁠ — ⁠ The system for modern product development. Read how Linear does Quality Wednesdays – it’s fascinating:
1:35

How is AI changing software development? Martin Fowler (Martin Fowler) says AI is the biggest shift in the field since high-level languages appeared (ones like Fortran or C, offering a new abstaction level to code at, versus Assembly). We also talked about where GenAI works well, thoughts on refactoring, software architecture and more. I very much recommend checking out the whole episode: • YouTube: • Spotify: • Apple: Brought to you by: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. Check it out: •⁠ Linear ⁠ — ⁠ The system for modern product development. Read how Linear does Quality Wednesdays – it’s fascinating:

Gergely Orosz

38,889 次观看 • 7 个月前

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!
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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 次观看 • 7 个月前

Why does "vibe coding" not lead to anything productive, for the most part? A great person to answer is Addy Osmani: he has been working on Chrome for 10+ years, and has just published his new book: Beyond Vibe Coding. 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.
0:47

Why does "vibe coding" not lead to anything productive, for the most part? A great person to answer is Addy Osmani: he has been working on Chrome for 10+ years, and has just published his new book: Beyond Vibe Coding. 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.

Gergely Orosz

51,789 次观看 • 8 个月前

. Kent Beck 🌻 is a legend in software engineering: and after coding for 52 years, he's never had more fun than now, he told me. Why? Because AI agents brought back the joy of creating software without the stuff that he's started to hate about coding for so long. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Sonar — Code quality and code security for ALL code •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more • Augment Code — AI coding assistant that pro engineering teams love Two of my takeaways from this chat with Kent: 𝟭. 𝗞𝗲𝗻𝘁 𝗶𝘀 𝗿𝗲-𝗲𝗻𝗲𝗿𝗴𝗶𝘇𝗲𝗱 𝘁𝗵𝗮𝗻𝗸𝘀 𝘁𝗼 𝘂𝘀𝗶𝗻𝗴 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝘀𝘁𝘂𝗳𝗳. Kent has been coding for 52 years, and the last decade, he’s gotten a lot more tired of all of it: learning yet another new language or framework, or debugging the issues when using the latest framework. What he loves about these AI agents (and AI coding tools) is how he doesn’t need to know exactly all the details: he can now be a lot more ambitious in his projects. Currently, Kent is building a server in Smalltalk (that he’s been wanting to do for many years) and a Language Server Protocol (LSP) for Smalltalk 𝟮. 𝗙𝗮𝗰𝗲𝗯𝗼𝗼𝗸 𝘄𝗿𝗼𝘁𝗲 𝗻𝗼 𝘂𝗻𝗶𝘁 𝘁𝗲𝘀𝘁𝘀 𝗶𝗻 𝟮𝟬𝟭𝟭, 𝗮𝗻𝗱 𝘁𝗵𝗶𝘀 𝘀𝘁𝘂𝗻𝗻𝗲𝗱 𝗞𝗲𝗻𝘁, 𝗯𝗮𝗰𝗸 𝗶𝗻 𝘁𝗵𝗲 𝗱𝗮𝘆. Kent joined Facebook in 2011, and was taken aback by the lack of testing and how everyone pushed code to production without automated testing. What he came to realize – and appreciate! – was how Facebook had several things balancing this out: • Devs took responsibility for their code very seriously • Nothing at Facebook was “someone else’s problem:” devs would fix bugs when they saw them, regardless of whose commit caused it • Feature flags were heavily used for risky code • Facebook did staged rollouts to smaller markets like New Zealand To this date, Facebook ships code to production in a unique way. We covered more in the deepdive Shipping to Production at
1:00

. Kent Beck 🌻 is a legend in software engineering: and after coding for 52 years, he's never had more fun than now, he told me. Why? Because AI agents brought back the joy of creating software without the stuff that he's started to hate about coding for so long. Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Sonar — Code quality and code security for ALL code •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more • Augment Code — AI coding assistant that pro engineering teams love Two of my takeaways from this chat with Kent: 𝟭. 𝗞𝗲𝗻𝘁 𝗶𝘀 𝗿𝗲-𝗲𝗻𝗲𝗿𝗴𝗶𝘇𝗲𝗱 𝘁𝗵𝗮𝗻𝗸𝘀 𝘁𝗼 𝘂𝘀𝗶𝗻𝗴 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝘀𝘁𝘂𝗳𝗳. Kent has been coding for 52 years, and the last decade, he’s gotten a lot more tired of all of it: learning yet another new language or framework, or debugging the issues when using the latest framework. What he loves about these AI agents (and AI coding tools) is how he doesn’t need to know exactly all the details: he can now be a lot more ambitious in his projects. Currently, Kent is building a server in Smalltalk (that he’s been wanting to do for many years) and a Language Server Protocol (LSP) for Smalltalk 𝟮. 𝗙𝗮𝗰𝗲𝗯𝗼𝗼𝗸 𝘄𝗿𝗼𝘁𝗲 𝗻𝗼 𝘂𝗻𝗶𝘁 𝘁𝗲𝘀𝘁𝘀 𝗶𝗻 𝟮𝟬𝟭𝟭, 𝗮𝗻𝗱 𝘁𝗵𝗶𝘀 𝘀𝘁𝘂𝗻𝗻𝗲𝗱 𝗞𝗲𝗻𝘁, 𝗯𝗮𝗰𝗸 𝗶𝗻 𝘁𝗵𝗲 𝗱𝗮𝘆. Kent joined Facebook in 2011, and was taken aback by the lack of testing and how everyone pushed code to production without automated testing. What he came to realize – and appreciate! – was how Facebook had several things balancing this out: • Devs took responsibility for their code very seriously • Nothing at Facebook was “someone else’s problem:” devs would fix bugs when they saw them, regardless of whose commit caused it • Feature flags were heavily used for risky code • Facebook did staged rollouts to smaller markets like New Zealand To this date, Facebook ships code to production in a unique way. We covered more in the deepdive Shipping to Production at

Gergely Orosz

42,514 次观看 • 1 年前

Chris Lattner (Chris Lattner) is one of the most influential engineers of the past two decades. He created LLVM, Swift, contributed to TensorFlow, and created the Mojo programming language. What was the story about creating Swift - and why did he face resistance inside Apple when wanting to replace Objective C? What did he learn at Tesla, Google and CPU maker SiFive, that led him to working on Mojo at Modular? We cover these and many more in today's episode. 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. My favorite quote from Chris in this episode: “I believe in the power of programmers. I believe in the human potential of people that want to create things. And that’s fundamentally why I love software is that you can create anything that you can imagine.”
1:54

Chris Lattner (Chris Lattner) is one of the most influential engineers of the past two decades. He created LLVM, Swift, contributed to TensorFlow, and created the Mojo programming language. What was the story about creating Swift - and why did he face resistance inside Apple when wanting to replace Objective C? What did he learn at Tesla, Google and CPU maker SiFive, that led him to working on Mojo at Modular? We cover these and many more in today's episode. 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. My favorite quote from Chris in this episode: “I believe in the power of programmers. I believe in the human potential of people that want to create things. And that’s fundamentally why I love software is that you can create anything that you can imagine.”

Gergely Orosz

206,271 次观看 • 8 个月前

It's always energizing to do a podcast with Steve Yegge (Steve Yegge, engineer+author, formerly at Amazon+Google, creator of Gas Town). Timestamps: 00:00 Intro 01:43 Steve’s latest projects 02:27 Important blog posts 04:48 Shifts in what engineers need to know 10:46 Steve’s current AI stance 13:23 Steve’s book Vibe Coding 18:25 Layoffs and disruption in tech 31:13 Gas Town 40:10 New ways of working 51:08 The problem of too many people 54:45 Why AI results lag in business 59:57 Gamification and product stickiness 1:04:54 The ‘Bitter Lesson’ explained 1:07:14 The future of software development 1:23:06 Where languages stand 1:24:47 Adapting to change 1:27:32 Steve’s predictions Brought to you by: • Statsig – ⁠ The unified platform for flags, analytics, experiments, and more. • Sonar – The makers of SonarQube, the industry standard for automated code review. • WorkOS – Everything you need to make your app enterprise ready. Three interesting thoughts from Steve that we talked about in this conversation: 1. Reading ability is becoming a blocker for wider AI adoption. Some struggle with walls of text that current AI tools produce, and Steve predicts that in the very near future, most people will program by talking to a visual avatar, not reading terminal output because he observes that five paragraphs is already a lot to read for many devs. 2. What software engineers need to know keeps changing. In the 1990s, any decent software engineer knew Assembly, and today almost no decent developer knows it because Assembly has long been superseded by technical progress. What engineers “need” to know these days is different from the ‘90s and that process continues with AI, changing the parts of the craft that are essential for devs. We grumble about this but that won’t change anything by itself. 3. There’s a “Dracula Effect” where AI-augmented work drains engineers faster than traditional work. This is because AI automates the easy tasks, meaning that engineers are stuck doing high-intensity thinking all day. Steve says you may only get three daily productive hours at max speed, but during that time, you could produce 100x more output than before.
1:31:59

It's always energizing to do a podcast with Steve Yegge (Steve Yegge, engineer+author, formerly at Amazon+Google, creator of Gas Town). Timestamps: 00:00 Intro 01:43 Steve’s latest projects 02:27 Important blog posts 04:48 Shifts in what engineers need to know 10:46 Steve’s current AI stance 13:23 Steve’s book Vibe Coding 18:25 Layoffs and disruption in tech 31:13 Gas Town 40:10 New ways of working 51:08 The problem of too many people 54:45 Why AI results lag in business 59:57 Gamification and product stickiness 1:04:54 The ‘Bitter Lesson’ explained 1:07:14 The future of software development 1:23:06 Where languages stand 1:24:47 Adapting to change 1:27:32 Steve’s predictions Brought to you by: • Statsig – ⁠ The unified platform for flags, analytics, experiments, and more. • Sonar – The makers of SonarQube, the industry standard for automated code review. • WorkOS – Everything you need to make your app enterprise ready. Three interesting thoughts from Steve that we talked about in this conversation: 1. Reading ability is becoming a blocker for wider AI adoption. Some struggle with walls of text that current AI tools produce, and Steve predicts that in the very near future, most people will program by talking to a visual avatar, not reading terminal output because he observes that five paragraphs is already a lot to read for many devs. 2. What software engineers need to know keeps changing. In the 1990s, any decent software engineer knew Assembly, and today almost no decent developer knows it because Assembly has long been superseded by technical progress. What engineers “need” to know these days is different from the ‘90s and that process continues with AI, changing the parts of the craft that are essential for devs. We grumble about this but that won’t change anything by itself. 3. There’s a “Dracula Effect” where AI-augmented work drains engineers faster than traditional work. This is because AI automates the easy tasks, meaning that engineers are stuck doing high-intensity thinking all day. Steve says you may only get three daily productive hours at max speed, but during that time, you could produce 100x more output than before.

Gergely Orosz

41,987 次观看 • 4 个月前

How have servers and the cloud evolved in the last 30 years, and what might be next? Bryan Cantrill (Bryan Cantrill) has been at the thick of the industry since the Dotcom Boom and Bust, and shares fascinating stories from both this time; on how AWS was born; why Kubernetes was key for GCP to gain ground, and why they're building a completely custom server rack computer at Oxide Computer Company. Bryan is one of my all-time favorite people to talk with - don't miss this one. Teaser - he talked about how Jeff Bezos tricked almost everyone in tech to believe that the cloud was a terrible business, and how Oracle (yes, Oracle!) taught him something extremely valuable he uses to this date: • YouTube: • Spotify: • Apple: Thanks to our wonderful season sponsors: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. Check it out: •⁠ Linear ⁠ — ⁠ The system for modern product development. They now support AI agents and you can also build your own - see how:
1:10

How have servers and the cloud evolved in the last 30 years, and what might be next? Bryan Cantrill (Bryan Cantrill) has been at the thick of the industry since the Dotcom Boom and Bust, and shares fascinating stories from both this time; on how AWS was born; why Kubernetes was key for GCP to gain ground, and why they're building a completely custom server rack computer at Oxide Computer Company. Bryan is one of my all-time favorite people to talk with - don't miss this one. Teaser - he talked about how Jeff Bezos tricked almost everyone in tech to believe that the cloud was a terrible business, and how Oracle (yes, Oracle!) taught him something extremely valuable he uses to this date: • YouTube: • Spotify: • Apple: Thanks to our wonderful season sponsors: •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more. Check it out: •⁠ Linear ⁠ — ⁠ The system for modern product development. They now support AI agents and you can also build your own - see how:

Gergely Orosz

36,842 次观看 • 6 个月前

How is the world's largest storage system, AWS S3 built? I found the best person to talk about this: Mai-Lan Tomsen Bukovec, who has been heading up S3 for 13 years (!) S3's scale is something else (tens of millions of hard drives, eleven 9s of durability (!!) and heavy usage of formal methods, microservices dedicated to durability, amongst others.) Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Statsig — ⁠ The unified platform for flags, analytics, experiments, and more. • Sonar – The makers of SonarQube, the industry standard for automated code review. Check out their latest State of Code Developer Survey report: • WorkOS – Everything you need to make your app enterprise ready.
1:38

How is the world's largest storage system, AWS S3 built? I found the best person to talk about this: Mai-Lan Tomsen Bukovec, who has been heading up S3 for 13 years (!) S3's scale is something else (tens of millions of hard drives, eleven 9s of durability (!!) and heavy usage of formal methods, microservices dedicated to durability, amongst others.) Watch or listen: • YouTube: • Spotify: • Apple: Brought to you by: • Statsig — ⁠ The unified platform for flags, analytics, experiments, and more. • Sonar – The makers of SonarQube, the industry standard for automated code review. Check out their latest State of Code Developer Survey report: • WorkOS – Everything you need to make your app enterprise ready.

Gergely Orosz

133,580 次观看 • 5 个月前

What if we're actually in the middle of the third golden age of software engineering? This is what Grady Booch sees happening. If you are anxious about the state of the industry, you want to watch/listen to Grady's longer-term perspective and stories. Watch the full episode here: 00:00 Intro 01:58 The first golden age of software engineering 18:59 The software crisis 33:01 The second golden age of software engineering 42:21 Y2K and the Dotcom crash 45:47 Early AI 47:34 The third golden age of software engineering 51:48 Why software engineers will very much be needed 58:46 Grady responds to Dario Amodei 1:06:54 New skills engineers will need to succeed 1:10:04 Resources for studying complex systems 1:14:33 How to thrive during periods of change Brought to you by: • Statsig — ⁠ The unified platform for flags, analytics, experiments, and more. • Sonar – The makers of SonarQube, the industry standard for automated code review. Join me online at the Sonar Summit on March 3rd, where I talk about practical tactics for the AI era. • WorkOS – Everything you need to make your app enterprise-ready.
1:17:58

What if we're actually in the middle of the third golden age of software engineering? This is what Grady Booch sees happening. If you are anxious about the state of the industry, you want to watch/listen to Grady's longer-term perspective and stories. Watch the full episode here: 00:00 Intro 01:58 The first golden age of software engineering 18:59 The software crisis 33:01 The second golden age of software engineering 42:21 Y2K and the Dotcom crash 45:47 Early AI 47:34 The third golden age of software engineering 51:48 Why software engineers will very much be needed 58:46 Grady responds to Dario Amodei 1:06:54 New skills engineers will need to succeed 1:10:04 Resources for studying complex systems 1:14:33 How to thrive during periods of change Brought to you by: • Statsig — ⁠ The unified platform for flags, analytics, experiments, and more. • Sonar – The makers of SonarQube, the industry standard for automated code review. Join me online at the Sonar Summit on March 3rd, where I talk about practical tactics for the AI era. • WorkOS – Everything you need to make your app enterprise-ready.

Gergely Orosz

86,896 次观看 • 5 个月前

Boris Cherny ( Boris Cherny ) created Claude Code, but few know his full career story. Today I'm sharing an interview with him about how he grew as an engineer, we discussed: • Why every engineer needs "side quests" • Why being under leveled is a good thing • The story behind his growth to Principal (IC8) at Meta • Technical book that had the biggest impact on him as an engineer • The most important principle in product engineering • Claude Code stories & competition in AI coding products You can find the full episode here: • YouTube: • Spotify: • Transcript: • Apple:
0:59

Boris Cherny ( Boris Cherny ) created Claude Code, but few know his full career story. Today I'm sharing an interview with him about how he grew as an engineer, we discussed: • Why every engineer needs "side quests" • Why being under leveled is a good thing • The story behind his growth to Principal (IC8) at Meta • Technical book that had the biggest impact on him as an engineer • The most important principle in product engineering • Claude Code stories & competition in AI coding products You can find the full episode here: • YouTube: • Spotify: • Transcript: • Apple:

Ryan Peterman

577,196 次观看 • 7 个月前

🚨ZUCK: "Probably in 2025, Meta, as well as other companies, will have an AI that can effectively be a mid-level engineer that you have at your company that can write code. In the beginning that will be very expensive to run, then at some point a lot of the code we have in our apps will be built by AI engineers instead of people engineers. In my opinion that will augment the people working on it. My view is that in the future people will be so much more creative and freed up to do crazy things."
1:02

🚨ZUCK: "Probably in 2025, Meta, as well as other companies, will have an AI that can effectively be a mid-level engineer that you have at your company that can write code. In the beginning that will be very expensive to run, then at some point a lot of the code we have in our apps will be built by AI engineers instead of people engineers. In my opinion that will augment the people working on it. My view is that in the future people will be so much more creative and freed up to do crazy things."

Autism Capital 🧩

1,666,456 次观看 • 1 年前

Some personal hot takes from AI: engineer Miami follows... 1. Software development is a dead-end profession because anyone can be a software developer now. 2. Anyone can use Cursor or any other tool and generate code. Being a coder and being a software engineer are different. 3. Computers used to be gated; now everyone has the power to make computers malleable. Everyone is a software developer now, but that does not mean they are software engineers 4. If you cannot demonstrate how a coding agent works, you are just a consumer and have imposed an artificial glass ceiling on your career as a software engineer. 5. If you are curious, you will have a job. If you have not been curious in the last two years, you are replaceable. 6. SaaS per-seat economics may become unstable as customers need fewer people to achieve results, prompting founders to think about new unit economics 7. Most companies will take two or three years (or more!) to figure out AI transformation. 8. Some companies are already building AI native teams of five to ten people who can build with the grain of AI 9. There will be an explosion in the number of software developers. Software development is now essentially free, and tokens are cheaper than humans 10. Not enough engineers know what it means to be a product engineer 11. JIRA ticket monkeys are cooked 12. If your company has banned AI, you should quit that company 13. AI is more like a musical instrument than just a tool play with it, make discoveries, build intuition learn where AI is good and where it fails
14:55

Some personal hot takes from AI: engineer Miami follows... 1. Software development is a dead-end profession because anyone can be a software developer now. 2. Anyone can use Cursor or any other tool and generate code. Being a coder and being a software engineer are different. 3. Computers used to be gated; now everyone has the power to make computers malleable. Everyone is a software developer now, but that does not mean they are software engineers 4. If you cannot demonstrate how a coding agent works, you are just a consumer and have imposed an artificial glass ceiling on your career as a software engineer. 5. If you are curious, you will have a job. If you have not been curious in the last two years, you are replaceable. 6. SaaS per-seat economics may become unstable as customers need fewer people to achieve results, prompting founders to think about new unit economics 7. Most companies will take two or three years (or more!) to figure out AI transformation. 8. Some companies are already building AI native teams of five to ten people who can build with the grain of AI 9. There will be an explosion in the number of software developers. Software development is now essentially free, and tokens are cheaper than humans 10. Not enough engineers know what it means to be a product engineer 11. JIRA ticket monkeys are cooked 12. If your company has banned AI, you should quit that company 13. AI is more like a musical instrument than just a tool play with it, make discoveries, build intuition learn where AI is good and where it fails

geoff

55,887 次观看 • 18 天前

A man who's been at Amazon for 27 years: "Tasks that needed dozens of developers and a multi-year budget are now done by a motivated engineer over a weekend." 31 minutes on what AI does to teams, jobs and moats, from a guy leading it at Amazon. He explains how to be the one who wins from this, not the one who gets left behind. Watch it, then read the guide on everything Claude can do below and you'll already know more than 99% of people.
31:30

A man who's been at Amazon for 27 years: "Tasks that needed dozens of developers and a multi-year budget are now done by a motivated engineer over a weekend." 31 minutes on what AI does to teams, jobs and moats, from a guy leading it at Amazon. He explains how to be the one who wins from this, not the one who gets left behind. Watch it, then read the guide on everything Claude can do below and you'll already know more than 99% of people.

Anatoli Kopadze

64,600 次观看 • 16 天前

Boris Cherny ( Boris Cherny ) created Claude Code, but few know his full career story. I interviewed him about how he grew as an engineer (episode dropping next week), we discussed: • Why every engineer needs "side quests" • Why being under leveled is a good thing • The story behind his growth to Principal (IC8) at Meta • Technical book that had the biggest impact on him as an engineer • The most important principle in product engineering • Claude Code stories & competition in AI coding products The full episode will drop next week on the following platforms, subscribe if you don't want to miss it: Youtube - Spotify - Apple Podcasts -
0:44

Boris Cherny ( Boris Cherny ) created Claude Code, but few know his full career story. I interviewed him about how he grew as an engineer (episode dropping next week), we discussed: • Why every engineer needs "side quests" • Why being under leveled is a good thing • The story behind his growth to Principal (IC8) at Meta • Technical book that had the biggest impact on him as an engineer • The most important principle in product engineering • Claude Code stories & competition in AI coding products The full episode will drop next week on the following platforms, subscribe if you don't want to miss it: Youtube - Spotify - Apple Podcasts -

Ryan Peterman

72,222 次观看 • 7 个月前

How does tooling and promotions work at Google, and what are tactics to become a more influential engineer? Ex-Google engineer Irina Stanescu shares insights in the latest The Pragmatic Engineer Podcast episode. Watch the full episode: A special thanks to the fantastic sponsors of the podcast: • WorkOS — The modern identity platform for B2B SaaS. Check it out at • Sonar — Trust your developers – verify your AI-generated code. Learn more at In the episode, dive into these following topics: • An inside look at Google’s unique working processes • How to build credibility as a new engineer • Tactical tips for getting promoted • The importance of having a career plan and guidance in designing one • Having influence vs. influencing—and how to become more influential • Essential leadership skills to develop • And so much more Check it out, and thank you to Irina for the insightful and honest chat! Irina also writes the newsletter The Caring Techie, and you can read it here: (If your company is interested in sponsoring the podcast, you can reach out at sponsor@pragmaticengineer.com. 2024 is fully booked, but there are open spaces for the first quarter of 2025).
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How does tooling and promotions work at Google, and what are tactics to become a more influential engineer? Ex-Google engineer Irina Stanescu shares insights in the latest The Pragmatic Engineer Podcast episode. Watch the full episode: A special thanks to the fantastic sponsors of the podcast: • WorkOS — The modern identity platform for B2B SaaS. Check it out at • Sonar — Trust your developers – verify your AI-generated code. Learn more at In the episode, dive into these following topics: • An inside look at Google’s unique working processes • How to build credibility as a new engineer • Tactical tips for getting promoted • The importance of having a career plan and guidance in designing one • Having influence vs. influencing—and how to become more influential • Essential leadership skills to develop • And so much more Check it out, and thank you to Irina for the insightful and honest chat! Irina also writes the newsletter The Caring Techie, and you can read it here: (If your company is interested in sponsoring the podcast, you can reach out at [email protected]. 2024 is fully booked, but there are open spaces for the first quarter of 2025).

Gergely Orosz

17,617 次观看 • 1 年前

In May 2023, a live streaming world record was set with 32 million concurrent viewers watching the finale of the IPL cricket game. How was this system built? Ashutosh Agrawal was the architect behind this system, and he walks us through how live streaming at scale works, how the system was built and tested, and other interesting learnings. Watch or listen: • YouTube: • Spotify: • Apple: --- Brought to you by our wonderful sponsors: • WorkOS — The modern identity platform for B2B SaaS • CodeRabbit — Cut code review time and bugs in half (use the code PRAGMATIC to get one month free) • Augment Code — AI coding assistant that pro engineering teams love --- Three of my biggest takeaways: 1. The architecture behind live streaming systems is surprisingly logical. In the episode, Ashutosh explains how the live streaming system works, starting from the physical cameras on-site, through the production control room (PCR), streams being sliced-and-diced, and the HLS protocol (HTTP Live Streaming) used. 2. There are a LOT of tradeoffs you can play with when live streaming! The tradeoffs between server load, latency, server resources vs client caching are hard decisions to make. Want to reduce the server load? Serve longer chunks to clients, resulting in fewer requests per minute, per client… at the expense of clients potentially lagging more behind. This is just one of many possible decisions to make. 3. “Game day” is such a neat load testing concept. The team at Jio would simulate “game day” load months before the event. They did tell teams when the load test will start: but did not share anything else! Preparing for a “Game day” test is a lot of work, but it can pay off to find parts of the system that shutter under extreme load. See more takeaways and a summary here: Thanks Ashutosh for all these behind-the-scene details!
0:30

In May 2023, a live streaming world record was set with 32 million concurrent viewers watching the finale of the IPL cricket game. How was this system built? Ashutosh Agrawal was the architect behind this system, and he walks us through how live streaming at scale works, how the system was built and tested, and other interesting learnings. Watch or listen: • YouTube: • Spotify: • Apple: --- Brought to you by our wonderful sponsors: • WorkOS — The modern identity platform for B2B SaaS • CodeRabbit — Cut code review time and bugs in half (use the code PRAGMATIC to get one month free) • Augment Code — AI coding assistant that pro engineering teams love --- Three of my biggest takeaways: 1. The architecture behind live streaming systems is surprisingly logical. In the episode, Ashutosh explains how the live streaming system works, starting from the physical cameras on-site, through the production control room (PCR), streams being sliced-and-diced, and the HLS protocol (HTTP Live Streaming) used. 2. There are a LOT of tradeoffs you can play with when live streaming! The tradeoffs between server load, latency, server resources vs client caching are hard decisions to make. Want to reduce the server load? Serve longer chunks to clients, resulting in fewer requests per minute, per client… at the expense of clients potentially lagging more behind. This is just one of many possible decisions to make. 3. “Game day” is such a neat load testing concept. The team at Jio would simulate “game day” load months before the event. They did tell teams when the load test will start: but did not share anything else! Preparing for a “Game day” test is a lot of work, but it can pay off to find parts of the system that shutter under extreme load. See more takeaways and a summary here: Thanks Ashutosh for all these behind-the-scene details!

Gergely Orosz

50,597 次观看 • 1 年前