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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... show more

Gergely Orosz

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225,804 次观看 • 8 个月前 •via X (Twitter)

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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.

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

134,042 次观看 • 8 个月前

How has the day-to-day workflow of Mitchell Hashimoto (Mitchell Hashimoto) changed, thanks to AI tools? Timestamps: 00:00 Intro 07:19 HashiCorp origins 18:22 The 2010s startup scene in SF 23:11 Funding HashiCorp 25:23 The "Hashi stack" 38:28 The open-core pivot 48:08 Taking HashiCorp public 51:58 The almost-VMware acquisition 59:10 Mitchell’s take on AWS, GCP and Azure 01:06:02 AI’s impact on open source 01:07:00 Ghostty 01:19:13 How Mitchell uses AI 01:28:36 Open source + AI 01:31:46 The problem of Git and monorepos 01:39:57 Mitchell’s hiring practices 01:47:52 Mitchell’s AI adoption journey 01:50:41 Advice to future founders 01:55:03 Closing Also on YouTube, Spotify and Apple (see the next tweet) 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: • WorkOS – Everything you need to make your app enterprise ready.

How has the day-to-day workflow of Mitchell Hashimoto (Mitchell Hashimoto) changed, thanks to AI tools? Timestamps: 00:00 Intro 07:19 HashiCorp origins 18:22 The 2010s startup scene in SF 23:11 Funding HashiCorp 25:23 The "Hashi stack" 38:28 The open-core pivot 48:08 Taking HashiCorp public 51:58 The almost-VMware acquisition 59:10 Mitchell’s take on AWS, GCP and Azure 01:06:02 AI’s impact on open source 01:07:00 Ghostty 01:19:13 How Mitchell uses AI 01:28:36 Open source + AI 01:31:46 The problem of Git and monorepos 01:39:57 Mitchell’s hiring practices 01:47:52 Mitchell’s AI adoption journey 01:50:41 Advice to future founders 01:55:03 Closing Also on YouTube, Spotify and Apple (see the next tweet) 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: • WorkOS – Everything you need to make your app enterprise ready.

Gergely Orosz

59,544 次观看 • 7 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.

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

87,027 次观看 • 8 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.

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

51,868 次观看 • 11 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:

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

38,992 次观看 • 10 个月前

What does it mean for software engineering when we no longer write the code? Here's the take from Boris Cherny (Boris Cherny), the creator of Claude Code. Timestamps: 00:00 Intro 11:15 Lessons from Meta 19:46 Joining Anthropic 23:08 The origins of Claude Code 32:55 Boris's Claude Code workflow 36:27 Parallel agents 40:25 Code reviews 47:18 Claude Code's architecture 52:38 Permissions and sandboxing 55:05 Engineering culture at Anthropic 1:05:15 Claude Cowork 1:12:48 Observability and privacy 1:14:45 Agent swarms 1:21:16 LLMs and the printing press analogy 1:30:16 Standout engineer archetypes 1:32:12 What skills still matter for engineers 1:35:24 Book recommendations 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. Proactively find and fix issues in real-time with the SonarQube MCP Server: • WorkOS – Everything you need to make your app enterprise ready. Three interesting things from this conversation: 1. Boris automated himself out of code review well before AI. Boris was one of the most prolific code reviewers at Meta company. And he worked hard to minimize time spent on code review. His system::every time he left the same kind of review comment, he logged it in a spreadsheet. Once a pattern hit 3-4 occurrences, he’d write a lint rule to automate it away! 2. PRDs are dead on the Claude Code team: prototypes replaced them. Instead of writing Product Requirement Documents (specs), they build hundreds of working prototypes before shipping a feature. Boris: “There’s just no way we could have shipped this if we started with static mocks and Figma or if we started with a PRD.” 3. This is the year of the generalist (and maybe the year of those with ADHD) Boris’s work has shifted from deep-focus single-threaded coding to managing multiple parallel agents and context-switching rapidly. As Boris put it: “It’s not so much about deep work, it’s about how good I am at context switching and jumping across multiple different contexts very quickly.”

What does it mean for software engineering when we no longer write the code? Here's the take from Boris Cherny (Boris Cherny), the creator of Claude Code. Timestamps: 00:00 Intro 11:15 Lessons from Meta 19:46 Joining Anthropic 23:08 The origins of Claude Code 32:55 Boris's Claude Code workflow 36:27 Parallel agents 40:25 Code reviews 47:18 Claude Code's architecture 52:38 Permissions and sandboxing 55:05 Engineering culture at Anthropic 1:05:15 Claude Cowork 1:12:48 Observability and privacy 1:14:45 Agent swarms 1:21:16 LLMs and the printing press analogy 1:30:16 Standout engineer archetypes 1:32:12 What skills still matter for engineers 1:35:24 Book recommendations 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. Proactively find and fix issues in real-time with the SonarQube MCP Server: • WorkOS – Everything you need to make your app enterprise ready. Three interesting things from this conversation: 1. Boris automated himself out of code review well before AI. Boris was one of the most prolific code reviewers at Meta company. And he worked hard to minimize time spent on code review. His system::every time he left the same kind of review comment, he logged it in a spreadsheet. Once a pattern hit 3-4 occurrences, he’d write a lint rule to automate it away! 2. PRDs are dead on the Claude Code team: prototypes replaced them. Instead of writing Product Requirement Documents (specs), they build hundreds of working prototypes before shipping a feature. Boris: “There’s just no way we could have shipped this if we started with static mocks and Figma or if we started with a PRD.” 3. This is the year of the generalist (and maybe the year of those with ADHD) Boris’s work has shifted from deep-focus single-threaded coding to managing multiple parallel agents and context-switching rapidly. As Boris put it: “It’s not so much about deep work, it’s about how good I am at context switching and jumping across multiple different contexts very quickly.”

Gergely Orosz

491,342 次观看 • 7 个月前

Just six months ago, DHH (creator of Ruby on Rails and Omarchy) said how he doesn’t really use AI tools to write code, because they are not good enough. Things have changed, a lot. Timestamps: 00:00 Intro 02:11 Omarchy and Ruby on Rails 08:25 37signals overview 10:12 Launching HEY 18:38 Building HEY 22:47 Designers at 37signals 28:08 The craft of design 31:52 Why DHH now embraces AI workflows 39:45 The AI inflection point 44:23 DHH’s agent-first workflow 55:09 AI’s impact on junior developers 1:03:08 Developer experience with AI 1:16:43 What does AI mean for developers? 1:23:33 37signals teams and hiring 1:38:20 Work-life balance with AI 1:41:41 Why DHH keeps building 1:45:24 Closing Brought to you by: • Statsig – ⁠ The unified platform for flags, analytics, experiments, and more. Stop switching between different tools, and have them all in one place. • WorkOS – Everything you need to make your app enterprise ready. WorkOS gives you APIs to ship enterprise features in days. Check out • Sonar – The makers of SonarQube, the industry standard for automated code review. See how SonarQube Advanced Security is empowering the Agent Centric Development Cycle (AC/DC) with new capabilities. Three interesting observations from this conversation: #1 DHH's philosophy on AI has not changed, but the available tools very much have. Autocomplete-style coding assistants were genuinely annoying for experienced developers six months ago. Things changed with the shift from tab-completion to agent harnesses, plus the emergence of powerful models like Opus 4.5 – when agents started producing code which DHH does want to merge with little to no alteration. #2 Beautiful code and products aren’t matters of vanity; they’re signals of correctness. Dipping into philosophy, DHH says: “When something is beautiful, it’s likely to be correct.” He argues that Steve Jobs wanted the inside of a computer to be beautiful because people who care about circuit board layout are also those who sweat on the details of the UI. #3 DHH’s development workflow, today: He runs tmux to have two models running, and neovim in the center. Specifics: - One fast LLM running (typically Gemini 2.5) in one split terminal - A slow but more powerful model in another terminal (usually Opus) - NeoVim for reviewing diffs via Lazygit

Just six months ago, DHH (creator of Ruby on Rails and Omarchy) said how he doesn’t really use AI tools to write code, because they are not good enough. Things have changed, a lot. Timestamps: 00:00 Intro 02:11 Omarchy and Ruby on Rails 08:25 37signals overview 10:12 Launching HEY 18:38 Building HEY 22:47 Designers at 37signals 28:08 The craft of design 31:52 Why DHH now embraces AI workflows 39:45 The AI inflection point 44:23 DHH’s agent-first workflow 55:09 AI’s impact on junior developers 1:03:08 Developer experience with AI 1:16:43 What does AI mean for developers? 1:23:33 37signals teams and hiring 1:38:20 Work-life balance with AI 1:41:41 Why DHH keeps building 1:45:24 Closing Brought to you by: • Statsig – ⁠ The unified platform for flags, analytics, experiments, and more. Stop switching between different tools, and have them all in one place. • WorkOS – Everything you need to make your app enterprise ready. WorkOS gives you APIs to ship enterprise features in days. Check out • Sonar – The makers of SonarQube, the industry standard for automated code review. See how SonarQube Advanced Security is empowering the Agent Centric Development Cycle (AC/DC) with new capabilities. Three interesting observations from this conversation: #1 DHH's philosophy on AI has not changed, but the available tools very much have. Autocomplete-style coding assistants were genuinely annoying for experienced developers six months ago. Things changed with the shift from tab-completion to agent harnesses, plus the emergence of powerful models like Opus 4.5 – when agents started producing code which DHH does want to merge with little to no alteration. #2 Beautiful code and products aren’t matters of vanity; they’re signals of correctness. Dipping into philosophy, DHH says: “When something is beautiful, it’s likely to be correct.” He argues that Steve Jobs wanted the inside of a computer to be beautiful because people who care about circuit board layout are also those who sweat on the details of the UI. #3 DHH’s development workflow, today: He runs tmux to have two models running, and neovim in the center. Specifics: - One fast LLM running (typically Gemini 2.5) in one split terminal - A slow but more powerful model in another terminal (usually Opus) - NeoVim for reviewing diffs via Lazygit

Gergely Orosz

329,135 次观看 • 6 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.

Gergely Orosz

42,193 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).

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

17,634 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.”

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 • 11 个月前

How did a tiny team of 30 engineers build WhatsApp, more than a decade ago? From Jean Lee, engineer #19 at the company. Timestamps: 00:00 Intro 01:39 Early years in tech 06:18 Becoming engineer #19 at WhatsApp 13:53 WhatsApp’s tech stack 18:09 WhatsApp’s unique ways of working 25:27 Countdown displays and outages 27:07 Why WhatsApp won 28:53 The Facebook acquisition 33:13 Life after acquisition 39:27 Working at Facebook in London 44:07 Transitioning to management 47:27 Performance reviews as a manager 53:29 After Facebook 58:53 AI’s impact on engineering 1:02:34 Jean’s advice to new grads and startups 1:06:45 Empowering employees 1:08:17 Book recommendations 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. • WorkOS – Everything you need to make your app enterprise ready Three interesting observations from this episode: 1. WhatsApp had no code reviews after in-place. WhatsApp cofounder, Brian Acton, reviewed the very first pull request of each new hire, and after that, there were no more code reviews. Jean recounts how Brian reviewed her debut PR in extreme detail. This first (and only!) review set the bar high, and she wrote code to that standard from then on. 2. WhatsApp had close to zero formal processes. WhatsApp had no Scrum, no Agile, no TDD (test driven development), and no formal code reviews beyond the first commit. In contrast, Skype had 1,000 engineers and mandatory Scrum training, but WhatsApp still outcompeted it and won. Jean’s response to hearing of all the formal processes Skype used in order to execute faster: “I’m surprised to hear they thought they were shipping faster because of it.” Perhaps process is often a substitute for trust, not quality?” 3. Saying “no” to features was a competitive advantage. WhatsApp’s CEO, Jan Koum, rejected 99% of feature requests from the team. While competitors shipped dozens of shiny, new features, WhatsApp ruthlessly prioritized reliability and simplicity. Jan repeatedly told the team what the mission was. “I want a grandma living in the countryside to be able to use our app”, he said.

How did a tiny team of 30 engineers build WhatsApp, more than a decade ago? From Jean Lee, engineer #19 at the company. Timestamps: 00:00 Intro 01:39 Early years in tech 06:18 Becoming engineer #19 at WhatsApp 13:53 WhatsApp’s tech stack 18:09 WhatsApp’s unique ways of working 25:27 Countdown displays and outages 27:07 Why WhatsApp won 28:53 The Facebook acquisition 33:13 Life after acquisition 39:27 Working at Facebook in London 44:07 Transitioning to management 47:27 Performance reviews as a manager 53:29 After Facebook 58:53 AI’s impact on engineering 1:02:34 Jean’s advice to new grads and startups 1:06:45 Empowering employees 1:08:17 Book recommendations 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. • WorkOS – Everything you need to make your app enterprise ready Three interesting observations from this episode: 1. WhatsApp had no code reviews after in-place. WhatsApp cofounder, Brian Acton, reviewed the very first pull request of each new hire, and after that, there were no more code reviews. Jean recounts how Brian reviewed her debut PR in extreme detail. This first (and only!) review set the bar high, and she wrote code to that standard from then on. 2. WhatsApp had close to zero formal processes. WhatsApp had no Scrum, no Agile, no TDD (test driven development), and no formal code reviews beyond the first commit. In contrast, Skype had 1,000 engineers and mandatory Scrum training, but WhatsApp still outcompeted it and won. Jean’s response to hearing of all the formal processes Skype used in order to execute faster: “I’m surprised to hear they thought they were shipping faster because of it.” Perhaps process is often a substitute for trust, not quality?” 3. Saying “no” to features was a competitive advantage. WhatsApp’s CEO, Jan Koum, rejected 99% of feature requests from the team. While competitors shipped dozens of shiny, new features, WhatsApp ruthlessly prioritized reliability and simplicity. Jan repeatedly told the team what the mission was. “I want a grandma living in the countryside to be able to use our app”, he said.

Gergely Orosz

112,027 次观看 • 7 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:

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 • 10 个月前

OpenClaw - the agentic software spreading like wildfire - was built on top of Pi, a minimalist, self-modifying agent. I sat down with Pi's creator, Mario Zechner and longtime Pi user (+ the creator of Flask) Armin Ronacher ⇌ to talk Pi, and their (very grounded!) takes on building with AI. Timestamps: 00:00 Intro 07:30 How Mario, Armin, and Peter Steinberger met 15:15 How 30 dev teams use AI agents: learnings 21:50 The importance of judgment 24:26 Challenges when non-engineers write code 28:30 Downsides of over-automation 32:18 Pi 48:09 OpenClaw + Pi 50:54 “Clankers” 57:32 Open source and AI 1:00:22 Complexity as the enemy 1:02:50 Building an AI-native startup 1:11:52 “Slow the F down” 1:16:40 MCPs vs. CLI 1:25:03 Predictions and staying up to date • 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 code verification and automated code review. Try it out for yourself. • WorkOS – WorkOS gives you APIs to ship enterprise features – SSO, directory sync, RBAC, audit logs – in days, not months. Visit learn more. --- Three parts I found especially interesting in this discussion: 1. New trend: AI makes it harder for senior engineers to reject pointless complexity. Historically, senior engineers kept software complexity at bay simply by saying “no” a lot. But Armin observes that these days, more junior engineers and product managers deploy agent-scripted counterarguments when a senior colleague kicks an idea to the curb. This makes decision-making exhausting, and more bad ideas make it into production as a result. 2. It should be MUCH easier to build specialized tools for specific tasks. Different projects need different harness types because, as Mario points out, the same hammer is not ideal for every single construction job. As such, Pi is built with the goal of allowing the creation of specialized harnesses. It can modify itself so that a user can create the bespoke harness needed for any task. Mario believes it’s a preview of how self-modifiable software might look in the future. 3. Automation bias is one of the biggest risks of working with AI agents. Once devs confirm that an AI agent can produce acceptable code, they start to review its output less often, even though agents can – and do! – produce slop. Mario advises being far more sceptical with agents, and cautions that the quality of their output isn’t guaranteed, however well they performed previously.

OpenClaw - the agentic software spreading like wildfire - was built on top of Pi, a minimalist, self-modifying agent. I sat down with Pi's creator, Mario Zechner and longtime Pi user (+ the creator of Flask) Armin Ronacher ⇌ to talk Pi, and their (very grounded!) takes on building with AI. Timestamps: 00:00 Intro 07:30 How Mario, Armin, and Peter Steinberger met 15:15 How 30 dev teams use AI agents: learnings 21:50 The importance of judgment 24:26 Challenges when non-engineers write code 28:30 Downsides of over-automation 32:18 Pi 48:09 OpenClaw + Pi 50:54 “Clankers” 57:32 Open source and AI 1:00:22 Complexity as the enemy 1:02:50 Building an AI-native startup 1:11:52 “Slow the F down” 1:16:40 MCPs vs. CLI 1:25:03 Predictions and staying up to date • 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 code verification and automated code review. Try it out for yourself. • WorkOS – WorkOS gives you APIs to ship enterprise features – SSO, directory sync, RBAC, audit logs – in days, not months. Visit learn more. --- Three parts I found especially interesting in this discussion: 1. New trend: AI makes it harder for senior engineers to reject pointless complexity. Historically, senior engineers kept software complexity at bay simply by saying “no” a lot. But Armin observes that these days, more junior engineers and product managers deploy agent-scripted counterarguments when a senior colleague kicks an idea to the curb. This makes decision-making exhausting, and more bad ideas make it into production as a result. 2. It should be MUCH easier to build specialized tools for specific tasks. Different projects need different harness types because, as Mario points out, the same hammer is not ideal for every single construction job. As such, Pi is built with the goal of allowing the creation of specialized harnesses. It can modify itself so that a user can create the bespoke harness needed for any task. Mario believes it’s a preview of how self-modifiable software might look in the future. 3. Automation bias is one of the biggest risks of working with AI agents. Once devs confirm that an AI agent can produce acceptable code, they start to review its output less often, even though agents can – and do! – produce slop. Mario advises being far more sceptical with agents, and cautions that the quality of their output isn’t guaranteed, however well they performed previously.

Gergely Orosz

173,334 次观看 • 5 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

. 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

42,542 次观看 • 1 年前

Why Trump is pissed at Jamie Dimon (and sued $JPM for $5 million) Listen to the full episode of "Risk and Return" with Bob Sloan and I on your favorite platform YouTube: Spotify: Apple: Brought to you by S3 Partners

Why Trump is pissed at Jamie Dimon (and sued $JPM for $5 million) Listen to the full episode of "Risk and Return" with Bob Sloan and I on your favorite platform YouTube: Spotify: Apple: Brought to you by S3 Partners

Charles Gasparino

10,685 次观看 • 8 个月前

Hear from one of our oldest volunteers as they share unforgettable memories of the first ever Mahashivratri celebration at Isha! The night of 26 February 2025 can be the most exuberant and transformative night of your year! Join us on 26 February from 6 PM to 6 AM IST to celebrate Mahashivratri – the most spiritually potent night of the year. The celebrations include performances by musical and dance performances by renowned artists, explosive meditations, Sadhguru's discourse and more. For the first time ever, get initiated into the Mahamantra at Midnight by Sadhguru. Join the celebration in person or online. Join live:

Hear from one of our oldest volunteers as they share unforgettable memories of the first ever Mahashivratri celebration at Isha! The night of 26 February 2025 can be the most exuberant and transformative night of your year! Join us on 26 February from 6 PM to 6 AM IST to celebrate Mahashivratri – the most spiritually potent night of the year. The celebrations include performances by musical and dance performances by renowned artists, explosive meditations, Sadhguru's discourse and more. For the first time ever, get initiated into the Mahamantra at Midnight by Sadhguru. Join the celebration in person or online. Join live:

Isha Foundation

16,182 次观看 • 1 年前

#WATCH | Delhi | On the protest by the Indian Youth Congress at the India AI Impact Summit, Union Minister Ashwini Vaishnaw says, "...They might have gotten scared as to how such a grand AI summit is being organised...This is the time when we should keep the summit above politics and everybody cooperates with this effort...The Congress only want to create obstacles in everything and only God can save them..."

#WATCH | Delhi | On the protest by the Indian Youth Congress at the India AI Impact Summit, Union Minister Ashwini Vaishnaw says, "...They might have gotten scared as to how such a grand AI summit is being organised...This is the time when we should keep the summit above politics and everybody cooperates with this effort...The Congress only want to create obstacles in everything and only God can save them..."

ANI

19,717 次观看 • 7 个月前