Avsnitt
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In today’s episode of The Pragmatic Engineer, I’m joined by Irina Stanescu, a seasoned engineer with over 14 years in software engineering and engineering leadership roles at tech companies like Google and Uber. Now an engineering leadership coach, Irina helps tech professionals build impactful careers, teaches a course on influence, and shares insights through her newsletter, The Caring Techie. In our conversation today, Irina shares her journey of rising through the ranks at Google and Uber. We dive into the 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
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In this episode, we cover:
(01:34) Irina’s time at Google
(03:10) An overview of ‘design docs’ at Google
(08:27) The readiness review at Google
(10:40) Why Irina uses spreadsheets
(11:44) Irina’s favorite tools and how she uses them
(13:46) How Google certifies readability
(15:40) Google’s meme generator
(17:36) Advice for engineers thinking about working for an organization like Google
(20:14) How promotions work at Google
(23:15) How Irina worked towards getting promoted
(27:50) How Irina got her first mentor
(30:44) Organizational shifts at Uber while Irina and Gergely were there
(35:50) Why you should prioritize growth over promotion
(36:50) What a career plan is and how to build one
(40:40) Irina’s current role coaching engineers
(42:23) A simple explanation of influence and influencing
(51:54) Why saying no is necessary at times
(54:30) The importance of building leadership skills
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The Pragmatic Engineer deepdives relevant for this episode:
• Preparing for promotions ahead of time: https://newsletter.pragmaticengineer.com/p/preparing-for-promotions
• Engineering career paths at Big Tech and scaleups: https://newsletter.pragmaticengineer.com/p/engineering-career-paths
• Getting an Engineering Executive Job: https://newsletter.pragmaticengineer.com/p/getting-an-engineering-executive
• The Seniority Rollercoaster: https://newsletter.pragmaticengineer.com/p/the-seniority-rollercoaster
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Where to find Irina Stanescu:
• X: https://x.com/thecaringtechie
• LinkedIn: https://www.linkedin.com/in/irinastanescu/
• Website: https://www.thecaringtechie.com/
• Maven course: Impact through Influence in Engineering Teams: https://maven.com/irina-stanescu/influence-swe
Where to find Gergely:
• Newsletter: https://www.pragmaticengineer.com/
• YouTube: https://www.youtube.com/c/mrgergelyorosz
• LinkedIn: https://www.linkedin.com/in/gergelyorosz/
• X: https://x.com/GergelyOrosz
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References and Transcripts:
See the transcript and other references from the episode at https://newsletter.pragmaticengineer.com/podcast
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe -
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• ByteByteGo — Ace your next system design interview.
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You may not be familiar with Bending Spoons, but I guarantee you’ve encountered some of their well-known products, like Evernote and Meetup. In today’s episode of The Pragmatic Engineer, we sit down with three key figures from the Italy-based startup: cofounder and CEO Luca Ferrari, CTO Francesco Mancone, and Evernote product lead Federico Simionato. Bending Spoons has been profitable from day one, and there's plenty we can learn from their unique culture, organizational structure, engineering processes, and hiring practices. In today’s conversation, we cover the following topics:
• The controversial acquisitions approach of Bending Spoons
• How Bending Spoons spent more than $1 billion in buying tech companies
• How the Evernote acquisition happened
• How Bending Spoons operates and how it organizes product and platform teams
• Why engineering processes are different across different products
• How ‘radical simplicity’ is baked into everything from engineering processes to pay structure.
• And much more!
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The Pragmatic Engineer deepdives relevant for this episode:
• Good attrition, bad attrition for software engineers: https://newsletter.pragmaticengineer.com/p/attrition
• Healthy oncall practices: https://newsletter.pragmaticengineer.com/p/healthy-oncall-practices • Shipping to production: https://newsletter.pragmaticengineer.com/p/shipping-to-production
• QA across the tech industry: https://newsletter.pragmaticengineer.com/p/qa-across-tech
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In this episode, we cover:
(2:09) Welcome, Luca, Francesco, and Federico from Bending Spoons
(03:15) An overview of the well-known apps and products owned by Bending Spoons
(06:38) The elephant in the room: how Bending Spoons really acquires companies
(09:46) Layoffs: Bending Spoons’ philosophy on this
(14:10) Controversial principles
(17:16) Revenue, team size, and products
(19:35) How Bending Spoons runs AI products and allocates GPUs
(23:05) History of the company
(27:04) The Evernote acquisition
(29:50) Modernizing Evernote’s infrastructure
(32:44) “Radical simplicity” and why they try for zero on calls
(36:13) More on changes made to the Evernote systems
(41:13) How Bending Spoons prioritizes and ships fast
(49:40) What’s new and what’s coming for Bending Spoons
(51:08) Organizational structure at the company
(54:07) Engineering practices
(57:03) Testing approaches
(58:53) Platform teams
(1:01:52) Bending Spoons tech stack and popular frameworks
(1:05:55) Why Bending Spoons hires new grads and less experienced engineers
(1:08:09) The structure of careers and titles at Bending Spoons
(1:09:50) Traits they look for when hiring
(1:12:50) Why there aren’t many companies doing what Bending Spoons does
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Where to find Luca Ferrari:
• X: https://x.com/luke10ferrari
• LinkedIn: https://www.linkedin.com/in/luca-ferrari-12418318
Where to find Francesco Mancone:
• LinkedIn: https://www.linkedin.com/in/francesco-mancone
Where to find Federico Simionato:
• X: https://x.com/fedesimio
• LinkedIn: https://www.linkedin.com/in/federicosimionato
Where to find Gergely:
• Newsletter: https://www.pragmaticengineer.com/
• YouTube: https://www.youtube.com/c/mrgergelyorosz
• LinkedIn: https://www.linkedin.com/in/gergelyorosz/
• X: https://x.com/GergelyOrosz
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References and Transcripts:
See the transcript and other references from the episode at https://newsletter.pragmaticengineer.com/podcast
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe -
Saknas det avsnitt?
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On today’s episode of The Pragmatic Engineer, I’m joined by Quinn Slack, CEO and co-founder of Sourcegraph, a leading code search and intelligence platform. Quinn holds a degree in Computer Science from Stanford and is deeply passionate about coding: to the point that he still codes every day! He also serves on the board of Hack Club, a national nonprofit dedicated to bringing coding clubs to high schools nationwide. In this insightful conversation, we discuss:
• How Sourcegraph's operations have evolved since 2021
• Why more software engineers should focus on delivering business value
• Why Quinn continues to code every day, even as a CEO
• Practical AI and LLM use cases and a phased approach to their adoption
• The story behind Job Fairs at Sourcegraph and why it’s no longer in use
• Quinn’s leadership style and his focus on customers and product excellence
• The shift from location-independent pay to zone-based pay at Sourcegraph
• And much more!
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Where to find Quinn Slack:
• X: https://x.com/sqs
• LinkedIn: https://www.linkedin.com/in/quinnslack/
• Website: https://slack.org/
Where to find Gergely:
• Newsletter: https://www.pragmaticengineer.com/
• YouTube: https://www.youtube.com/c/mrgergelyorosz
• LinkedIn: https://www.linkedin.com/in/gergelyorosz/
• X: https://x.com/GergelyOrosz
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In this episode, we cover:
(01:35) How Sourcegraph started and how it has evolved over the past 11 years
(04:14) How scale-ups have changed
(08:27) Learnings from 2021 and how Sourcegraph’s operations have streamlined
(15:22) Why Quinn is for gradual increases in automation and other thoughts on AI
(18:10) The importance of changelogs
(19:14) Keeping AI accountable and possible future use cases
(22:29) Current limitations of AI
(25:08) Why early adopters of AI coding tools have an advantage
(27:38) Why AI is not yet capable of understanding existing codebases
(31:53) Changes at Sourcegraph since the deep dive on The Pragmatic Engineer blog
(40:14) The importance of transparency and understanding the different forms of compensation
(40:22) Why Sourcegraph shifted to zone-based pay
(47:15) The journey from engineer to CEO
(53:28) A comparison of a typical week 11 years ago vs. now
(59:20) Rapid fire round
The Pragmatic Engineer deepdives relevant for this episode:
• Inside Sourcegraph’s engineering culture: Part 1 https://newsletter.pragmaticengineer.com/p/inside-sourcegraphs-engineering-culture• Inside Sourcegraph’s engineering culture: Part 2 https://newsletter.pragmaticengineer.com/p/inside-sourcegraphs-engineering-culture-part-2
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References and Transcript:
See the transcript and other references from the episode at https://newsletter.pragmaticengineer.com/podcast
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe -
The first episode of The Pragmatic Engineer Podcast is out. Expect similar episodes every other Wednesday. You can add the podcast in your favorite podcast player, and have future episodes downloaded automatically.
Listen now on Apple, Spotify, and YouTube.
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On the first episode of the Pragmatic Engineer Podcast, I am joined by Simon Willison.
Simon is one of the best-known software engineers experimenting with LLMs to boost his own productivity: he’s been doing this for more than three years, blogging about it in the open.
Simon is the creator of Datasette, an open-source tool for exploring and publishing data. He works full-time developing open-source tools for data journalism, centered on Datasette and SQLite. Previously, he was an engineering director at Eventbrite, joining through the acquisition of Lanyrd, a Y Combinator startup he co-founded in 2010. Simon is also a co-creator of the Django Web Framework. He has been blogging about web development since the early 2000s.
In today’s conversation, we dive deep into the realm of Gen AI and talk about the following:
• Simon’s initial experiments with LLMs and coding tools
• Why fine-tuning is generally a waste of time—and when it’s not
• RAG: an overview
• Interacting with GPTs voice mode
• Simon’s day-to-day LLM stack
• Common misconceptions about LLMs and ethical gray areas
• How Simon’s productivity has increased and his generally optimistic view on these tools
• Tips, tricks, and hacks for interacting with GenAI tools
• And more!
I hope you enjoy this episode.
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In this episode, we cover:
(02:15) Welcome
(05:28) Simon’s ‘scary’ experience with ChatGPT
(10:58) Simon’s initial experiments with LLMs and coding tools
(12:21) The languages that LLMs excel at
(14:50) To start LLMs by understanding the theory, or by playing around?
(16:35) Fine-tuning: what it is, and why it’s mostly a waste of time
(18:03) Where fine-tuning works
(18:31) RAG: an explanation
(21:34) The expense of running testing on AI
(23:15) Simon’s current AI stack
(29:55) Common misconceptions about using LLM tools
(30:09) Simon’s stack – continued
(32:51) Learnings from running local models
(33:56) The impact of Firebug and the introduction of open-source
(39:42) How Simon’s productivity has increased using LLM tools
(41:55) Why most people should limit themselves to 3-4 programming languages
(45:18) Addressing ethical issues and resistance to using generative AI
(49:11) Are LLMs are plateauing? Is AGI overhyped?
(55:45) Coding vs. professional coding, looking ahead
(57:27) The importance of systems thinking for software engineers
(1:01:00) Simon’s advice for experienced engineers
(1:06:29) Rapid-fire questions
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Where to find Simon Willison:
• X: https://x.com/simonw
• LinkedIn: https://www.linkedin.com/in/simonwillison/
• Website: https://simonwillison.net/
• Mastodon: https://fedi.simonwillison.net/@simon
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Referenced:
• Simon’s LLM project: https://github.com/simonw/llm
• Jeremy Howard’s Fast Ai: https://www.fast.ai/
• jq programming language: https://en.wikipedia.org/wiki/Jq_(programming_language)
• Datasette: https://datasette.io/
• GPT Code Interpreter: https://platform.openai.com/docs/assistants/tools/code-interpreter
• Open Ai Playground: https://platform.openai.com/playground/chat
• Advent of Code: https://adventofcode.com/
• Rust programming language: https://www.rust-lang.org/
• Applied AI Software Engineering: RAG: https://newsletter.pragmaticengineer.com/p/rag
• Claude: https://claude.ai/
• Claude 3.5 sonnet: https://www.anthropic.com/news/claude-3-5-sonnet
• ChatGPT can now see, hear, and speak: https://openai.com/index/chatgpt-can-now-see-hear-and-speak/
• GitHub Copilot: https://github.com/features/copilot
• What are Artifacts and how do I use them?: https://support.anthropic.com/en/articles/9487310-what-are-artifacts-and-how-do-i-use-them
• Large Language Models on the command line: https://simonwillison.net/2024/Jun/17/cli-language-models/
• Llama: https://www.llama.com/
• MLC chat on the app store: https://apps.apple.com/us/app/mlc-chat/id6448482937
• Firebug: https://en.wikipedia.org/wiki/Firebug_(software)#
• NPM: https://www.npmjs.com/
• Django: https://www.djangoproject.com/
• Sourceforge: https://sourceforge.net/
• CPAN: https://www.cpan.org/
• OOP: https://en.wikipedia.org/wiki/Object-oriented_programming
• Prolog: https://en.wikipedia.org/wiki/Prolog
• SML: https://en.wikipedia.org/wiki/Standard_ML
• Stabile Diffusion: https://stability.ai/
• Chain of thought prompting: https://www.promptingguide.ai/techniques/cot
• Cognition AI: https://www.cognition.ai/
• In the Race to Artificial General Intelligence, Where’s the Finish Line?: https://www.scientificamerican.com/article/what-does-artificial-general-intelligence-actually-mean/
• Black swan theory: https://en.wikipedia.org/wiki/Black_swan_theory
• Copilot workspace: https://githubnext.com/projects/copilot-workspace
• Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems: https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321
• Bluesky Global: https://www.blueskyglobal.org/
• The Atrocity Archives (Laundry Files #1): https://www.amazon.com/Atrocity-Archives-Laundry-Files/dp/0441013651
• Rivers of London: https://www.amazon.com/Rivers-London-Ben-Aaronovitch/dp/1625676158/
• Vanilla JavaScript: http://vanilla-js.com/
• jQuery: https://jquery.com/
• Fly.io: https://fly.io/
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe -
Welcome to The Pragmatic Engineer Podcast, hosted by Gergely Orosz, the author of The Pragmatic Engineer newsletter. In each episode, we dive deep into the world of software engineering, offering practical insights on scaling teams, engineering leadership, and navigating the evolving tech landscape. With industry veterans and successful engineers as guests, this podcast is perfect for anyone looking to level up their engineering career with real-world advice.
Subscribe to the podcast on YouTube, on Spotify, or Apple.
You can also subscribe to the newsletter here.
Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe
