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The Pragmatic Engineer

The Pragmatic Engineer

Written by: Gergely Orosz
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Software engineering at Big Tech and startups, from the inside. Deepdives with experienced engineers and tech professionals who share their hard-earned lessons, interesting stories and advice they have on building software. Especially relevant for software engineers and engineering leaders: useful for those working in tech.

newsletter.pragmaticengineer.comGergely Orosz
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Episodes
  • How AWS S3 is built
    Jan 21 2026
    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.—Amazon S3 is one of the largest distributed systems ever built, storing and serving data for a significant portion of the internet. Behind its simple interfaces hides an enormous amount of engineering work, careful tradeoffs, and long-term thinking.In this episode, I sit down with Mai-Lan Tomsen Bukovec, VP of Data and Analytics at AWS, who has been running Amazon S3 for more than a decade. Mai-Lan shares how S3 operates at extreme scale, what it takes to design for durability and availability across millions of servers, and why building for failure is a core principle.We also go deep into how AWS approaches correctness using formal methods, how storage tiers and limits shape system design, and why simplicity remains one of the hardest and most important goals at S3’s scale.—Timestamps(00:00) Intro(01:03) S3’s scale (03:58) How S3 started (07:25) Parquet, Iceberg, and S3 tables(09:46) S3 for developers (13:37) Why AWS keeps S3 prices low (17:10) AWS pricing tiers(19:38) Availability and durability (26:21) The cost of S3's consistency(31:22) Automated reasoning and proof of correctness (35:14) Durability at AWS scale(39:58) Correlated failure and crash consistency (43:22) Failure allowances (46:04) Two opposing principles in S3 design(49:09) S3’s evolution (52:21) S3 Vectors (1:01:16) The 50 TB limit on AWS(1:07:54) The simplicity principle(1:10:10) Types of engineers working on S3(1:14:15) Closing recommendations —The Pragmatic Engineer deepdives relevant for this episode:• Inside Amazon’s engineering culture• How AWS deals with a major outage• A Day in the Life of a Senior Manager at Amazon• What is a Principal Engineer at Amazon? – with Steve Huynh• Working at Amazon as a software engineer – with Dave AndersonAmazon papers recommended by Mai-Lan:• Using lightweight formal methods to validate a key-value storage node in Amazon S3• Formally verified cloud-scale authorization• Analyzing metastable failures• Amazon’s engineering tenets—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe
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    1 hr and 18 mins
  • The history of servers, the cloud, and what’s next – with Oxide
    Dec 17 2025

    Brought to You By:

    •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.

    •⁠ Linear ⁠ — ⁠ The system for modern product development.

    How have servers and the cloud evolved in the last 30 years, and what might be next? Bryan Cantrill was a distinguished engineer at Sun Microsystems during both the Dotcom Boom and the Dotcom Bust. Today, he is the co-founder and CTO of Oxide Computer, where he works on modern server infrastructure.

    In this episode of The Pragmatic Engineer, Bryan joins me to break down how modern computing infrastructure evolved. We discuss why the Dotcom Bust produced deeper innovation than the Boom, how constraints shape better systems, and what the rise of the cloud changed and did not change about building reliable infrastructure.

    Our conversation covers early web infrastructure at Sun, the emergence of AWS, Kubernetes and cloud neutrality, and the tradeoffs between renting cloud space and building your own. We also touch on the complexity of server-side software updates, experimenting with AI, the limits of large language models, and how engineering organizations scale without losing their values.

    If you want a systems-level perspective on computing that connects past cycles to today’s engineering decisions, this episode offers a rare long-range view.

    Timestamps

    (00:00) Intro

    (01:26) Computer science in the 1990s

    (03:01) Sun and Cisco’s web dominance

    (05:41) The Dotcom Boom

    (10:26) From Boom to Bust

    (15:32) The innovations of the Bust

    (17:50) The open source shift

    (22:00) Oracle moves into Sun’s orbit

    (24:54) AWS dominance (2010–2014)

    (28:15) How Kubernetes and cloud neutrality

    (30:58) Custom infrastructure

    (36:10) Renting the cloud vs. buying hardware

    (45:28) Designing a computer from first principles

    (50:02) Why everyone is paid the same salary at Oxide

    (54:14) Oxide’s software stack

    (58:33) The evolution of software updates

    (1:02:55) How Oxide uses AI

    (1:06:05) The limitations of LLMs

    (1:11:44) AI use and experimentation at Oxide

    (1:17:45) Oxide’s diverse teams

    (1:22:44) Remote work at Oxide

    (1:24:11) Scaling company values

    (1:27:36) AI’s impact on the future of engineering

    (1:31:04) Bryan’s advice for junior engineers

    (1:34:01) Book recommendations

    The Pragmatic Engineer deepdives relevant for this episode:

    • Startups on hard mode: Oxide. Part 1: Hardware

    • Startups on hard mode: Oxide, Part 2: Software & Culture

    • Three cloud providers, three outages: three different responses

    • Inside Uber’s move to the Cloud

    • Inside Agoda’s private Cloud

    Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com.



    Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe
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    1 hr and 39 mins
  • Being a founding engineer at an AI startup
    Dec 3 2025

    Brought to You By:

    •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.

    •⁠ Linear ⁠ — ⁠ The system for modern product development.

    Michelle Lim joined Warp as engineer number one and is now building her own startup, Flint. She brings a strong product-first mindset shaped by her time at Facebook, Slack, Robinhood, and Warp. Michelle shares why she chose Warp over safer offers, how she evaluates early-stage opportunities, and what she believes distinguishes great founding engineers.

    Together, we cover how product-first engineers create value, why negotiating equity at early-stage startups requires a different approach, and why asking founders for references is a smart move. Michelle also shares lessons from building consumer and infrastructure products, how she thinks about tech stack choices, and how engineers can increase their impact by taking on work outside their job descriptions.

    If you want to understand what founders look for in early engineers or how to grow into a founding-engineer role, this episode is full of practical advice backed by real examples

    Timestamps

    (00:00) Intro

    (01:32) How Michelle got into software engineering

    (03:30) Michelle’s internships

    (06:19) Learnings from Slack

    (08:48) Product learnings at Robinhood

    (12:47) Joining Warp as engineer #1

    (22:01) Negotiating equity

    (26:04) Asking founders for references

    (27:36) The top reference questions to ask

    (32:53) The evolution of Warp’s tech stack

    (35:38) Product-first engineering vs. code-first

    (38:27) Hiring product-first engineers

    (41:49) Different types of founding engineers

    (44:42) How Flint uses AI tools

    (45:31) Avoiding getting burned in founder exits

    (49:26) Hiring top talent

    (50:15) An overview of Flint

    (56:08) Advice for aspiring founding engineers

    (1:01:05) Rapid fire round

    The Pragmatic Engineer deepdives relevant for this episode:

    • Thriving as a founding engineer: lessons from the trenches

    • From software engineer to AI engineer

    • AI Engineering in the real world

    • The AI Engineering stack

    Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com.



    Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe
    Show More Show Less
    1 hr and 4 mins
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