Uploaded August 2026 | Updated September 2026, 2 weeks ago

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This interview was recorded for the GOTO Book Club. #GOTOcon #GOTObookclub
http://gotopia.tech/bookclub

Check out more here:
https://gotopia.tech/articles/452

Jim Ledin - President at Ledin Engineering & Author of “Modern Computer Architecture and Organization” @jledin1
Maciej «MJ» Jedrzejewski - Tech Agnostic Architect & Author of “Master Software Architecture” @learnsoftwarearchitecture

RESOURCES
Jim
linkedin.com/in/jimledin
https://x.com/ledin_eng
github.com/jledin
ledin.com

MJ
github.com/meaboutsoftware
linkedin.com/in/jedrzejewski-maciej
fractionalarchitect.io

Links
youtu.be/wNT2qkusVrA
youtu.be/Pv0cfsastFs
youtu.be/cI9dfQLTXlU
youtu.be/a2DvXnecXVk

DESCRIPTION
Jim Ledin — author of Modern Computer Architecture and Organization, now in its third edition — joins Maciej "MJ" Jedrzejewski to talk through the book's two brand-new chapters on GPUs and large language models, and the specific challenge of writing about hardware that changes faster than a book can ship. Ledin's approach was to focus on durable architectural principles (parallelism, memory bandwidth, tensor processing, and how systems scale from one chip to an entire data center rack) rather than chasing the current state of the art. For the LLM chapter specifically, he chose GPT-2 as the teaching example precisely because it's open-source and small enough to trace by hand — and because, as he explains, the transformer architecture underneath today's frontier models is fundamentally the same structure, just scaled up.

The most concrete takeaway for engineers: the AI buildout's real bottleneck right now isn't compute, it's memory bandwidth — a shift driving high-bandwidth memory production at the expense of consumer RAM, which Ledin illustrates with a blunt data point (a 32GB DDR5 stick that cost $69 a year ago now runs $440). But asked which single chapter would most change how a working developer with no hardware background thinks about their own code, Ledin doesn't point to AI at all — he points to the chapter on pipelining and cache hierarchy, arguing that most of the thousandfold speedup from 1980s PCs to today came from those optimizations, not clock speed, and that writing cache- and pipeline-friendly code is still one of the highest-leverage skills a developer can have.

TIMECODES
00:00 Intro
00:47 The Commodore 64 that started it all
04:36 Two new chapters: GPUs & LLMs
10:00 Why GPUs became AI hardware by accident
13:33 Training vs Inference: Same chip, different job
15:03 Why GPT-2, not GPT-5, is the best teacher
17:37 The data center is the computer now
18:41 The real AI bottleneck nobody's talking about
21:59 The one chapter every developer should read
25:43 Outro

RECOMMENDED BOOKS
Jim Ledin • Modern Computer Architecture and Organization • amzn.to/4wHMhQN
Jim Ledin • Architecting High-Performance Embedded Systems • amzn.to/3UpXl7z
Jim Ledin • Simulation Engineering • amzn.to/4qvylYQ
Maciej «MJ» Jedrzejewski • Master Software Architecture • leanpub.com/master-software-architecture

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