Fascinating reading if you care about system design. Who would imagine this charged the world.

https://info.cern.ch/hypertext/WWW/DesignIssues/Overview.htm...

I am watching ACM A.M. Turing Award Laureate Interviews to set the perspective.

https://www.youtube.com/playlist?list=PLn0nrSd4xjjaSLBSzmno-...

For example:

Allen Newell, 1975 ACM A. M. Turing Award Recipient: “Desires and Diversions”

https://www.youtube.com/watch?v=hCe0ZPGap_k

Wisdom from the previous AI era.

I watched this YouTube video

Two decades of Git: A conversation with creator Linus Torvalds

https://www.youtube.com/watch?v=sCr_gb8rdEI

I was surprised that he only spent four months on it as a maintainer. What a great piece of work by a great software developer.

I am not at lecture 9 yet. I would love to follow their journey at human pace just like I did 30 years ago.

I do think your point is valid. The trend in the industry is putting emphasis on cosmetic qualities (format, workflow, testing), producing huge amount of metadata that consumes huge amount of human and machine energy for the peace of mind.

Complexity, maintainability, modularity have more to do with thinking about the problems at proper abstraction levels.

It seems we ended up spending more time on tools like writers spending more time on sharpening pencils or playing with fonts than writing something meaningful.

A low quality software can have beautiful code just like a low quality book has beautiful fonts.

When I was a Physics Ph.D. student in NYU in the late nineties, I took a course called UNIX tools in the CS department. It was a hands on course where the instructor did live REPL in the terminal and we watched him showing us all the tricks. I got hooked with UNIX since then. Got myself a dialup terminal in my tiny apartment in east village and dial in to the workstation on campus. The latency is so bad that I can’t only see the feedback after a few keystrokes. That was when I trained my vi muscle memory. (EMacs was out of the question.)

Later I got my own IBM 386 and installed Linux on it and started to program in Perl …

I am a big fan of Jon’s YouTube videos on Rust and I started to use Rust in non conventional ways.

I am going to follow this lecture series and “port” them to rustdoc and see how it goes.

Another rabbit hole to fall down, it is going to be fun.

https://ontouchstart.github.io/rabbit-holes/missing/

I have played with both mlx-lm and llama.cpp after I bought a 24GB M5 MacBook Pro last year.

Then I fell down the rabbit holes of uv, rust and C++ and forgot about LLMs. Today after I saw this announcement and answered someone’s question about how to set it up, when I got home, I decided play with llama.cpp again.

I was surprised and impressed:

https://ontouchstart.github.io/rabbit-holes/llama.cpp/

I am not going to use mlx-lm or lmstudio anymore. llama.cpp is so much fun.

Attention feeds attention.

Attention is ALL You Need.

This is the easiest set up on a Mac. You need at least 16gb on a MacBook:

https://github.com/ggml-org/llama.cpp/discussions/15396

This topic is very relevant in the age of agentic AI when every decision is a statistical next token prediction “trained” on some loss function. AGENT.md, SOUL.md etc are just smoke and mirrors of The Wizard of the Oz.

Eventually manager as a profession will be replaced by tools, just like computer as a profession, editor as a profession.

The evolution of computer science will be manager science. There is more than loss function and KPI.

Are technical/scientific books from pre-1925 particularly useful for self-learning today? I'd imagine for most disciplines, the knowledge has progressed and possibly changed course since then and it may be more outdated than not.

It might depend on the topic. Classical mechanics? I'm not sure that there is any fundamentally new knowledge since 1925 in that field. What's different is that people have 100 more years of figuring out how to explain it well.