Prompting Is Programming(brethorsting.com)

5 points by aaronbrethorst 10 days ago | 0 comments

Blog post by Aaron Brethorst arguing that prompting an AI well is essentially programming, explaining why engineers get more value from LLMs than non-programmers.

Introduction to Programming Languages(hjaem.info)

54 points by parksb 1 year ago | 10 comments

AP5 - Declarative Programming Library For Common Lisp (1995)(oceanpark.com)

49 points by contrapunctus 2 years ago | 2 comments

HTML, the Programming Language(html-lang.org)

266 points by recursivedoubts 2 years ago | 126 comments

Emacs in the Age of Magic(commandlinesystems.com)

289 points by ggcr 2 days ago | 131 comments

A plain-text essay reflecting on Emacs culture after AI coding tools like Claude Code, with case studies of AI-built packages excali-mode.el and cooked.el.

The ABC Programming Language(homepages.cwi.nl)

55 points by TheFreim 1 year ago | 6 comments

Competitive Programmer's Handbook (2018) [pdf](cses.fi)

302 points by vinhnx 1 month ago | 79 comments

PDF of the Competitive Programmer's Handbook by Antti Laaksonen (July 2018 draft), a free book on algorithms for programming contests.

A hacker's guide to language models [video](youtube.com)

749 points by rrampage 3 years ago | 35 comments

YouTube video by Jeremy Howard titled "A Hackers' Guide to Language Models," a code-first introduction to using and understanding LLMs.

Advanced coding in low-resource programming languages(openai.com)

79 points by sumnole 24 days ago | 102 comments

OpenAI research publication on improving its models' coding abilities in low-resource programming languages like COBOL, Fortran, OCaml, and Visual Basic.

The Linux Kernel Module Programming Guide(sysprog21.github.io)

340 points by asicsp 3 years ago | 26 comments

Online edition of The Linux Kernel Module Programming Guide by Salzman, Burian, Pomerantz, Mottram and Huang, with GitHub source and PDF download.

Context Language Models(arxiv.org)

164 points by emersonmacro 1 month ago | 44 comments

arXiv paper introducing Context Language Models, LLMs that natively manage their own context by treating it as an editable file, with benchmarks on agent tasks.

Understanding Machine Learning: From Theory to Algorithms(cs.huji.ac.il)

407 points by Anon84 1 year ago | 51 comments

Link to the free online copy of the textbook Understanding Machine Learning: From Theory to Algorithms; the page loaded as a security-block error.