Developers are increasingly relying on AI coding assistants to accelerate our daily workflows. These tools can autocomplete functions, suggest bug fixes, and even generate entire modules or MVPs. Yet, as many of us have learned, the quality of the AI’s output depends largely on the quality of the prompt you provide. In other words, prompt engineering has become an essential skill. A poorly phrased
This post is about why we need a coroutine package for Go, and what it would look like. But first, what are coroutines? Every programmer today is familiar with function calls (subroutines): F calls G, which stops F and runs G. G does its work, potentially calling and waiting for other functions, and eventually returns. When G returns, G is gone and F continues running. In this pattern, only one fu
A few months ago, I set myself the challenge of writing a C compiler in 500 lines of Python1, after writing my SDF donut post. How hard could it be? The answer was, pretty hard, even when dropping quite a few features. But it was also pretty interesting, and the result is surprisingly functional and not too hard to understand! There's too much code for me to comprehensively cover in a single blog
Lessons from Writing a Compiler
The prototypical compilers textbook is: 600 pages on parsing theory. Three pages of type-checking a first-order type system like C. Zero pages on storing and checking the correctness of declarations (the “symbol table”). Zero pages on the compilation model, and efficiently implementing separate compilation. 450 pages on optimization and code generation. The standard academic literature is most use
Rewriting the Ruby parser
At Shopify, we have spent the last year writing a new Ruby parser, which we’ve called YARP (Yet Another Ruby Parser). As of the date of this post, YARP can parse a semantically equivalent syntax tree to Ruby 3.3 on every Ruby file in Shopify’s main codebase, GitHub’s main codebase, CRuby, and the 100 most popular gems downloaded from rubygems.org. We recently got approval to merge this work into C
4 Pandas Anti-Patterns to Avoid and How to Fix Them
pandas is a powerful data analysis library with a rich API that offers multiple ways to perform any given data manipulation task. Some of these approaches are better than others, and pandas users often learn suboptimal coding practices that become their default workflows. This post highlights four common pandas anti-patterns and outlines a complementary set of techniques that you should use instea
Update 1.69.1: The update addresses these issues. Update 1.69.2: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the June 2022 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: 3-way merge editor - Resolve merge conflicts wit
Golang Mini Reference 2022: A Quick Guide to the Modern Go Programming Language (REVIEW COPY)
Golang Mini Reference 2022 A Quick Guide to the Modern Go Programming Language (REVIEW COPY) Harry Yoon Version 0.9.0, 2022-08-24 REVIEW COPY This is review copy, not to be shared or distributed to others. Please forward any feedback or comments to the author. • feedback@codingbookspress.com The book is tentatively scheduled to be published on September 14th, 2022. We hope that when the release da
How I developed a faster Ruby interpreter | Red Hat Developer
In this article, I will describe my efforts to implement a faster interpreter for CRuby, the Ruby language interpreter, using a dynamically specialized internal representation (IR). I believe this article will interest developers trying to improve the interpreter performance of dynamic programming languages (e.g., CPython developers). I will cover the following topics: Existing CRuby interpreter a
Over the course of my Spring 2020 semester at Harvey Mudd College, I developed a self-hosting compiler entirely from scratch. This article walks through many interesting parts of the project. It’s laid out so you can just read from beginning to end, but if you’re more interested in a particular topic, feel free to jump there. Or, take a look at the project on GitHub. Table of contents What the pro
Shai Hulud Strikes Again (v2)Another wave of Shai-Hulud campaign has hit npm with more than 500 packages and 700+ versions affected. Update: November 26, 2025 PostHog has published a detailed post mortem describing how one of its GitHub Actions workflows was abused as an initial access vector for Shai Hulud v2. An attacker briefly opened a pull request that modified a script executed via pull_requ
We now live in a world where ML workflows (pre-training, post training, etc) are heterogeneous, must contend with hardware failures, are increasingly asynchronous and highly dynamic. Traditionally, PyTorch has relied on an HPC-style multi-controller model, where multiple copies of the same script are launched across different machines, each running its own instance of the application (often refer
This article is a translation, the original version is available here. I started using the OCaml language regularly around 2012, and since then, my interest and enthusiasm for this language have only grown. It has become my preferred choice for almost all my personal projects, and it has also influenced my professional choices. Since 2014, I have been actively participating in public conferences d
Mojo vision | Modular
Our vision for Mojo is to be the one programming language developers need to target diverse hardware—CPUs, GPUs, and other accelerators—using Python's intuitive syntax combined with modern systems programming capabilities. Although this vision focuses on the Mojo language, we recognize it's just one part of a larger Mojo ecosystem. When combined, the developer tools, the community, and the landsca
Introduction: Density Is King (With a Tiny VM) I've previously come to the conclusion that there's little reason for using bytecode in the modern world, except in order to get more compact code, for which it can be very effective. So, what kind of a bytecode engine will give you more compact code? Suppose I want a bytecode interpreter for a very small programming environment, specifically to minim
Right now, asyncio is one of the trendier topics in Python, and rightfully so – It’s a great way to handle I/O-bound programs! When I was learning about asyncio, It took me a while to understand how it actually worked. But later, I came to find out that it’s basically just a really nice layer on top of Python Generators. In this article, I’m going to create a simplified version of asyncio using ju
C interpreters are a common language implementation technique and the basis for the reference implementations of languages such as Lua, Ruby, and Python. Unfortunately, C interpreters are slow, especially compared to language implementations powered by JIT compilers. In this post I’m going to show that it is possible to take C interpreters and, by changing a tiny proportion of code, automatically
An AI-native software engineer is one who deeply integrates AI into their daily workflow, treating it as a partner to amplify their abilities. This requires a fundamental mindset shift. Instead of thinking “AI might replace me” an AI-native engineer asks for every task: “Could AI help me do this faster, better, or differently?”. The mindset is optimistic and proactive - you see AI as a multiplier
After studying how companies deploy generative AI applications, I noticed many similarities in their platforms. This post outlines the common components of a generative AI platform, what they do, and how they are implemented. I try my best to keep the architecture general, but certain applications might deviate. This is what the overall architecture looks like. This is a pretty complex system. Thi
Why APL is a language worth knowing
“A language that doesn't affect the way you think about programming, is not worth knowing.”, by Alan J. Perlis. Why APL is a language worth knowing Alan Perlis, the computer scientist recipient of the first Turing award, wrote “A language that doesn't affect the way you think about programming, is not worth knowing.” ― Alan J. Perlis, 1982. Special feature: Epigrams on programming. ACM Sigplan Not
LambdaLisp - A Lisp Interpreter That Runs on Lambda Calculus
LambdaLisp is a Lisp interpreter written as an untyped lambda calculus term. The input and output text is encoded into closed lambda terms using the Mogensen-Scott encoding, so the entire computation process solely consists of the beta-reduction of lambda calculus terms. When run on a lambda calculus interpreter that runs on the terminal, it presents a REPL where you can interactively define and e
Screencast If you click on this screenshot, you'll see OSH running ./configure from CPython's tarball, with GC debug output. This is: 16K lines of gnarly shell generated by GNU autoconf Running in our shell interpreter, written in ~40K lines of typed Python. But, it's translated to ~80K lines of pure C++! That generated C++ runs on top of a ~4K line runtime of garbage collected data structures, an
Python behind the scenes #12: how async/await works in Python
Mark functions as async. Call them with await. All of a sudden, your program becomes asynchronous – it can do useful things while it waits for other things, such as I/O operations, to complete. Code written in the async/await style looks like regular synchronous code but works very differently. To understand how it works, one should be familiar with many non-trivial concepts including concurrency,
Python Interview Questions
Here is a list of common Python interview questions with detailed answers to help you prepare for the interview as a Python developer. Python, with its versatile use cases and straightforward syntax, has seen its popularity growing continuously in software development, data science, artificial intelligence, and many other fields. As such, interviews for Python-related positions are designed not on
Sketch of a Post-ORM
I’ve been writing a lot of database access code as of late. It’s frustrating that in 2023, my choices are still to either write all of the boilerplate by hand, or hand all database access over to some inscrutable “agile” ORM that will become a crippling liability in the 2-3y timescale. This post is about how I want to use databases, from the perspective of an application server developer—not a DBA
Performance of Python programs has been a major focus of development for the language over the last five years or so; the Faster CPython project has been a big part of that effort. One of its subprojects is to add an experimental just-in-time (JIT) compiler to the language; at last year's PyCon US, project member Brandt Bucher gave an introduction to the copy-and-patch JIT compiler. At PyCon US 20
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models Qizheng Zhang 1∗ Changran Hu 2∗ Shubhangi Upasani 2 Boyuan Ma 2 Fenglu Hong 2 Vamsidhar Kamanuru 2 Jay Rainton 2 Chen Wu 2 Mengmeng Ji 2 Hanchen Li 3 Urmish Thakker 2 James Zou 1 Kunle Olukotun 1 1 Stanford University 2 SambaNova Systems, Inc. 3 UC Berkeley ∗ equal contribution # qizhengz@stanford.edu, changran.hu@sa
GitHub - ComfyUI-Workflow/awesome-comfyui: A collection of awesome custom nodes for ComfyUI
ComfyUI-Gemini_Flash_2.0_Exp (⭐+172): A ComfyUI custom node that integrates Google's Gemini Flash 2.0 Experimental model, enabling multimodal analysis of text, images, video frames, and audio directly within ComfyUI workflows. ComfyUI-ACE_Plus (⭐+115): Custom nodes for various visual generation and editing tasks using ACE_Plus FFT Model. ComfyUI-Manager (⭐+113): ComfyUI-Manager itself is also a cu
[Simon Tatham, initial version 2023-09-01, last updated 2025-03-25] [Coroutines trilogy: C preprocessor | C++20 native | general philosophy ] Introduction Why I’m so enthusiastic about coroutines The objective view: what makes them useful? Versus explicit state machines Versus conventional threads The subjective view: why do I like them so much? “Teach the student when the student is ready” They s
Paul: Today’s spotlight: Paolo Perrone, master of turning tech into scroll-stopping content. This one’s packed, let’s go 👀 ↓ I’m going to be honest with you. Most AI agent tutorials are garbage. They show you how to copy-paste LangChain code, build a demo that breaks the moment you try anything real, and leave you feeling like you learned something. Three months later, you try to build something
Reflection Agents
Reflection Agents Reflection is a prompting strategy used to improve the quality and success rate of agents and similar AI systems. This post outlines how to build 3 reflection techniques using LangGraph, including implementations of Reflexion and Language Agent Tree Search. Key LinksSimple Reflection: (Python)Reflexion: (Python)Language Agents Tree Search: (Python)YoutubeReflection is a prompting
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The Prompt Engineering Playbook for Programmers
research!rsc: Coroutines for Go
Writing a C compiler in 500 lines of Python
June 2022 (version 1.69)
Kalyn: a self-hosting compiler for x86-64
Shai Hulud Strikes Again (v2) - Socket
Introducing PyTorch Monarch – PyTorch
xvw.lol - Why I chose OCaml as my primary language
bytecode interpreters for tiny computers ⁑ Dercuano
How Python Asyncio Works: Recreating it from Scratch
Laurence Tratt: Retrofitting JIT Compilers into C Interpreters
The AI-Native Software Engineer
Building A Generative AI Platform
Pictures of a Working Garbage Collector
Following up on the Python JIT
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Philosophy of coroutines
The Realistic Guide to Mastering AI Agents in 2026