The hottest Programming Substack posts right now

And their main takeaways
Category
Top Technology Topics

Functional Genie

Software Design: Tidy First? • 243 implied HN points • 08 Jun 25
🕹 Technology Programming Software Development Languages Engineering
  1. When coding in Rust, it can be tricky to use the right idioms, especially when dealing with functions that return an Option. It's good to pay attention to how you handle these results.
  2. In Rust, the common way to check for values is with an 'if' statement, which can take some getting used to if you're new to the language.
  3. Building a high-quality map implementation in Rust can be performance competitive, but learning the language and its features is essential for success.

What's In A List—Yes, But What's *Really* In A List

The Python Coding Stack • by Stephen Gruppetta • 259 implied HN points • 13 Oct 24
🕹 Technology Programming Data Structures Python Education Computing
  1. In Python, lists don't actually hold the items themselves but instead hold references to those items. This means you can change what is in a list without changing the list itself.
  2. If you create a list by multiplying an existing list, all the elements will reference the same object instead of creating separate objects. This can lead to unexpected results, like altering one element affecting all the others.
  3. When dealing with immutable items, such as strings, it doesn't matter if references point to the same object. Since immutable objects cannot be changed, there are no issues with such references.

The Generalize Step In TDD

Software Design: Tidy First? • 265 implied HN points • 06 Jun 25
🕹 Technology Software Design Development Programming Testing
  1. TDD is not just about writing tests, it also involves thoughtful design. Practitioners understand the balance between testing and creating a good product structure.
  2. Having good examples in TDD practices is really important for understanding and applying concepts effectively. Clear examples can help break down complex ideas.
  3. There is a common misconception that TDD lacks a design phase, but experienced users know that design is a key part of the process. It's essential to integrate design thinking into TDD for better outcomes.

Copy From a Simpler Language

Software Design: Tidy First? • 375 implied HN points • 31 May 25
🕹 Technology Software Coding Design Innovation Programming
  1. Using a simpler coding language can help solve complex problems more effectively. It's like making a tough task easier by breaking it down.
  2. There's a technique to get better results from complicated languages by copying from simpler ones. This might be useful for solving tricky coding challenges.
  3. The speed of changes in coding can create new ways to approach these problems. Staying aware of these changes can help developers improve their skills.

🤖 OpenAI Reveals AI’s No Match for Human Coders

HackerPulse Dispatch • 5 implied HN points • 25 Feb 25
🕹 Technology AI Programming Software Development Code Quality
  1. AI still struggles with real coding tasks despite being fast. It often fails to diagnose bugs or offer reliable solutions, proving that human coders are still needed.
  2. Using AI tools can make coding easier but might hurt learning. New programmers miss out on important problem-solving experiences that come from debugging and experimenting with code.
  3. AI-generated code can lead to more issues, like code duplication and technical debt. While it helps with productivity, it can also create long-term maintenance challenges.
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What's up Python: MOAR uv, flask-like Django, debugging live processes...

Bite code! • 1590 implied HN points • 29 Dec 24
🕹 Technology Programming Software Web Development Community Debugging
  1. Astral is expanding its projects and has taken control of python-build-standalone, making it easier to install Python on different systems without complicated setups.
  2. PEP 768 is a new proposal that will allow easier and safer debugging for live Python processes, improving how we can fix issues in running applications.
  3. The Django community is updating their framework to be more user-friendly by replacing old commands with simpler ones, while keeping the framework modern and relevant.

Solving The SwiftUI Interview

Jacob’s Tech Tavern • 2186 implied HN points • 10 Dec 24
🕹 Technology Software Programming Interviews Coding Swift
  1. Understanding SwiftUI is crucial for coding interviews, especially for positions focused on iOS development. It helps you stand out as a candidate.
  2. Practicing Swift Concurrency will give you an edge in solving problems more efficiently during interviews. It's an important skill that employers value.
  3. Interviews don't have to be stressful or frustrating. Using structured approaches can make the process smoother and more enjoyable for both candidates and interviewers.

AI #92: Behind the Curve

Don't Worry About the Vase • 2777 implied HN points • 28 Nov 24
🕹 Technology AI Machine Learning Tech Policy Programming Innovation
  1. AI language models are improving in utility, specifically for tasks like coding, but they still have some limitations such as being slow or clunky.
  2. Public perception of AI-generated poetry shows that people often prefer it over human-created poetry, indicating a shift in how we view creativity and value in writing.
  3. Conferences and role-playing exercises around AI emphasize the complexities and potential outcomes of AI alignment, highlighting that future AI developments bring both hopeful and concerning possibilities.

UV tricks

Bite code! • 1957 implied HN points • 15 Dec 24
🕹 Technology Software Programming Development Tools Python
  1. Using 'uv run' lets you run commands in a temporary environment without cluttering your main setup. This makes it easy to use big tools like Jupyter without installing them every time.
  2. The 'uvx' command works like 'npx', letting you test and run Python utilities quickly. It handles dependencies nicely, so you can focus on your tasks without worrying about setup.
  3. Creating scripts with 'uv init' helps you get started fast. It sets up everything you need, including project files and dependencies, making it easier to organize your Python projects.

Fine-tuning LLMs with 32-bit, 8-bit, and Paged AdamW Optimizers

The Kaitchup – AI on a Budget • 259 implied HN points • 07 Oct 24
🕹 Technology AI Machine Learning Optimization Data processing Programming
  1. Using 8-bit and paged AdamW optimizers can save a lot of memory when training large models. This means you can run more complex models on cheaper, lower-memory GPUs.
  2. The 8-bit optimizer is almost as effective as the 32-bit version, showing similar results in training. You can get great performance with less memory required.
  3. Paged optimizers help manage memory efficiently by moving data only when needed. This way, you can keep training even if you don't have enough GPU memory for everything.

Self-documenting Makefiles

Blog System/5 • 827 implied HN points • 10 Jan 25
🕹 Technology Software Development Programming Documentation Open Source
  1. Using Makefiles can help stitch together complex build processes easily. They allow you to create a command dispatcher with minimal code.
  2. By implementing a 'make help' command, you can provide users with a clear overview of available actions and necessary configuration, reducing confusion.
  3. Documenting both targets and user-settable variables in Makefiles can make them more user-friendly. This helps users know how to interact with the project without getting lost.

What is a Crash?

Jacob’s Tech Tavern • 3498 implied HN points • 04 Nov 24
🕹 Technology Software Programming Mobile App Development Operating Systems
  1. A crash happens when an app unexpectedly stops, but it can actually be a safety measure to prevent bigger problems. Think of it like a controlled explosion that protects your device.
  2. There are two main types of crashes: those caused by the Swift Runtime and those from the XNU Kernel. Each has its own reasons for triggering a crash to protect the system.
  3. Crashes don't just cause inconvenience; they are there to protect users from worse issues, like losing data or compromising security. They help keep everything safe even when things go wrong.

All your Python project in one file with shiv

Bite code! • 978 implied HN points • 02 Jan 25
🕹 Technology Software Programming Development Tools
  1. Shiv allows you to bundle your Python project into a single executable zip file, which includes all your code and its dependencies. This makes it easy to run your program on any compatible server without needing to install anything else.
  2. Creating a zipapp with shiv involves a few steps, including setting up a virtual environment and running specific commands to package your project. It’s important to understand the process to avoid common pitfalls.
  3. Using shiv can simplify deployment, especially for web services or applications with many dependencies. However, it does require Python to be installed on the target machine and might not work well with certain compiled extensions.

Advanced Swift Concurrency

Jacob’s Tech Tavern • 2624 implied HN points • 12 Nov 24
🕹 Technology Programming Software Development Concurrency Coding
  1. Swift Concurrency is a modern way to handle tasks in Swift, making it easier and more powerful compared to earlier methods like GCD. It's designed for simplicity and efficiency.
  2. Important concepts in Swift Concurrency include Task properties like priority, cancellation, and timeout settings. Understanding these helps developers manage their applications better.
  3. Using Task effectively allows developers to create more responsive and dynamic apps. It’s great to explore real-life examples to grasp how to implement these advanced features.

The Swift Runtime: Your Silent Partner

Jacob’s Tech Tavern • 1312 implied HN points • 16 Dec 24
🕹 Technology Programming Software Development Open Source Tech Trends
  1. The Swift Runtime, known as libswiftCore, is a C++ library that helps run Swift programs by managing essential features like memory and error handling.
  2. This library works alongside your Swift code, linking dynamically when you launch your app, which is why it's mentioned as running 'alongside'.
  3. By exploring the code within libswiftCore, you can learn how core Swift features are implemented at a deeper level, which can help you understand the language better.

AI #95: o1 Joins the API

Don't Worry About the Vase • 1164 implied HN points • 19 Dec 24
🕹 Technology AI Software Innovation Data science Programming
  1. The release of o1 into the API is significant. It enables developers to build applications with its capabilities, making it more accessible for various uses.
  2. Anthropic released an important paper about alignment issues in AI. It highlights some worrying behaviors in large language models that need more awareness and attention.
  3. There are still questions about how effectively AI tools are being used. Many people might not fully understand what AI can do or how to use it to enhance their work.

Behind AI #7: Top Python Libraries Any AI Enthusiast Should Know

Artificial Corner • 138 implied HN points • 09 Oct 24
🕹 Technology AI Programming Data science Software Development Web Development
  1. Python is a key language for AI because it has many useful libraries for tasks like data collection, cleaning, and visualization. Learning these libraries can help you work effectively on AI projects.
  2. For data collection, libraries like Requests and Beautiful Soup are useful for web scraping. If you need to handle JavaScript-driven sites, Selenium and Scrapy are great options.
  3. To visualize data, Matplotlib and Seaborn can help you create standard plots, while Plotly and Bokeh allow for interactive visualizations, making your data easier to understand.

The Great Tech Demographic Survey of 2025

The Lunduke Journal of Technology • 2297 implied HN points • 10 Feb 25
🕹 Technology IT Industry Programming Demographics Cryptocurrency
  1. A big survey is happening to gather data on tech workers' preferences and opinions. It asks about topics like programming languages, operating systems, and even personal beliefs.
  2. Everyone's answers will be anonymous, and you can choose which questions to answer. This approach aims to collect honest and diverse opinions.
  3. More participation leads to better data. The survey from last year had over 7,200 responses, and the goal is to get even more this time.

Notes on Nix

Cloud Irregular • 2956 implied HN points • 20 Jan 25
🕹 Technology Software Programming Development Cloud DevOps
  1. Nix is a tool that helps you set up your software environment the same way every time, making deployments easier. It's designed to manage software dependencies reliably.
  2. Nix can be complex to learn, especially because it uses functional programming concepts. This makes some programmers hesitant to adopt it.
  3. While Docker is useful for containerization, Nix offers better reproducibility for builds by focusing on what the environment should look like, rather than just the steps to create it.

What if AI eventually makes programmers smarter, not dumber?

Bite code! • 1467 implied HN points • 15 Nov 24
🕹 Technology AI Programming Software Development Automation
  1. AI can help programmers by reducing the amount of typing they do. This means they can focus more on solving problems instead of just writing code.
  2. As programmers use AI tools more, they might become better at understanding and defining problems instead of just following strict coding rules.
  3. In the long run, AI could make the whole community of developers smarter. It will lower the barrier for entry to coding and help people learn more about the real issues we need to solve.

Song Pong

Victor Tao • 273 HN points • 28 Aug 24
🕹 Technology Gaming Optimization Music Visualization Programming
  1. You can make a pong game more exciting by syncing the ball's movements to music. This allows paddles to dance to the beat as they hit the ball.
  2. Using math and optimization techniques can help you decide where the paddles should hit the ball. It ensures that the game looks good while still following all the rules.
  3. Changing the physics of the game doesn't have to be hard. You just update the rules in your math model, making it easy to test new ideas and keep improving the game.

Python 3.13, what didn't make the headlines

Bite code! • 1957 implied HN points • 25 Oct 24
🕹 Technology Programming Software Development Tools System
  1. Python 3.13 introduces improvements in debugging tools like PDB, making it easier to work with errors and set breakpoints. This is a big win for developers who rely on debugging in their workflow.
  2. The shutil module has seen many bug fixes and enhancements, which means working with files and directories will be more reliable. Developers can finally use it without constant worries about it failing.
  3. There are small but useful updates for concurrency in Python, such as changes to asyncio and task management. These little updates add up to make handling multiple tasks easier and more efficient.

Mocking OpenAI - Unit testing in the age of LLMs (Part One)

Laszlo’s Newsletter • 21 implied HN points • 23 Feb 25
🕹 Technology AI Software Programming Development Testing
  1. Unit tests are still important even with LLMs. They help ensure your code behaves as expected, even when using unpredictable AI tools.
  2. Mocking is needed to effectively test code that relies on LLMs. Instead of calling the actual AI, you create a 'fake' version that simulates its behavior.
  3. Using libraries like 'respx' can simplify mocking in your tests, and it's essential to handle things like retry logic carefully to keep tests fast.

The Black Spatula Project

Am I Stronger Yet? • 564 implied HN points • 18 Dec 24
🕹 Technology AI Science Research Programming Community
  1. A mistake in a scientific paper about black plastic utensils showed that math errors can change health implications. This finding led to a community initiative to check past papers for errors.
  2. The project aims to use AI to find mistakes in scientific papers, helping researchers ensure their work is accurate. This could lead to better practices in publishing and scientific research.
  3. Many ideas have emerged for improving how we check scientific work, such as creating tools to validate papers and verify information. The community is in the early stages of exploring these possibilities.

My Wronggest Content

Jacob’s Tech Tavern • 656 implied HN points • 26 Nov 24
🕹 Technology Social media Software Development Marketing Content creation Programming
  1. Posting wrong code online can lead to getting helpful feedback from others. Sometimes people are quick to point out mistakes, but that can help you learn.
  2. Using social media regularly can grow your audience. Posting interesting and engaging content helps attract more subscribers.
  3. Accepting criticism is important. It can be tough to hear people say your work is bad, but it's a chance to improve and grow.

"Don't talk to strangers" also applies to software development.

System Design Classroom • 499 implied HN points • 19 Jul 24
🕹 Technology Software Development System Design Programming Software Engineering Architecture
  1. Loose coupling is important in software. It means different parts of a program should depend on each other as little as possible, making it easier to change and fix things.
  2. The Law of Demeter suggests that objects should only talk to their direct friends and not reach out too far. This helps to keep dependencies low and makes code more manageable.
  3. Using strategies like the Single Responsibility Principle, interfaces, and dependency injection can improve your code's structure. This makes modules clear, easy to test, and maintain.

The Unreasonable Impact of Gradient Checkpointing for Fine-tuning LLMs

The Kaitchup – AI on a Budget • 79 implied HN points • 03 Oct 24
🕹 Technology AI Machine Learning Data science Programming Computing
  1. Gradient checkpointing helps to reduce memory usage during fine-tuning of large language models by up to 70%. This is really important because managing large amounts of memory can be tough with big models.
  2. Activations, which are crucial for training models, can take up over 90% of the memory needed. Keeping track of these is essential for successfully updating the model's weights.
  3. Even though gradient checkpointing helps save memory, it might slow down training a bit since some activations need to be recalculated. It's a trade-off to consider when choosing methods for model training.

LLMs Fight With Both Hands Tied Behind Their Back

Am I Stronger Yet? • 313 implied HN points • 27 Dec 24
🕹 Technology Artificial Intelligence Machine Learning Programming Data science Software Development
  1. Large Language Models (LLMs) like o3 are becoming better at solving complex math and coding problems, showing impressive performance compared to human competitors. They can tackle hard tasks with many attempts, which is different from how humans might solve them.
  2. Despite their advances, LLMs struggle with tasks that require visual reasoning or creativity. They often fail to understand spatial relationships in images because they process information in a linear way, making it hard to work with visual puzzles.
  3. LLMs rely heavily on knowledge in their 'heads' and do not have access to real-world knowledge. When they gain access to more external tools, their performance could improve significantly, potentially changing how they solve various problems.

Mach 1 with Python!

Bite code! • 733 implied HN points • 19 Nov 24
🕹 Technology Programming IOT Hardware Software Engineering
  1. You can measure distance using sonar technology, which was once considered advanced but is now easily available and affordable for projects like Raspberry Pi.
  2. Creating fun experiences, like detecting when people pass through a giant Mario pipe and playing a sound, requires careful planning and some troubleshooting.
  3. Working with hardware can be tricky, as it often involves dealing with unexpected issues and requires patience, but it can lead to creative and playful outcomes.

Measuring Programmer Influence, Kinda Sorta

Software Design: Tidy First? • 1347 implied HN points • 27 Jan 25
🕹 Technology Software Development Data Analysis Programming Project management
  1. Data can provide hints about a programmer's influence, but it can't give a clear answer. It's important to interpret the data with caution and avoid making strict decisions based solely on it.
  2. Creating files is one way to measure initiation of influence, but it's not the only factor. The impact is also determined by how frequently those files are modified by others.
  3. Using data for bonuses or promotions can lead to problems. It's better to focus on improvement and impact rather than just the numbers, to maintain a healthy team dynamic.

Bugs Optional?

Software Design: Tidy First? • 1723 implied HN points • 03 Jan 25
🕹 Technology Software Development Programming Engineering Quality Assurance Project management
  1. Bugs don't have to be a normal part of software development. Some teams manage to almost eliminate bugs by approaching their work differently.
  2. Instead of seeing bugs as inevitable, teams can work to understand and prevent them right from the start. This includes practices like continuous integration and team collaboration.
  3. Changing how we think about bugs from a normal part of life to something rare can help create a better work environment and improve software quality.

What's up Python? 3.13 is out, t-strings look awesome, dep groups come in handy...

Bite code! • 856 implied HN points • 29 Oct 24
🕹 Technology Software Programming Development Updates Tools
  1. Python 3.13 has been released, bringing many new features like better error messages and a new JIT compiler. It's exciting, but users are advised to hold off on upgrading until next year.
  2. Template strings (or t-strings) are introduced, offering a cleaner way to create formatted strings that can be used in various situations. This could help prevent mistakes when handling string formatting for tasks like translation or logging.
  3. New proposals like external wheel hosting and dependency groups in pyproject.toml make it easier to manage packages and their dependencies, especially for larger libraries.

Last week at The Lunduke Journal (Dec 1 - Dec 7, 2024)

The Lunduke Journal of Technology • 1723 implied HN points • 08 Dec 24
🕹 Technology Software Web Development Programming Tech news Digital Culture
  1. Mozilla has decided to brand itself as a 'Global Crew of Activists' which many people find confusing and unnecessary.
  2. KDE's new approach of nagging users for support seems to be working well, greatly increasing their income.
  3. There are ongoing discussions about the impact of codes of conduct in tech communities and how they may need changes or even elimination.

Yes, you need to duplicate your frontend business logic on the server

Bite code! • 978 implied HN points • 13 Oct 24
🕹 Technology Web Development Software Engineering Cybersecurity Programming Systems Architecture
  1. Always have your business logic on both the frontend and the server. If you only trust the client side, you risk getting incorrect data.
  2. Your server needs to handle requests from various sources, including non-standard browsers and bots. These can bypass your frontend checks if they're not replicated on the server.
  3. Any important checks for security and data integrity should happen on the server to prevent unexpected issues. This means you'll often have to duplicate checks that you already do on the frontend.

Launching Live Courses on Systems Programming

Confessions of a Code Addict • 1058 implied HN points • 25 Jan 25
🕹 Technology Software Development Systems Engineering Education Programming Course design
  1. There is a growing gap between complex systems in software and the engineers who understand them. More engineers need to learn how these systems work in detail.
  2. The new live courses will help those interested in systems engineering to gain practical skills. They'll start with basics like programming in X86 assembly and progress to more complex topics.
  3. Hands-on practice is key to learning in these courses. Along with guidance, you'll need to put in effort and time to really understand the concepts.

Demystifying GPU Compute Software

The Chip Letter • 6989 implied HN points • 10 Mar 24
🕹 Technology Computing Programming Hardware Frameworks Development
  1. GPU software ecosystems are crucial and as important as the GPU hardware itself.
  2. Programming GPUs requires specific tools like CUDA, ROCm, OpenCL, SYCL, and oneAPI, as they are different from CPUs and need special support from hardware vendors.
  3. The effectiveness of GPU programming tools is highly dependent on support from hardware vendors due to the complexity and rapid changes in GPU architectures.

Additional Testing After Refactoring

Software Design: Tidy First? • 950 implied HN points • 20 Jan 25
🕹 Technology Software Development Testing Refactoring Design Patterns Programming
  1. It's important to write more tests after refactoring. This helps improve accuracy and confidence in your code.
  2. When you break down a big piece of code into smaller parts, consider writing smaller tests for those parts, especially if you plan to reuse them.
  3. You might face a dilemma on whether to keep redundant tests after refactoring. It's good to regularly review tests to make sure you have the best approach for checking your code.

Data Science Weekly - Issue 560

Data Science Weekly Newsletter • 139 implied HN points • 15 Aug 24
🕹 Technology Data science AI Machine Learning Software Development Programming
  1. The Turing Test raises questions about what it means for a computer to think, suggesting that if a computer behaves like a human, we might consider it intelligent too.
  2. Creating a multimodal language model involves understanding different components like transformers, attention mechanisms, and learning techniques, which are essential for advanced AI systems.
  3. A recent study tested if astrologers can really analyze people's lives using astrology, addressing the ongoing debate about the legitimacy of astrology among the public.

JAX things to watch for in 2025

Gonzo ML • 378 implied HN points • 26 Nov 24
🕹 Technology AI Software Programming Data science Machine Learning
  1. The new NNX API is set to replace the older Linen API for building neural networks with JAX. It simplifies the coding process and offers better performance options.
  2. The shard_map feature improves multi-device computation by allowing better handling of data. It’s a helpful evolution for developers looking for precise control over their parallel computing tasks.
  3. Pallas is a new JAX tool that lets users write custom kernels for GPUs and TPUs. This allows for more specialized and efficient computation, particularly for advanced tasks like training large models.