The hottest Code Quality Substack posts right now

And their main takeaways
Category
Top Technology Topics

Why Does Development Slow?

Software Design: Tidy First? • 2143 implied HN points • 19 Nov 25
đź•ą Technology Code Quality
  1. Software seems fast at first because the codebase starts with lots of options, but each feature you add burns options and over time complexity, bugs, and compatibility needs make progress slow.
  2. Every feature gives immediate value but also reduces optionality for future work, so shipping more features makes later changes harder and costlier.
  3. To keep momentum, alternate shipping features with deliberate work to restore or increase optionality—tidying, refactoring, or redesign between features so future work stays easier.

80 characters? In this economy?

Bite code! • 733 implied HN points • 17 Nov 25
đź•ą Technology Code Quality
  1. Keeping lines of code to 80 characters makes it easier for our eyes to read. It helps us quickly find where the next line starts.
  2. Having shorter lines is useful when using multiple tools side by side, like browsers and code editors. It makes coding and comparing changes easier.
  3. Sticking to the 80-character limit can improve programming habits, like using clear variable names and reducing complexity in code. This helps create better overall code.

Augmented Coding: Beyond the Vibes

Software Design: Tidy First? • 1855 implied HN points • 25 Jun 25
đź•ą Technology Code Quality
  1. Augmented coding is different from vibe coding. It's about caring for the code quality and complexity, not just getting the system to work.
  2. Keeping the project scope clear is key. You should focus on specific tasks, like creating a B+ Tree, while ensuring the code is tidy and functional.
  3. Collaboration with AI tools can enhance coding efficiency. You can rely on AI for tasks like writing tests or suggesting optimizations, but you must guide it to stay on track.

5 engineering dogmas it's time to retire

Leading Developers • 139 implied HN points • 16 Dec 25
đź•ą Technology Code Quality
  1. Don’t automatically reach for a third‑party package; weigh the security, maintenance, and reliability costs of a dependency against writing and owning the code yourself.
  2. Rigid rules like mandatory reviews for every PR and fixed 2–4 week sprints can slow teams and kill creativity; trust skilled engineers, consider pair programming, and try alternative ways of working that fit your team.
  3. Use feature flags judiciously because they add complexity and testing burden, and don’t be dogmatic about comments—short, clear comments can save future developers a lot of time.

The Pythonic Emptiness

Confessions of a Code Addict • 529 implied HN points • 09 Nov 24
đź•ą Technology Code Quality
  1. In Python, you can check if a list is empty by using 'if not mylist' instead of 'if len(mylist) == 0'. This way is faster and is more widely accepted as the Pythonic approach.
  2. Some people find the truthiness method confusing, but it often boils down to bad coding practices, like unclear variable names. Keeping your code clean and well-named can make this style clearer and more readable.
  3. Using 'len()' to check for emptiness isn't wrong, but you should choose based on your situation. The main point is that the Pythonic method isn't ambiguous; it just needs proper context and quality coding.
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Avoid these Mistakes if you are Android Developers

Better Engineers • 19 implied HN points • 18 Jul 24
đź•ą Technology Code Quality
  1. Avoid common mistakes like leaving commented code and using hardcoded values. These habits can help make your code cleaner and more reliable.
  2. Develop strong code review skills to give helpful feedback and improve your team's coding practices. This will also help you grow as a developer.
  3. Focus on scalability by breaking down large features into smaller tasks and using modern tools and concepts. This approach will make your projects easier to manage as they grow.

The Measurement Problem in Software Engineering

Maestro's Musings • 17 implied HN points • 15 Dec 25
đź•ą Technology Code Quality
  1. Counting artifacts like lines of code, story points, or PR counts has repeatedly failed; these proxies miss real value, are easy to game, and can harm organizations.
  2. AI both breaks traditional metrics—making code volume meaningless and often increasing churn and bugs—and widens perception gaps where developers feel faster than measured results show.
  3. A promising path is semantic, context-aware measurement that uses AI to understand what changes actually do and synthesize those findings into simple narratives for leaders, aiming for "good enough" insight that’s harder to game.

AI made us faster. That’s not the same as better.

Brick by Brick • 9 implied HN points • 24 Dec 25
đź•ą Technology Code Quality
  1. AI coding tools have evolved into a diverse, faster set of assistants with different interaction styles, and engineers now choose which tool to use for each task.
  2. These tools speed up work but rarely produce code that’s clearly better — most AI-generated code still needs human review, polishing, or refactoring before it’s ship-ready.
  3. Engineers use AI selectively and responsibly: they get productivity and satisfaction gains while maintaining ownership of code quality and long-term maintenance.

Technical Debt 101: A Short Quick Guide

Weekend Developer • 19 implied HN points • 31 May 24
đź•ą Technology Code Quality
  1. Technical debt is like borrowing time when you write code shortcuts that need to be revised later, similar to financial debt repayment with interest.
  2. Ways technical debt can occur: rushed development, lack of documentation, poor testing, ignoring refactoring, avoiding version upgrades, and lacking developer tools.
  3. Consequences of excessive technical debt include decreased productivity, increased bugs, higher costs, team morale issues, and security risks; managing it involves prioritizing refactoring, writing tests, documenting, reviewing code, and communicating with stakeholders.

Legacy Shmegacy

David Reis on Software • 59 implied HN points • 24 Nov 24
đź•ą Technology Code Quality
  1. Legacy code often gets that label just because newer programmers don’t understand it. The core issue is usually about people, not the actual code quality.
  2. To avoid creating legacy code, focus on writing clear and simple code that others can easily understand, and engage in practices like mentoring and pair programming.
  3. When dealing with legacy code, try to understand it fully before deciding to rewrite it. Often, working with what's there and improving it gradually is the better choice.

To hack or not to hack

Sunday Letters • 179 implied HN points • 24 Jan 22
đź•ą Technology Code Quality
  1. In software development, it's a challenge to choose between making a general solution or focusing on a specific problem. Both approaches have their pros and cons.
  2. If you hack your code without planning, it can become messy and hard to manage. But if you overthink it and try to make it too general too soon, you might waste time and effort.
  3. To find the right balance, ask how hard it is to change things later and how long the general solution will take to pay off. It's about making smart decisions based on the problem at hand.

Developers hate this one thing (all about code reviews)

Technically • 20 implied HN points • 17 Jun 25
đź•ą Technology Code Quality
  1. Code reviews are essential for ensuring that code is high quality and maintainable. They help catch mistakes and ensure everyone is on the same page when writing code.
  2. Code reviews can be really slow because they require a lot of context and detail. Often, waiting for a review takes longer than actually writing the code.
  3. AI tools like CodeRabbit are starting to help speed up code reviews by automating parts of the process. They can provide quick feedback, which helps developers stay focused and efficient.

The AI Shift: Preparing for What’s Next

Dev Interrupted • 32 implied HN points • 05 Dec 24
đź•ą Technology Code Quality
  1. AI tools can help developers work faster, but they need to be careful about the quality of the code. It's important for developers to review what AI produces to ensure it meets necessary standards.
  2. AI is a permanent part of software development, but it has its flaws. Many AI-generated codes can be incorrect, so developers should set up proper checks to keep the software secure and reliable.
  3. To prevent burnout and improve productivity, developers should focus on important projects and let automation tools help with code reviews. Changing hiring practices can also help bring in fresh talent and support better workflows.

Let's add a whole bunch of simplicity

Sunday Letters • 119 implied HN points • 15 Nov 21
đź•ą Technology Code Quality
  1. Simplicity is about removing complexity, not adding it. We often think we can just make things easier, but the reality is that we have to eliminate the complicated parts.
  2. To create simplicity, we should clearly define our goals. Understanding exactly what we need to do helps us focus and decide what to avoid.
  3. Finding the simplest version of a project may mean letting go of features you like. It's important to be disciplined and recognize that simplifying can sometimes feel uncomfortable.

The need for beautiful code

Wednesday Wisdom • 56 implied HN points • 28 Feb 24
đź•ą Technology Code Quality
  1. Investing time in writing beautiful code is crucial for code longevity and maintainability.
  2. Code that 'mostly works' is not the standard to aim for; focus on creating code that is always functional and meets significant requirements.
  3. Developing a culture of producing beautiful code in a team requires more than guidelines and prizes; it involves a collective shift in mindset and commitment.

Episode 40: Better Built By Burkhard

burkhardstubert • 19 implied HN points • 15 Apr 23
đź•ą Technology Code Quality
  1. I/O-free tests are better for Test-Driven Development (TDD) because they are faster, isolated, and repeatable. This makes them more suitable for writing reliable software.
  2. It doesn't really matter if tests are labeled as unit, integration, or acceptance tests. What matters is how easy they are to write and how quickly they run.
  3. Successful software development practices like pair programming require a supportive company culture and a willingness from each developer to learn and adapt.

Software Quality

Engineering Enablement • 37 implied HN points • 05 Jan 24
đź•ą Technology Code Quality
  1. Software quality encompasses four types: process, code, system, and product quality.
  2. Process quality sets the foundation for overall software quality by having a strong development process.
  3. Code quality is crucial for system quality and product quality, focusing on maintainability and reducing defects.

Why are non-DRY specs more maintainable?

The Daily Developer • 2 HN points • 20 Feb 24
đź•ą Technology Code Quality
  1. Non-DRY specs prioritize duplication over the wrong abstraction, promoting simple code with locality over complexity.
  2. Locality in code refers to its ability to be easily understood without relying on larger context, making it more maintainable.
  3. Compression in code, which requires understanding context, is seen as the wrong abstraction, leading to complexity and less maintainable code.

🤖 OpenAI Reveals AI’s No Match for Human Coders

HackerPulse Dispatch • 5 implied HN points • 25 Feb 25
đź•ą Technology 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.

Refactoring BabyAGI - Code Quality and LLMs

Laszlo’s Newsletter • 27 implied HN points • 04 May 23
đź•ą Technology Code Quality
  1. When refactoring code, it's important to move code into service classes for better organization and readability.
  2. Utilize constants and parameters closer to their use for easier handling of configurations and serialization/deserialization.
  3. Consider refactoring to address code smells like 'Feature Envy' and 'Primitive Obsession' to improve code maintainability and readability.

Good Comment, Bad Comment

David Reis on Software • 13 implied HN points • 09 Mar 24
đź•ą Technology Code Quality
  1. Many new programmers think that not commenting code is a sign of good practice because of the idea that 'clean code has no comments.' This leads to less readable code.
  2. Good code should be easily understood, but comments can help clarify complex parts when necessary. It's okay to use comments to explain why something is done a certain way.
  3. Writers should be careful with popular ideas that seem easy and convenient, as they can sometimes oversimplify important concepts and lead people to misunderstand or misuse them.

Episode 15: Burkhard on Qt Embedded Systems

burkhardstubert • 19 implied HN points • 28 Feb 21
đź•ą Technology Code Quality
  1. There are events happening for Qt embedded systems, and the deadlines for presenting are coming up soon. If you want to share your work, make sure to submit your proposals on time!
  2. When writing code, it's important to make it readable by using good names and comments. Bad names should be replaced with clearer function names instead of relying on comments to explain them.
  3. Focus on breaking down your code into smaller, manageable functions. Each function should do one task well, which makes it easier to read and understand.