Code Pings

While preferences may vary among teams, there are proven best practices that lead to consistently better outcomes when it comes to code review. In this article, we'll dive into the key elements of an effective Laravel code review. https://saasykit.com/blog/how-to-review-laravel-code

We think we know AI dangers because we know software bugs are bad & fixable. This is wrong! AI system flaws are fundamentally different from traditional software issues. Applying old "bug fix" logic to AI is misleading and stops us from seeing the real risks. https://boydkane.com/essays/boss

Making Documentation Simpler and Practical: Our Docs-as-Code Journey https://engineering.squarespace.com/blog/2025/making-documentation-simpler-and-practical-our-docs-as-code-journey

The Great Software Quality Collapse: How We Normalized Catastrophe https://techtrenches.substack.com/p/the-great-software-quality-collapse

Martin Kleppmann, Adam Wiggins, Peter van Hardenberg, and Mark McGranaghan. Local-first software: you own your data, in spite of the cloud. https://www.inkandswitch.com/essay/local-first/

"Why Engineers Hate Their Managers" https://terriblesoftware.org/2025/06/24/why-engineers-hate-their-managers-and-what-to-do-about-it/

Intent-to-infrastructure: Platform engineers break bottlenecks with AI https://platformengineering.org/blog/intent-to-infrastructure-platform-engineers-break-bottlenecks-with-ai

The best optimizations begin with deletion.

Scaling systems means scaling responsibility too.

Good leaders don’t ask everyone to be the same, they ask everyone to be their best.

Sure, skip the form: just be ready to write the postmortem. https://codebymario.com/what-about/pain-and-paper

You can’t grow new habits without deprecating old ones.

Managing multiple issues at the same time isn't a superpower, it's just survival.

For clarity and maintainability, functions should return the modified object. To avoid side effects and ensure predictability, consider immutability or creating new copies. Relying on side effects may work in simple cases but can lead to errors. https://bagvalueobjects.com/

In tech, not knowing certain things but being good at finding them is a well-established standard. Interviews should focus on professionalism and, above all, 'ganas'. Ganas can't be faked with AI. https://newsletter.pragmaticengineer.com/p/how-genai-changes-tech-hiring

What you believe about yourself can change dramatically with one breakthrough.

A 'quick fix' seems obvious until it snowballs into unmanageable complexity.

Every productivity system seems revolutionary until you realize you’ve just rearranged your procrastination habits.

What seems like a failure can become a pivot point when seen from the right perspective.

Sometimes, the biggest growth comes from unlearning what you thought you knew.

We admire frameworks until their abstractions start to get in the way.

The obvious parts of a system often distract from the hidden dynamics that truly matter.

Feedback loops are amazing until you realize they mostly loop back to you doing more work.

You may think you're growing until you realize you’ve just been repeating the same cycle.

The most complex bugs feel rewarding to fix, but they also make you question every life choice that led you to that moment.

Version control workflows can seem universal until you work with a team that operates entirely differently.

There are design principles so ingrained that challenging them feels like heresy.

Trade-offs can feel like constraints until you see them as the seeds of creativity.

An elegant algorithm can make you forget that clarity is often more valuable than cleverness.

The best practices we cling to were once experiments, not eternal truths.

Some solutions feel inevitable until you meet someone who solves the same problem a different way.

Reading self-help books feels empowering until you realize you’ve spent more time reading about habits than building any.

I overoptimized a function to save milliseconds, only to learn it was called once a week. Lesson? Know what actually matters, sometimes "fast enough" is already perfect.

We once solved a complex bug and celebrated, only for a customer to find it again a week later. Turns out, we fixed the symptom, not the cause. Lesson? Band-aids work short-term, but root causes need surgery.

More often than not, I’m the one struggling to understand the code I wrote just a few months ago. There’s nothing more humbling than being schooled by your own past self.

Nothing brings a team together like realizing you’ve all been misunderstanding the same requirement for two weeks.

Root cause analysis feels exhaustive until you remember it's only as good as the questions you ask.

Feature flags are like duct tape: incredibly handy until you realize you’ve covered the entire car in it.

A senior dev once said, "Write code as if you're explaining it to someone who's tired, in a rush, and annoyed. Because someday, that will be you." Lesson? Clear, simple code saves lives (or at least sanity).

During a sprint, we rushed to finish everything. The result? Features shipped half-baked and bugs rolled in. Lesson? Finishing less but doing it well often beats delivering a lot and spending weeks cleaning up.

Agile seems brilliant until your standups start feeling like 'Groundhog Day' with less Bill Murray and more Jira tickets.