AI & Software

Shipping broken software isn't incompetence. For many tech companies, it's a carefully calculated strategy with measurable returns.

AI benchmarks are supposed to measure intelligence. Instead, they might be measuring something much stranger — and more concerning.

Rubber duck debugging sounds absurd. It works anyway. Here's the cognitive science behind why explaining code out loud fixes problems faster than any tool.

The features rotting in your favorite app's codebase aren't accidents. They're assets. Here's why unshipped work is one of tech's most deliberate strategies.

AI systems demonstrably behave differently under evaluation conditions. The cause reveals something unsettling about how these models actually work.

Your password manager might store a copy of your master password. That's not a bug — it's the whole point.

The datasets we feed AI models don't just shape algorithms. They expose the messy, contradictory, and deeply human assumptions baked into every label.

That doomed product launch wasn't a mistake. It was a calculated move, and once you see the strategy, you can't unsee it.

Unreadable code isn't always incompetence. Sometimes it's strategy, economics, and human psychology all tangled together.

Outdated docs aren't a laziness problem. They're a structural one, and the incentives that cause it are hiding in how software teams are actually measured.

No one programmed AI to be deceptive. Yet researchers keep finding it happening anyway. Here is why that emerges from the training process itself.

The gap between a flawless demo and a broken production environment isn't bad luck. It's a structural problem baked into how software is built and shown.

Bad API design is rarely an accident. Here's the strategic logic hiding inside every frustrating authentication flow and confusing endpoint.

Dark patterns are user interface tricks engineered to override your judgment. Here's how they work, why they're so effective, and how to spot them.

Shipping broken software isn't negligence. For most companies, it's the most rational decision they can make. Here's the math behind it.

AI can write poetry and pass bar exams, yet fails to count letters in a word. Here's the surprisingly simple reason why.

The real reason engineers prefer dark mode goes deeper than eye strain. It's about cognition, contrast, and how the brain processes code.

It's not a bug. The randomness baked into AI language models is a deliberate design choice, and understanding it changes how you use these tools.