Lena Park

The research on how we really spend our workdays is uncomfortable. Understanding the gap between perceived and actual productive time is the first step to closing it.

Blaming notifications for your distraction problem is like blaming your inbox for your email problem. The architecture underneath is what's broken.

Bigger AI models aren't always better. Smaller, specialized models are faster, cheaper, and often more accurate for the tasks that actually matter in production.

A software team's postmortem reveals something worse than lost time: context switching doesn't pause your thinking, it corrupts it.

Every notification you receive has already cost you something, whether you act on it or not. Here's how to think about that cost systematically.

Canceling a meeting isn't avoidance. Sometimes it's the most productive decision in your calendar. Here's why, item by item.

Engineers spend weeks optimizing inference. Meanwhile, the real latency culprit sits quietly in preprocessing, I/O, and orchestration code nobody's benchmarked.

Every popular to-do system is optimized for capture. Almost none are optimized for completion. Here's what that costs you.

Heisenbugs vanish the moment you try to observe them. Understanding why they exist is the first step to catching them.

A stubborn architectural problem at a software consultancy got solved not in a sprint, but in the shower. Here's why that keeps happening and what to do about it.

A software team's experiment with async-first communication revealed something counterintuitive: removing synchronous time didn't slow decisions. It accelerated them.

Autocomplete doesn't just finish your sentences. It nudges you toward the most statistically average version of what you were about to say, and you rarely notice.

Your presence in meetings isn't neutral. It changes what gets said, who speaks, and what gets decided. Sometimes the best thing you can do is stay out.

Most teams fine-tune a model expecting it to learn new information. That's not what happens. Here's what actually changes inside the model.

Every shared document exists in at least two states: what you sent and what each recipient actually sees. The gap between them is where communication breaks down.

Shipping a model isn't the finish line. It's where the interesting problems start. Here's what your model is silently doing (and suffering) in production.

Every team thinks they agree on what 'done' means. They don't. Here's where the definition quietly falls apart.

Priority-based task lists feel logical but consistently fail in practice. The sorting dimension you're missing isn't urgency or importance. It's activation energy.