Priya Sharma

Chain-of-thought prompting genuinely improves LLM reasoning, but not for the reasons most people assume. Here's the real mechanism.

Your brain keeps processing an interruption long after you dismiss it. Here's what that costs you and how to design your day around it.

Time blocking feels productive. But for deep, creative work, it often destroys the conditions that make that work possible.

Vector databases don't understand language. They store coordinates. What happens between those two facts explains a lot about where AI search succeeds and fails.

Canceling a meeting isn't failure. Often it's the most productive decision in your calendar. Here's why, and how to make it a habit.

You write code in English-like syntax. The CPU speaks binary. Here's what happens in between, and why it matters more than you think.

When models train on AI-generated text, small errors compound into something worse than noise. This is a structural problem, not a data hygiene issue.

The friction in your productivity system is asymmetric. Adding takes one second. Finishing takes everything else.

Some bugs vanish the moment you try to observe them. This isn't magic — it's physics, timing, and a category of errors that your debugging tools can actively hide from you.

The most productive conversations at work don't appear on any calendar. Here's what that means for how you structure your day.

A bug fix feels like progress. Sometimes it is. Sometimes it quietly breaks the three things that were working around the bug you just removed.

The productivity cost of context switching isn't measured in minutes. It's measured in the quality of thought you never get to finish.

Spotify's recommendation engine didn't start with listening habits. It started with text. That choice reveals what embeddings actually are.

Adding more information to your AI prompts seems like it should help. Often it makes things noticeably worse. Here's the mechanics of why.

You completed the work. But until you formally close the task, your brain hasn't. That gap is costing you more than you think.

Most AI output problems aren't model failures. They're prompt failures. Here's how to stop blaming the tool and fix the actual problem.

When a bug only appears in production, it's not bad luck. It's a signal that your test suite is modeling the wrong world.

Starting a project feels good because your brain rewards the plan, not the work. Here's what that means for how you should be planning.