Esat Turan

All the speed-reading tests I've tried seem to have the same problem. There's nothing stopping you from just clicking through the text really fast and claiming you can read 900 words per minute. It sounds impressive, sure, but it doesn't actually mean anything.

So, I decided to build my own, but with a comprehension check built in. You read a passage, then answer some questions about it. If your score is at or around what you'd get just by guessing, you don't get a score. Instead, you get an explanation that there's no real way to know if you actually read it.

There were a couple of outcomes I didn't really anticipate. First, some people fail the test and get upset. I guess you could say that's actually the tool doing its job. Second, it made the results more useful, not less. Since comprehension is tracked as the speed increases, the test can tell you "you were still understanding the material at 332 wpm," instead of just giving you a theoretical top speed. That's a number you can actually do something with.

The thing I keep wrestling with is this: is it good product design to refuse to give someone a number they're looking for, or am I just annoying people and making them leave?

Over the past few months, I've noticed that AI coding tools are excellent at generating code, but they still struggle to keep context across larger projects. That often means spending time re-explaining the codebase instead of moving faster.

I'm curious whether others have noticed the same thing, or if you've run into different limitations. What's the biggest issue you've experienced?

Spent the last few weeks building three connected apps and shared microservices with Lovable/Cursor. The first 80% went shockingly smooth, the demo-stage stuff always does. Then real usage started, and the integration between services and the admin dashboard started throwing constant sync errors. A few different AI coding tools could patch individual symptoms but never quite nail the root cause.

For anyone who's taken an AI-built app past the demo stage: what was the first thing that actually broke once real users or data hit it, auth, data consistency, service integration, something else? And did you end up digging into the code yourself, or bring in outside help to sort it out?