Completely agree, most failures I’ve seen come from poor context management and unclear data flow, not the model itself. State handling also becomes a major issue when workflows scale, especially with multiple tools and agents interacting. In my experience, debugging improves a lot once you treat it as a system design problem rather than just an AI model issue.

Hmm, I think AI tools are actually pretty helpful, but you still have to double-check everything — they’re not perfect 🙂

This is exactly the kind of content I enjoy reading—simple, informative, and straight to the point. Keep it up!

The real shift is when you stop treating AI as a threat and start using it as a tool you actively guide—because clarity in your thinking is what makes it useful, not the other way around.

Spaced repetition for Leetcode is one of those obvious-in-hindsight ideas — I've watched candidates grind 400 problems and still blank on a tree traversal in week 2 because they never revisited the early ones. Curious about the scheduling: are you using straight SM-2 or did you tune the intervals around problem difficulty tiers (easy vs hard take different memory windows)?

YOU ALL HAVE TRY THIS CODE ALE194942