u/Far_Possibility_3985

I’m trying to understand the actual pain points people face while building with AI tools like ChatGPT, Claude, Cursor etc. Not looking for generic takes, more like repeated frustrations during real workflows.

What do you keep redoing? What feels broken? What do you hate re-explaining to AI? Where do you lose momentum or abandon flow? What part of building with AI feels unnecessarily frustrating?

Would love to hear from solo builders / indie hackers especially.

I've been noticing this pattern in myself for months and I finally snapped out of it.

You sit down with a simple idea. You ask ChatGPT about it. It gives you a really good answer. That answer mentions a few things you hadn't considered, so you ask about those too. Suddenly you're comparing architectures, databases, auth systems, deployment strategies... for an app that doesn't even exist yet.

Two hours go by and it genuinely feels like you made progress.

But you didn't build anything. You didn't even decide anything. You just explored endlessly.

And the weird part is ChatGPT (Or any AI) will never stop you. It won't say "you already researched this enough, just pick one." It won't tell you you're scope creeping or over-engineering your MVP. It'll happily keep answering forever.

So you end up drifting without realizing it.

Drifting - you came to build a task app, now you're designing an AI productivity ecosystem

Looping - you've compared React vs Vue vs Svelte three separate times and still haven't picked one

Second-guessing - you committed to Supabase an hour ago and now you're back to searching "Supabase vs Firebase" again

The dangerous part is that it all FEELS productive. You're learning things. You're thinking deeply. You're considering edge cases. But movement isn't direction.

AI solved the information problem. Now the problem is too much information and no guard rails. Nothing remembers what you already decided. Nothing tells you you're going in circles. It's just infinite helpfulness pulling you into deeper and deeper rabbit holes.

I've started asking myself one question whenever I'm deep in a ChatGPT session:

"What have I actually decided in the last 30 minutes?"

If the answer is "nothing," I'm probably not working.

I'm just spinning.

I’ve noticed something weird whenever I try to learn a new topic on my own.

The actual learning is only half the battle , the other half is constantly managing how to learn it.

Finding which YouTube video is actually worth watching, checking if I need some prerequisite first, opening PDFs/textbooks, asking ChatGPT doubts, making notes, figuring out what to study next… after a point it starts feeling like I’m doing project management instead of studying.

Sometimes I’m not even mentally tired from the concept itself, I’m tired from switching between 10 resources and trying to stitch everything together.

Would you actually use something that acts like a study guide and handles all of that for you?
Like it tells you what to study next, pulls the right video/PDF/notes when needed, patches gaps if you’re missing basics, and basically just keeps you moving so you can focus only on understanding.

Or do you think part of self-learning is manually doing all this anyway?

I’ve noticed something weird whenever I try to learn a new topic on my own.

The actual learning is only half the battle , the other half is constantly managing how to learn it.

Finding which YouTube video is actually worth watching, checking if I need some prerequisite first, opening PDFs/textbooks, asking ChatGPT doubts, making notes, figuring out what to study next… after a point it starts feeling like I’m doing project management instead of studying.

Sometimes I’m not even mentally tired from the concept itself, I’m tired from switching between 10 resources and trying to stitch everything together.

Would you actually use something that acts like a study guide and handles all of that for you?
Like it tells you what to study next, pulls the right video/PDF/notes when needed, patches gaps if you’re missing basics, and basically just keeps you moving so you can focus only on understanding.

Or do you think part of self-learning is manually doing all this anyway?

When I was trying to properly understand things like BFS, recursion, pointer movement, etc., I realized the part that usually makes it click is not the paragraph explanation — it's when someone keeps redrawing the board after every single step.

Like: queue state now visited nodes now pointer moved here stack frame added here

Most tutorials give you one final diagram and expect your brain to animate the rest.

That gap is weirdly hard when you're learning alone.

So I started finding resources that does something specific: instead of just explaining the topic in text, it auto-generates a fresh whiteboard-style diagram every time the state changes.

Meaning if it's BFS, it redraws after each dequeue/enqueue. If it's linked list reversal, it redraws after each pointer flip. If it's recursion, it redraws the call stack growth/shrink.

I'm not even sure yet if this is genuinely better pedagogy or if it just feels nicer to look at.

Curious: for people learning DSA/CS right now — would repeated state-transition diagrams actually help you more than the normal "one explanation + one static image" style?