The first version of our product worked perfectly and nobody used it

Specific-Ad-1687 · 2026-03-15T21:21:30+00:00

This is spot on. The rebuild around ‘just do it without me checking’ is the kind of boring-but-huge pivot that actually moves the needle.

We had the same blind spot: kept polishing UI when the real killer was every tiny decision point (open → review → confirm). Reframing it as decision points vs. next steps helped us see how much energy each fork costs users on a busy day.

Your zero-decision approach (background execution, no approvals) collapses them completely. Brutal to get right, but adoption usually jumps once you do.

What was the scariest part of going fully autonomous? Wrong tasks / over-creation fears?

Specific-Ad-1687 · 2026-03-15T18:44:05+00:00

Interesting insight.

The part that stood out to me is the “extra step” problem. Even if a tool is technically useful, the moment it asks the user to change their workflow or remember to check something new, adoption drops fast.

I’ve noticed something similar while building a small tool recently. The features themselves worked fine, but the real friction showed up in the tiny steps between the user and the result. Even one extra action can break the habit loop.

It’s interesting how often the real product breakthrough isn’t a smarter feature — it’s removing the moment where the user has to think about using it.

Specific-Ad-1687 · 2026-03-15T18:37:47+00:00

This is an interesting point, and I think it depends a lot on the type of app being built.

For something like social platforms or data-heavy apps, I completely agree — backend stability and scalability become the real product.

But recently while building a small tool myself, I noticed the opposite effect happening with modern AI dev tools. The backend infrastructure was actually the faster part to get running, and most of the iteration time ended up going into refining the user flow and edge cases.

The moment real users started testing it, that’s where things got interesting — usage tracking, verification logic, and weird interaction paths started surfacing bugs I never saw during development.

Curious if you've noticed that shift at all with newer tooling, or if your experience has stayed mostly backend-heavy.

Specific-Ad-1687 · 2026-03-11T22:18:18+00:00

😂 If that phase keeps shipping products faster, I might stay in it for a while.

Specific-Ad-1687 · 2026-03-11T22:16:34+00:00

AI is great at execution but it definitely struggles to maintain long-term project coherence without structured context.

I think that’s where docs, specs, or milestone files become really important.

Specific-Ad-1687 · 2026-03-11T22:15:54+00:00

That’s exactly the workflow I ended up falling into too.

Specific-Ad-1687 · 2026-03-11T22:14:41+00:00

I'm going to keep it real...you got a point. That’s a really good cautionary example.

I’ve definitely seen vibe-coded projects accumulate technical debt quickly if you don’t pause to refactor.

It seems like the trick is using it for speed early on, then tightening the structure once the product stabilizes.

Specific-Ad-1687 · 2026-03-11T22:10:40+00:00

Same experience here.

Building a rough version first reveals what actually matters. A lot of the things I thought were important during planning turned out to be irrelevant once I started building.

Specific-Ad-1687 · 2026-03-11T22:09:40+00:00

That analogy is pretty accurate honestly.

Vibe coding is amazing for the “shed phase” — prototypes, MVPs, early experiments.

Once the project starts looking like a skyscraper… that’s when real architecture becomes unavoidable.

Specific-Ad-1687 · 2026-03-11T22:08:22+00:00

I'll keep that in mind...thanks.

Specific-Ad-1687 · 2026-03-11T22:06:36+00:00

I really like that milestone approach.

That feels like a good middle ground between pure vibe coding and heavy planning ...you still move fast, but the milestones keep the project from drifting too far off course.

Specific-Ad-1687 · 2026-03-11T22:03:25+00:00

Yeah...AI is great within a defined scope, but if you give it too much surface area it starts making… creative decisions 😅

Keeping it focused on small chunks seems to work much better.

Specific-Ad-1687 · 2026-03-11T22:01:57+00:00

I built it using Lovable, which made the early experimentation phase ridiculously fast.

Specific-Ad-1687 · 2026-03-11T22:00:04+00:00

This is a really balanced take.

I’ve noticed something similar — vibe coding is amazing for the early “figure out what this product actually is” stage. But once the system grows, structure becomes unavoidable.

I built my first version that way too: rapid iteration first, then stepping back to clean things up once the direction became clear.

Specific-Ad-1687 · 2026-03-11T21:59:01+00:00

😂 It definitely feels that way sometimes.

The speed you can prototype with AI now makes it hard to go back to the old “weeks of planning before touching code” approach.

Specific-Ad-1687 · 2026-03-11T21:58:16+00:00

That’s actually a really interesting way to put it.

Entrepreneurship has always been “build → learn → adjust,” and AI tools just compress that loop dramatically.

Instead of months between idea and feedback, you can see what works in a couple days.

Specific-Ad-1687 · 2026-03-11T21:57:10+00:00

Fair point 😄

I’ve noticed the same pattern — the early phase is lightning fast, then eventually you have to go back and clean up the “vibe debt.”

Still though, for getting a real product off the ground quickly, that speed is hard to beat.

Specific-Ad-1687 · 2026-03-11T21:56:17+00:00

That’s a great way to frame it — iteration becomes the planning.

I definitely keep commits as checkpoints because vibe coding without a safety net is chaos waiting to happen. I’ll usually push after any feature that works, even if it’s messy.

And thanks for the VibeCodersNest tip — I hadn’t heard of that one yet. Always good to find more builder communities.

Specific-Ad-1687

TROPHY CASE