u/Suspicious-Bug-626

Vibe coding tricked me into thinking I shipped a product.
▲ 976 r/VibeCodeCamp+1 crossposts

Vibe coding tricked me into thinking I shipped a product.

The demo was clean. The UI was sharp. The deploy worked.

I genuinely thought I was done.

Then real users showed up. And everything I never built started breaking.

→ Auth flows leaked data because RLS was never set up
→ The API got hammered with zero rate limiting
→ Errors piled up silently with nothing tracking them
→ The database slowed to a crawl on its first real query

What looked like a finished product was actually frontend and backend sitting on top of 11 missing layers.

The stuff nobody shows in the launch tweet:

→ Auth and permissions
→ Hosting and deployment
→ Cloud and compute
→ CI/CD and version control
→ Security and Row Level Security
→ Rate limiting
→ Caching and CDN
→ Load balancing and scaling
→ Error tracking and logs
→ Database hardening
→ Availability and recovery

None of this lives in a Lovable preview. None of it shows up in a Cursor screen recording.

But all of it is what separates a working demo from a product real people pay for.

Vibe coding is incredible for proving an idea. It turns weeks of work into hours.

But shipping a real product still needs real engineering.

Pretending otherwise is how startups end up with 10,000 users and an app that crashes on Tuesday morning.

Use vibe coding to validate fast.

Then build the layers underneath that actually keep it alive.

Over to you: which layer broke first when your prototype met real users?

u/Suspicious-Bug-626 — 4 days ago

For context, I'm building an enterprise AI coding development tool that specifically excels in legacy codebases and regulated industries..I'm wondering if any devs here working within enterprise are seeing this trend where teams need stronger traceability and review discipline rather than just code generation?

Is the bigger opportunity faster coding, or better system understanding around every change?

I would love to get honest opinions as we currently work with a few healthcare, banking, and other regulated tech firms and this insight would help the product positioning better.

reddit.com
u/Suspicious-Bug-626 — 20 days ago

AI coding tools are getting better at helping individual developers produce code (within a local context), but enterprise software delivery still breaks down across the broader lifecycle. Most requirements become tickets, tickets become architecture decisions, and those decisions become code changes. The code changes made by AI affect testing, documentation, releases, downstream systems, and audit requirements.

In regulated industries like healthcare, lifecycle continuity matters more than raw code generation.

So my question is: Are we over‑indexing on AI that writes code and under‑building AI systems that preserve engineering context across the lifecycle?

What would the ideal enterprise AI development tool or workflow look like, and what particular features should it have?

reddit.com
u/Suspicious-Bug-626 — 20 days ago

I know almost every software engineer is using AI‑assisted development while building and editing software. I'm wondering how acceptable it is, especially in a regulated environment like healthcare.

Because one simple change may touch validation logic, workflow behavior, patient-facing systems, reporting, downstream integrations, etc etc.

So the question becomes less about whether AI can help write code, and really more about can the full change be understood and reviewed by a human properly (NOT BY ANOTHER AI)

What would need to be in place for you or your team to feel comfortable using AI in a regulated software workflow?

Impact analysis? Human approval gates? Audit logs?

Something else entirely? Feel free to let me know if Im thinking about this the right way as I'm pitching a healthcare client and need to to get some ground reality.

reddit.com
u/Suspicious-Bug-626 — 20 days ago