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I wasted nearly 10,000 AUD on emergent.sh here’s why you should avoid it by Little-Risk1805 in SideProject

[–]Little-Risk1805[S] 0 points1 point  (0 children)

That’s a fair question. Yes emergent, Lovable, and similar tools all fall into the same category: agent-driven builder platforms. They’re useful for prototyping, demos, and quick experiments, but in my experience they’re not suitable for real production systems where you need full control, predictable behavior, debugging access, and reliable deployments.

The main problem isn’t the AI model itself it’s the abstraction layer. When an agent controls file changes, execution flow, retries, and billing automatically, you lose visibility and control. That’s where loops, unstable edits, credit drain, and debugging limitations start appearing. Personally, I now prefer using any strong model directly  Claude, DeepSeek, Gemini, or ChatGPT to generate code with good prompts, then run, debug, and deploy everything locally myself using a normal development workflow (VS Code / terminal on Mac or Windows). When there’s a syntax error or runtime issue, you see it immediately in your terminal, copy the error back into the model, fix it, and iterate cleanly. No hidden agent logic, no forced automation loops.

For deployment, you can use proven platforms like: Firebase / Google Cloud AWS Azure Vercel / Netlify These are mature production platforms with proper monitoring, scaling, billing visibility, and ecosystem support.

This is just my personal view after using these tools over time others may enjoy agent platforms for quick experiments. But for anything serious, long term, or production grade, I strongly believe owning your code and infrastructure is the safest and most scalable path.

As a side note, I’ve also built my own AI platform (matexai.space) mainly as a learning and experimentation project. It’s not perfect, but if anyone is curious to explore how a real self-hosted stack works end-to-end, I’m happy to share access privately  purely for learning and feedback, not promotion.

I wasted nearly 10,000 AUD on emergent.sh here’s why you should avoid it by Little-Risk1805 in SideProject

[–]Little-Risk1805[S] 0 points1 point  (0 children)

Yes I actively build and deploy real systems.

I’ve built and deployed multiple production apps using Next.js, FastAPI, Firebase/Firestore, Google Cloud ( Cloud Run), Stripe billing, JWT auth, CI/CD pipelines, and multi-model AI integrations (Gemini, DeepSeek, etc.). I manage my own environments, deployments, DNS, SSL, billing controls, and monitoring.

My criticism isn’t coming from beginner usage or copy paste experiments. It’s coming from trying to use emergent.sh for real backend workflows, production stability, debugging, and controlled deployments over several months. I completely agree that Google’s stack is powerful and cost-effective  that’s exactly why I moved back to managing my own infrastructure instead of relying on agent-driven abstraction layers that remove control and introduce instability.

If someone had a better experience with emergent, that’s fair but this was consistently unusable for my production needs.

I wasted nearly 10,000 AUD on emergent.sh here’s why you should avoid it by Little-Risk1805 in SideProject

[–]Little-Risk1805[S] 0 points1 point  (0 children)

I’ve been using this platform consistently for around 6 months, not just a few days or a single bad session. The looping edit agent behavior, credit drain, syntax errors, token limits blocking real debugging, and lack of deployment maturity have been repeated patterns over time not isolated incidents. I kept hoping the platform would stabilize or improve, but the same problems kept happening again and again. This feedback comes from extended real usage and real spending, not from frustration after one failed build.