If you’re a developer trying to break into AI, here’s the exact road map we’ve used to launch a dozen realworld projects.

First, define your problem clearly.
What exactly do you want your app to do?
Nail that down before you even think about AI.

Next, test the AI component manually.
Just use Chat GPT or any AI chat tool to solve one example of the problem.
Go back and forth until you get it right.
That shows you exactly what you need from the AI side.

Then choose your framework and platform.
For a compute-heavy logic intensive app, we might use Laravel.
If it’s more interactive and light on compute, we’ll choose Django.
This approach works whether you’re building for consumers or enterprises.
We’ve done both successfully.

After that, vibe code the infrastructure.
We start with vibe coding, telling the AI to build the basic app skeleton on that platform.
Then we step in and fine-tune the AI parts manually.

Finally, test exhaustively.
Use AI to help build a test plan and always start with the best, most powerful model.
Once everything works, run a cheaper model in parallel to see if you can cut costs without losing quality.

This isn’t theory.
This is exactly how we’ve launched multiple AI projects into the real world for both consumers and enterprises.

So, if you want real step by step AI build advice from someone who’s done it, follow along.