The Problem With Building AI Apps Today
· Avery NXR
Building AI apps today looks easy.
Connect to a model. Send a prompt. Get a result.
But that simplicity hides deeper problems.
The Illusion Of Simplicity
At first, everything works.
Outputs look good.
The system feels powerful.
But as soon as you add complexity, things change.
Where It Starts Breaking
As you build more:
Prompts become harder to manage Outputs become inconsistent Workflows become unclear
You start adding patches.
More prompts. More checks. More logic.
The Real Issue
The problem isn’t the model.
It’s the lack of structure.
There’s no clear system defining how everything should work together.
Why This Doesn’t Scale
Without structure:
Every feature adds complexity Every change introduces risk Every edge case breaks something
The system becomes fragile.
What’s Missing
AI development today lacks:
Defined workflows Controlled execution System-level design
Without these, you don’t have an application.
You have a collection of prompts.
Final Thought
Building AI apps is easy.
Building reliable AI systems is not.
And that’s the gap we’re trying to solve.