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Why treating AI as a feature leads to fragile products — and how to design it as a system instead.

Why most AI tools fail — and how to turn simple prompts into meaningful, usable outputs.

Best practices for adding AI into existing systems without unnecessary complexity.

The quality of AI results depends on how you design inputs, context, and constraints.

Turning unstructured data into structured outputs that can actually be used in products and workflows.

What changes when you move from simple use cases to production-level AI systems.

And how structure, formatting, and consistency make the difference.

Best practices for integrating AI into existing systems without breaking your stack.

How AI can replace repetitive processes with structured, automated systems.