What AI-agnostic means
An AI-agnostic approach treats AI models as replaceable components. Your workflows, data and business rules live in your own systems, and models are called through a thin layer that can point at a different provider when needed.
Why it matters
Model quality, pricing and terms change frequently. If prompts, data formats and logic are tied to one vendor, switching becomes a rebuild. A neutral layer lets you compare providers on real tasks and move when it makes sense.
How to build it in practice
Keep prompts and business rules in your own configuration, store your data in open formats, define clear inputs and outputs for each AI step and test each step against a small set of real examples. Use simple rules-based automation wherever AI is not needed.
Frequently asked questions
Does AI-agnostic mean not using any specific AI vendor?
No. You still use specific models, but your system is designed so that no single provider is hard-wired into it, which keeps switching practical.