Why move a mountain when you can just swap a brick? The first instinct for many MLOps enthusiasts is to deploy a full model for every specific task—but that’s an infrastructure nightmare.

The smarter way? Build your ML like a Lego constructor. In this talk, I’ll show you how to take one powerful foundation like Gemma 3 and "snap on" tiny, specialized LoRA adapters to handle 100 different tasks. You get all the intelligence of a massive LLM without the heavy lifting

What we will explore:

- Training LoRA adapters instead of re-training the whole model.
- Using TGI to hot-swap these specialized skills in milliseconds.
- Orchestrating it all with GCP Inference Gateway to maximize efficiency