AI

Creating vector representations for semantic search, recommendations, and retrieval.

Designing data flow, model calls, tools, memory, and evaluation boundaries.

Running local models, choosing model sizes, managing inference servers, and monitoring resources.

Connecting agents to tools through Model Context Protocol clients and servers.

Diagnosing poor AI outputs by adjusting instructions, context, examples, and constraints.

Structuring instructions, context, and examples for reliable AI outputs.

Connecting LLMs to external knowledge with retrieval, ranking, and grounded responses.