tools
Applied AI interview questions tagged tools, across every topic.
2 questions · 0 unlocked for you
Concepts behind "tools"
The curriculum that explains the ideas these questions test.
Core
Prompting vs RAG vs Fine-TuningGiven an LLM use case, the senior move is matching the technique to what is missing rather than defaulting to one. Need external or changing knowledge? RAG. Need a specific behavior, format, or skill? Fine-tuning. Need to take actions or use live systems? Tools/agents. Just need better instructions? Prompting. They combine, and you escalate from cheapest (prompting) to most involved (fine-tuning). Applied-AI interviews probe it because choosing wrong wastes months, fine-tuning to inject changing facts is the classic mistake.🧠 Foundations of LLMs & GenAISign in
Core
Model Context Protocol (MCP)MCP is an open client-server standard that lets an agent connect to external tools, data, and prompts through a uniform interface, so one integration works across many hosts instead of writing bespoke glue per model. Servers expose tools, resources, and prompts with typed schemas; clients discover and call them at runtime. Applied AI interviews probe it because integration plumbing, not model quality, is usually what blocks an agent from shipping.🤖 Retrieval & AgentsSign in