tools
AI, ML & GenAI interview questions tagged tools, across every topic.
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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). AI, ML, and GenAI engineer 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 connects an agent to external tools, data, and prompts through one uniform interface, so a single integration serves many hosts instead of bespoke glue written per model. Servers publish tools, resources, and prompts with typed schemas; clients discover and invoke them at runtime. Applied AI interviews test it because what usually keeps an agent from shipping is integration plumbing rather than model quality.🤖 Retrieval & AgentsSign in