few shot
AI, ML & GenAI interview questions tagged few shot, across every topic.
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Concepts behind "few shot"
The curriculum that explains the ideas these questions test.
Foundational
Prompt EngineeringPrompting is the cheapest, fastest way to steer an LLM: clear instructions, few-shot examples, explicit output format, and the right context. It is the first technique to try before reaching for RAG or fine-tuning, and in production it means versioned, tested prompt templates with instructions kept separate from untrusted data, not ad-hoc strings. AI, ML, and GenAI engineer interviews probe it because most LLM features ship on prompting alone, and because sloppy prompts are a top source of unreliability and injection risk.🧠 Foundations of LLMs & GenAI
Foundational
Chain-of-Thought and In-Context LearningIn-context learning is the ability to perform a task from instructions or a few examples in the prompt, with no weight updates. Chain-of-thought prompting has the model reason step by step before answering, which markedly improves multi-step problems (math, logic, multi-hop questions). The catch is that the stated reasoning is not guaranteed to mirror the model's actual computation. AI, ML, and GenAI engineer interviews probe it because it is the cheapest accuracy boost on hard tasks, and because over-trusting the visible reasoning is a real pitfall.🧠 Foundations of LLMs & GenAI