few shot
Applied AI interview questions tagged few shot, across every topic.
2 questions · 0 unlocked for you
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 separated instructions and untrusted data, not ad-hoc strings. Applied-AI 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 asks the model to 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 reflect the model's actual computation. Applied-AI 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