planning
Applied AI interview questions tagged planning, across every topic.
4 questions · 0 unlocked for you
Concepts behind "planning"
The curriculum that explains the ideas these questions test.
Core
Agent Design Patterns: ReAct, Plan-and-Execute, ReflectionThese are the named control-flow architectures for LLM agents: ReAct interleaves reasoning and actions in a tight loop, plan-and-execute decomposes the task up front and then runs the steps, and reflection adds a self-critique pass that revises output. Each trades latency, token cost, and robustness differently. Applied AI interviews probe this to see whether you pick a pattern from task structure rather than defaulting to one loop for everything.🤖 Retrieval & AgentsSign in
Core
Agentic and Corrective RAGStandard RAG retrieves once and generates; agentic RAG wraps retrieval in a loop so the model decides whether to retrieve, what to query, evaluates the results, and retrieves again until it has what it needs. Corrective RAG adds a grader that checks retrieval quality and takes corrective action (re-retrieve, web search, or discard) when the context is poor. Applied-AI interviews probe it because complex, multi-hop questions defeat single-shot RAG, and self-correcting retrieval is the fix, at the cost of more calls and agent-reliability concerns.🤖 Retrieval & AgentsSign in