react
AI, ML & GenAI interview questions tagged react, across every topic.
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Concepts behind "react"
The curriculum that explains the ideas these questions test.
Foundational
Agents and Tool UseAn agent is an LLM in a loop that can take actions through tools: it reasons, calls a tool (search, a database, code, an API), observes the result, and loops until finished. Tool calling works because the model emits a structured request that your code executes, the model itself never runs anything. The upside is doing real work; the cost is reliability and the safety surface (an agent that can act can act wrongly). Applied-AI interviews cover it because agents are where LLMs meet real systems.🤖 Retrieval & Agents
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 breaks the task down up front and then runs the steps, and reflection adds a self-critique pass that revises output. Each strikes a different balance among latency, token cost, and resilience. Applied AI interviews test this to see whether you choose a pattern from task structure rather than falling back on one loop for everything.🤖 Retrieval & AgentsSign in