react
Applied AI 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 repeats until done. Tool calling works because the model emits a structured request that your code executes, the model never runs anything itself. The power is doing real work; the cost is reliability and the safety surface (an agent that can act can act wrongly). Applied-AI interviews probe 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 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