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Why should input validation and structured error messages be returned from agent tools rather than b...

What is the 'overloaded tool' anti-pattern and why does it hurt agent reliability?

Describe the three phases of one ReAct iteration.

Why are stop conditions more important than the loop itself in a ReAct agent?

What is the plan-then-execute pattern and how does it differ from ReAct?

What does a supervisor agent do in a multi-agent system, and what does it NOT do?

What should a handoff context object contain when one agent transfers control to another?

When does peer-to-peer agent communication make sense over a hub-and-spoke supervisor?

Name the four types of agent memory and briefly describe each.

What is 'summarization on overflow' and what is its main tradeoff?

What are the four levels of agent evaluation and what does each measure?

What are input, output, and action guardrails in an agent system?

What pattern does Build a tool registry with schema validation teach?

What pattern does Implement a ReAct reasoning loop teach?

What pattern does Add retry and fallback logic to tool calls teach?

What pattern does Parse structured outputs with error recovery teach?

What pattern does Conversation memory manager with token budgeting teach?

What pattern does Multi-agent handoff protocol teach?

What pattern does Agent evaluation harness teach?

What pattern does Cost-tracking middleware for agent tool calls teach?

When does an agent architecture add value, and when is it just complexity?

How would you design a tool schema for an LLM agent?

Explain the ReAct pattern and when to use it.

How do you manage agent memory to stay within context limits?

What is MCP (Model Context Protocol) and why does it matter for AI engineers?

How would you evaluate an agent's performance in production?

Compare supervisor vs peer-to-peer multi-agent architectures.

What are the three things that make or break a tool schema for an LLM agent?