Secure Agent Observability in a customer onboarding assistant
Senior security interview question on Agent Observability within AI Agents.
Read full explanationAGENTS.md Interview Questions & Best Practices
What belongs in AGENTS.md, why concise files win, company-wide templates, and securing agent config against repo attacks.
AGENTS.md is becoming the standard onboarding file for coding agents — a README written for Claude Code, Cursor agents, Codex CLI, and internal runtimes.
Interviews ask what belongs in the file, how to keep it short, how to roll it out across hundreds of repos, and how to stop attackers from poisoning AGENTS.md or related configs (.mcp.json, .cursor/rules).
Research nuance to cite: AGENTS.md is valuable when concise and focused; oversized instruction dumps can raise cost and hurt success rates. This guide covers best practices and secure AGENTS.md — high-signal topics for AI tooling and platform roles.
AGENTS.mdBest PracticesSecurityContext Engineering
Questions in this guide
Deep explanations with architecture diagrams for every question below.
Secure Agent Security in a customer onboarding assistant
Senior security interview question on Agent Security within AI Agents.
Read full explanationSecure Agent State in a customer onboarding assistant
Staff security interview question on Agent State within AI Agents.
Read full explanationSecure Infinite Loops in a customer onboarding assistant
Mid-Level security interview question on Infinite Loops within AI Agents.
Read full explanationSecure Planning in a customer onboarding assistant
Mid-Level security interview question on Planning within AI Agents.
Read full explanationSecure Tool Use in a customer onboarding assistant
Junior security interview question on Tool Use within AI Agents.
Read full explanationEvaluate Agent Security quality in an AI search product
Senior evaluation interview question on Agent Security within AI Agents.
Read full explanationExplain Agent Security with a production scenario
Senior conceptual interview question on Agent Security within AI Agents.
Read full explanation