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Browse 3 real-world technical and behavioral interview questions about Guardrails. Review scenarios, edge cases, and architectural best practices.
Indirect prompt injection is when instructions hidden in content the model reads are followed as if they came from you. Instructions and data share one token sequence, so there is no complete fix and the defence is architectural: least-privilege tools, filtered output, and human approval for side effects. It also connects llm security to the point an interviewer is testing.
Enforce step, token, wall-clock and monetary budgets in the orchestrator rather than in the prompt, detect repetition and lack of progress as separate conditions, and require an approval bound to specific arguments before any irreversible action. Exhausting a budget should hand back partial work, not vanish.
Streaming commits you to the response before you have seen it: the status code is already sent, any check that needs the whole output now runs after the user has read part of it, a mid-stream failure has no clean retry, and an abandoned tab keeps generating tokens you pay for. It also connects llm serving to the point an interviewer is testing.