A live-coding round that tells apart engineers who have shipped agents from those who have only read about them. Interviewers want a genuine plan-act-observe loop, tools that query a real SQL database, guardrails that block the obvious failures, and a concrete evaluation plan, rather than one prompt masquerading as an agent.
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Build a customer-support agent over a fake product/SQL database: tool-calling, retrieval, and a control loop.
A live-coding round that tells apart engineers who have shipped agents from those who have only read about them. Interviewers want a genuine plan-act-observe loop, tools that query a real SQL database, guardrails that block the obvious failures, and a concrete evaluation plan, rather than one prompt masquerading as an agent.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
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Next in this trackBuild a small in-memory document indexer and retriever from scratch (inverted index + BM25), then add a vector option.Next in this trackHow do you operate a multi-vector (ColBERT-style) index in production without it blowing up storage?Next in this trackHow do you decompose a complex query into sub-queries for retrieval, and when does it backfire?
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