hardSierra Decagon OpenAI

Build a customer-support agent over a fake product/SQL database: tool-calling, retrieval, and a control loop.

A live-coding round that separates people who have shipped agents from people who have read about them. The signal is a real plan-act-observe loop, tools that hit an actual SQL database, guardrails that stop the obvious failures, and a concrete evaluation plan, not a single prompt that pretends to be an agent.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

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LEARN THE BACKGROUND

These lessons teach the material this question tests, in order and from the beginning.

Applied AI Engineering·Tools and your first agentSign in120mProject: give your retrieval system a toolTake the system you built in module 4 and let it act, not just answer. One tool, one bounded loop, a confirmation gate on anything irreversible, and an honest comparison against the version without a loop.Applied AI Engineering·The interviewPremium14mDriving the design conversationA design round is a conversation you are expected to lead, not a question you answer. This lesson is the shape that works, the four moments that decide the outcome, and the two classic ways strong candidates lose one.

UP NEXT ON YOUR JOURNEY

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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