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expertOpenAIAnthropic

A customer wants a deep-research agent over their private docs and the open web. Design it so stakeholders trust the citations.

Deep-research agents run unsupervised for twenty minutes and their report goes straight to an executive. The failure mode is not a crash, it is confident citations that do not support the claims. Most candidates design the retrieval and skip the verification pass, the run budget, and the freshness story.

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

Deep-research agents run unsupervised for twenty minutes and their report goes straight to an executive. The failure mode is not a crash, it is confident citations that do not support the claims. Most candidates design the retrieval and skip the verification pass, the run budget, and the freshness story.

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FEDITOR'S NOTE

The senior signal is treating trust as a verification problem, not a prompting problem: a dedicated citation pass that re-opens each cited source and checks it against the final draft, per-claim provenance rendered for the reader, and a stated freshness window. Strong candidates also route the private corpus through the customer's own permission model (never a side index that ignores ACLs), allowlist and snapshot web access, and cap the run's token and subagent budget in the orchestration layer. Watch for candidates who quote the multi-agent quality gain without the token cost, or who treat 'no support found' as something to hide rather than the behavior that earns trust.

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