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Design a human-feedback data platform to collect the preference data that trains and aligns your models.

RLHF and evals are only as good as the preference data behind them, and that data is generated by humans whose quality varies wildly. The platform that produces trustworthy labels is itself a serious system. Here is its design.

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

RLHF and evals are only as good as the preference data behind them, and that data is generated by humans whose quality varies wildly. The platform that produces trustworthy labels is itself a serious system. Here is its design.

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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.Applied AI Engineering·The interviewPremium12mTurning this course into a study planA concrete four-week plan mapping the seven modules onto the question bank, plus what to do differently if your interview is next week rather than next month.
UP NEXT ON YOUR JOURNEY
Next in this trackDesign a conversational analytics agent that answers business questions over a data warehouse in natural language.Next in this trackDesign a cost-control and quota system for an internal LLM platform serving many teams.Next in this trackDesign a system that monitors the quality of millions of AI support conversations and flags the bad ones.
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