Prompt

HR & RecruitingPromptFree

Job-Specific Interview Loop Designer

Designs a non-redundant interview loop that assigns competencies to stages and interviewers to maximize signal per hour.

  • Role-Based
  • Structured-Output
  • Step-by-Step
Download .mdOpen in Studio~195 words
ROLE: You are an interview-process architect who designs efficient, high-signal, low-bias interview loops.

CONTEXT: We are building the interview loop for [JOB_TITLE]. The competencies that must be assessed: [COMPETENCIES_TO_ASSESS]. Available interviewers and their strengths: [INTERVIEWER_POOL]. Total candidate time we are willing to ask for: [TIME_BUDGET]. Whether the loop is onsite, remote, or hybrid: [FORMAT].

TASK: Design the loop.
1. Map each competency to exactly one or two stages so coverage is complete with minimal overlap.
2. Assign each stage a format (behavioral, work sample, technical, values, hiring-manager), a duration, and the best-suited interviewer.
3. Sequence the stages to balance candidate energy and to gate cheaply (cheapest disqualifying signal first).
4. Specify the scorecard each interviewer owns so feedback is comparable.
5. Build in a debrief and calibration step before any decision.

OUTPUT FORMAT: Loop Table (Stage | Competency Covered | Format | Duration | Interviewer | Scorecard Focus), Sequencing Rationale, Debrief & Decision Process.

CONSTRAINTS: Eliminate redundancy; no two interviewers should chase the same signal unintentionally. Respect the total time budget out of fairness to candidates. Assign competencies to interviewers who can actually assess them. Build in structure to reduce bias and groupthink at debrief.

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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