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InterviewFlowAI provides three different strategies for sourcing interview questions. You can mix and match these approaches to build the perfect Interviewer workflow. Here is a breakdown of how Custom Questions, Resume Questions, and Skills Questions differ.

1. Custom Questions (Manual)

Custom Questions are static, pre-written questions that your team explicitly authors. The AI asks these exactly as programmed for every candidate.

When to use them

  • Behavioral interviews: “Tell me about a time you handled a difficult client.”
  • Core competencies: To ensure absolute consistency, every candidate receives the exact same fundamental question.
  • Predictable scoring: You clearly define what constitutes a “Strong (5)” and “Weak (1)” answer in the rubric.

Key characteristics

  • Static input: You write the question manually.
  • Strict rubric: Requires specific benchmarks (looking_for, strong_answer, weak_answer, weight).
  • Predictable consistency: The AI does not improvise the base question, keeping the interview track completely uniform.

2. Resume Questions (Dynamic)

Resume Questions rely on the AI’s ability to instantly read and analyze the candidate’s uploaded resume. Instead of asking a generic question, the AI generates questions tailored precisely to the candidate’s past work history.

When to use them

  • Verifying experience: Deep-diving into specific projects or promotions listed on standard resumes.
  • Tailored exploration: Discovering the depth of a candidate’s actual responsibilities versus what they simply listed on paper.

Key characteristics

  • Dynamic input: The AI generates the question on the fly based on the resume text and your generationInstructions (up to 4,000 characters).
  • Highly personalized: No two candidates will receive the exact same question.
  • Follow-up intensive: You can instruct the AI to heavily scrutinize gaps in employment or specific project claims.

3. Skills Questions (Dynamic)

Skills Questions are generated by the AI to specifically test a candidate’s technical knowledge or proficiency in particular tools and frameworks.

When to use them

  • Technical screening: Checking knowledge in languages like Python, React, or AWS.
  • Hard-skills verification: Ensuring the candidate actually knows the specific software ecosystem required for the role.

Key characteristics

  • List-driven: The AI generates questions targeting an explicit list of allowedSkills (up to 50 items) that you provide.
  • Adaptable: By enabling flexibleSkills, the AI can adapt its questions if a candidate steers the conversation toward a related but strictly unlisted skill.
  • Knowledge-focused: These questions act more like technical quizzes than behavioral scenario questions.

Summary Comparison

FeatureCustom QuestionsResume QuestionsSkills Questions
OriginManually written by youDynamically generated from the resumeDynamically generated from a skills list
ConsistencyExact same phrasing per candidateHighly customized per candidateTargets the same technical stack per candidate
Best used forCore competencies, behavioralDrilling into past experienceTechnical testing, hard-skills validation