Problem: QA interviews don’t reflect real QA work
Most QA interviews still focus on:
- generic theory questions
- memorized definitions
- the same question list for every project
As a QA Lead, I kept running into the same problems:
- strong candidates failing interviews because questions were too abstract
- weaker candidates passing by answering theory well
- interviewers improvising instead of following a clear structure
- important project risks never being discussed
The biggest gap:
interviews rarely reflect how QA will actually work on this specific product.
Agent welcome / intro screen
Solution: a QA Interview Agent that starts with analysis, not questions
I built an AI QA Interview & Evaluation Assistant to support structured, evidence-based interview preparation.
This agent is not meant to:
- replace interviewers
- make hiring decisions
- auto-score candidates
Instead, it helps QA Leads and Hiring Managers:
- analyze role + project requirements
- identify real risks and weak spots
- turn that context into a clear interview plan
Agent instructions / role definition
How the agent works (step by step)
1. It collects real context, not just a role title
The agent asks for:
- candidate CV
- project domain and business logic
- must-have vs nice-to-have requirements
- team setup and constraints
- release pace and risk level
If information is missing, it:
- asks concise clarifying questions
- or proceeds with clearly stated assumptions
Clarifying questions / inputs
2. It analyzes before generating anything
Before writing interview questions, the agent:
- summarizes the candidate’s background
- highlights potential risks and gaps
- maps project requirements to real QA responsibilities
Examples:
- complex calculations → edge cases, rounding, VAT
- manual-only team → regression ownership
- high financial impact → escalation and documentation
CV summary + risks / gaps analysis
3. It builds a structured interview plan
Instead of a flat list, the output is a full interview plan:
- 30–50 questions (configurable)
- grouped by real QA responsibility areas
- aligned with project risks and role expectations
Typical sections:
- QA fundamentals & mindset
- Test design & edge cases
- Regression & release testing
- Documentation & requirements analysis
- Data & calculations validation
- Collaboration & ownership
- Scenario-based problem solving
Interview plan structure
4. Every question is intentional
Each question includes:
- what competency it checks
- what a Middle-level signal looks like
- a follow-up probe for deeper validation
This helps interviewers:
- stay consistent
- reduce subjectivity
- adapt depth based on candidate answers
5. Optional: table format for live interviews
The final interview plan can also be generated as a table, ready to use during the interview:
- Category
- Question
- Competency checked
- Middle-level signal
- Follow-up probe
This works well for:
- panel interviews
- shared interview docs
- interview calibration
Table view
Why this approach worked better for me
Using this structure helped me:
- focus interviews on real product risks
- ask fewer but higher-quality questions
- feel more confident in decisions
- spot gaps that generic interviews missed
Ask for feedback 🙌
This agent is still in the testing and iteration phase.
I’d love feedback from:
- QA Leads
- Hiring Managers
- anyone who conducts technical interviews
If you’re curious:
- try it
- skim the structure
- tell me what feels useful and what doesn’t
Your feedback will directly influence the next iteration.
Link here: QA Interview Questions Generator
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