Interviewer Skills

This short pre-work primes participants for a workshop on unbiased, equitable interviewing techniques. Before the session starts, participants write down their own open questions about interviewing and identify a personal goal for what would make the workshop a success for them, setting a personal stake in the material to come.

This module introduces structured interviewing as a way to reduce bias and make more consistent, accurate hiring decisions. Participants examine the business case for good interviewing ??? including the real costs of mishires and case data (such as Virgin Media's candidate-experience study) showing how a poor candidate experience can damage a company's customer base and revenue. The framing draws on examples from companies like Postmates and Glossier, but the core ideas ??? treating candidates like customers and building structure into interviews ??? apply to any hiring process.

This module, part of the Interviewer Skills series, teaches interviewers how to evaluate candidates against a company's stated values rather than a subjective sense of "culture fit." Participants discuss the difference between "culture fit" and "culture add," examine how to translate written values into observable on-the-job behaviors and red flags, and consider the "Brown M&M" concept???using a small, consistent signal to surface evidence of a value or skill during an interview. Participants practice this through a paired listening exercise where they reflect back which company values their partner demonstrated while describing a recent challenge.

This module teaches a three-step framework for structured interviewing: defining the critical attributes a role requires, building evidence-based rubrics (Excellent/Good/Acceptable/Poor) for each attribute, and writing fair, inclusive questions that give candidates of all backgrounds a real chance to demonstrate those skills. Participants practice using a real job posting (Senior Software Engineer, Data Infrastructure) to draft attributes and rubrics, work through an Engineering Manager example to build an evidence-based scoring rubric, distinguish four question types (Behavioral, Situational, Factual, Skill Assessment), and rewrite flawed interview questions to remove bias and closed-ended framing. A dedicated exercise also has participants use an AI prompt to generate a structured interview plan from their own job description and critique the output.

This module examines how unconscious bias shows up in hiring and everyday workplace interactions, and gives participants concrete tools to counter it. Participants learn to identify four specific bias types???confirmation bias, similarity bias, groupthink, and stereotyping???through interviewing examples, then practice applying before/during/after interview safeguards and evidence-based evaluation to a hiring debrief scenario. The module also introduces a framework for navigating "hot moments" (charged conversations involving bias), covering both internal actions (attend to your reaction, understand the situation, choose a short-term response, consider a long-term response) and external actions (interrupt, question, educate, echo), which participants apply to a scenario involving overheard biased comments about a colleague.

This module teaches interviewers how to gather and evaluate evidence during candidate interviews using the CAR (Context, Action, Result) method, then translate that evidence into structured feedback. Participants practice writing follow-up questions that probe vague or theoretical answers for concrete evidence, and learn how to document findings in Greenhouse using rubric-based competency ratings (1-5) and overall candidate ratings (1-4). The module also covers preparing for interviews with a pre-interview checklist and distinguishing a scorecard "pass" rating from an actual hiring decision.

This module focuses on making the interview process welcoming and equitable for every candidate, whether the interview happens in person or virtually. Participants examine how job description language and unnecessary requirements (like degree or years-of-experience thresholds) can cause qualified candidates to self-select out, then discuss what makes candidates feel comfortable and "wow-ed" during real interviews. Participants compare the demands of in-person versus virtual interviews through a poll, share personal experiences of strong and weak candidate experiences, and finish with a "Wouldn't it be great if..." brainstorm to generate and prioritize concrete ideas for improving the interview experience.

This module prepares hiring managers to run the full hiring process as a "hiring partner" rather than just an interviewer: sourcing and referring candidates, structuring and staffing an interview panel, evaluating candidates on evidence rather than gut feel, and running an effective debrief to reach a hiring decision. Participants examine real referral language to distinguish strong referral practices from weak ones, review common interview biases (confirmation, similarity, groupthink, and stereotyping) so they can spot them in their own evaluations, and walk through post-interview steps including scorecard review, debrief facilitation using a Debrief Discussion Guide, and closing/selling candidates on the role.

This module prepares interviewers to run effective virtual interviews, covering what to do before, during, and after a video-based interview. Participants discuss current virtual interviewing practices and frustrations, then work through concrete techniques for setting up logistics and back-up plans, managing camera/screen setup, checking in with candidates, removing virtual sources of bias (lighting, background noise, pets, kids) from evaluation, replacing the in-person office tour with a compelling virtual pitch, and closing the loop with a post-interview note and immediate feedback. Participants close by reflecting on their own time management, tool use, and judgment calls from a recent virtual interview.

This module teaches interviewers how to prepare for and run an effective hiring debrief. Participants learn to review completed scorecards before discussion to spot disagreements, thin evidence, and open questions; build a debrief agenda from those findings; and run the discussion itself using an intake-form anchor, targeted questions, and practices that counter groupthink and gut-instinct decisions.