How to Create a Standardized Interview Process

What’s the biggest challenge in recruiting right now? It’s not sourcing. It’s not volume. It’s not even alignment. It’s that the talent bar is higher than ever, and most interviewers haven’t been trained to assess against it. In Q1, I spoke with well over 50 Talent leaders, CEOs, hiring managers, and interviewers. And in nearly every conversation, the same two themes came up: “We have a very high talent bar.” “But our interviewers aren't skilled in interviewing.” The irony. 😵💫 It’s not that interviewers don’t care or aren’t capable. Most haven’t been taught how to assess consistently, or don’t interview often enough to build the skill. And most of the teams I spoke with don’t have ongoing support in place. It’s usually one training, and then interviewers are off to the races. Without structure or coaching, it’s easy to miss real signal. Meanwhile, candidates are expected to deliver crisp, strategic, high-impact answers under pressure, often in fast-paced conversations with unclear prompts and no follow-up. I’ve seen candidates passed on for being “too vague,” only to review the interview (thank you AI notetakers) and realize the question was layered, unclear, and never clarified. The candidate didn’t fail. The process did. So how do we actually fix this? Here’s what’s moved the needle for me: ✅ Get specific about what you’re hiring for Not just the title. What outcomes will this person need to deliver in 90 days? Six months? A year? Hire for the anniversary date, not just the start date. That’s the bar and interviewers need to be aligned on it. ✅ Assign focused areas to interviewers No more “everyone assess for strategic thinking.” Divide ownership. Go deep, not wide. This leads to stronger signal and better debriefs. ✅ Calibrate your scorecards Don’t just hand out a 1–4 scale and call it structured. Define what a 2 looks like. Define what makes someone a 4. Use real rubrics to make it objective. ✅ Coach with context, not just opinion Tools like BrightHire and Metaview can help you spot unclear questions, missed signal, and where interviewers need support. ✅ Use your ATS to scale interviewer readiness ATS's like Ashby makes this easy. You can track interviewer pools, assign shadows, and move people through training stages automatically. No spreadsheets. No guesswork. ✅ Debrief with evidence If the feedback is “not strong,” dig deeper. What did they say? What was missing? What would’ve made them a “strong hire”? Make sure your feedback reflects real signal, not just personal impression. Interviewing isn’t instinct. It’s a skill. One that needs to be continuously developed. And if we’re serious about hiring great talent, we have to enable the people responsible for identifying it. What are you doing this year to level up your interviewers? 👇🏼

I’ve been getting a ton of DMs and comments on my last post asking about the AI prompt I used to build an executive hiring assessment and interview plan. Not surprising, executive search is still broken in a lot of places. Too many interviews rely on instinct, vague questions, or outdated playbooks. So instead of sending my prompt to everyone individually, I figured I’d walk through how to build one yourself. Most prompts fall flat because they’re too shallow. A strong AI prompt for executive hiring should be treated like an API request: structured, layered, and loaded with context. Here’s how to build one that actually works: 1. Start with Context Give the AI business and hiring context, not just the role title. “You’re designing an interview plan for a Series B SaaS company hiring a VP of Marketing to scale pipeline efficiency and launch EMEA.” 2. Provide Source Material Feed the AI what you already have. Include: - Job description - Job ad - Talent Ladder - Company values - Success profiles or leveling framework - Team charter or hiring manager notes - Previous document structures that have worked in the past - Anything that hasn’t worked in the past Label each section clearly. The more signal you give, the more signal you get. 3. Define the Output Format Tell the AI what you want. Example: “Build a 5-stage interview loop. For each stage, include: - Interview title and purpose - Core competencies - Suggested questions (behavioral + scenario-based) - Evaluation criteria - Interviewer profile - Timebox in minutes” Structure = clarity. 4. Add Constraints + Nuance Make the AI smarter by telling it what to avoid and what to emphasize. “Avoid generic leadership questions. Emphasize org design, systems thinking, and cross-functional collaboration. Deprioritize ‘culture fit’ in favor of ‘culture add.’” 5. Layer in Iteration AI isn’t one-and-done. After the first output, ask: “Now revise this plan to reflect our values more clearly.” “Make this inclusive of candidates from non-traditional backgrounds.” “Sharpen the rubric for strategic thinking.” Bonus tip: Once you’ve dialed in your prompt structure, try formatting it in YAML. It makes the logic cleaner, easier to reuse, and more adaptable for tools like Gemini or ChatGPT. If you build your prompt with this kind of structure, you’ll stop getting interview plans that look smart and start getting ones that actually work. And yes, AI can do incredible things 💜 but only if you feed it the right ingredients. Have questions or want to troubleshoot your own prompt design? Happy to trade notes in the comments. #executivesearch #promptengineering #AI #talentacquisition #recruiting

I used to think the hardest part of hiring was sourcing candidates. Turns out, most firms lose the best talent before interviews even begin, because of subtle bias in job descriptions and unstructured interviews. Here’s what I learned: 1. Unbiased Job Descriptions Matter Gender-neutral language: Replace “he/she” with “they/their,” and swap masculine/feminine-coded words for neutral alternatives like “goal-oriented” or “team-player.” Clear, accessible language: Avoid jargon, acronyms, and long lists of “must-haves” that unintentionally filter out qualified candidates. Inclusive titles: Use “software engineer” instead of “rockstar coder,” “firefighter” instead of “fireman.” 2. Structured Interviews Reduce Bias Standardized questions: Ask every candidate the same questions in the same order to avoid “likability bias.” Scoring rubrics: Grade answers objectively on merit, not gut feeling. Behavioral + situational questions: Focus on skills and past performance, not shared backgrounds. Diverse panels & limited chit-chat: Multiple perspectives + minimal small talk reduce affinity bias. Here’s the kicker: these simple practices don’t just make hiring fairer, they make it smarter. Firms using inclusive, structured approaches attract more qualified, diverse candidates, shorten time-to-hire, and build teams that actually perform. If you’re still relying on old-school job posts and free-flow interviews, you’re leaving talent and revenue on the table.

There is a right way to run an interview process (in the tech industry). And it’s not up for debate. Three stages. That’s the number. Not five. Not “as many as it takes.” Three. This isn’t a theory. It’s a model distilled from decades of hands-on work designing, executing, and measuring hiring processes for some of the most recognized companies in the world. Here’s how it works: Stage One: The Skilled Recruiter Screen - Not just anyone with “recruiter” in their title. - Someone who can source, match, and compel—armed with data, not buzzwords. - This call (30 min) aligns on what the candidate wants, breaks down environmental attributes, and surfaces cultural + functional fit. Stage Two: The Deep Dive - Think of Stage One as the X-axis—wide-ranging. Stage Two is the Y-axis—deep and direct. - Led by the hiring manager (ex: CTO), this is a 45-60 min session built on Stage One’s foundation. - It should explore decision-making, collaboration, execution, and real alignment to the roadmap ahead. Stage Three: The Final Round - This isn’t just a “panel.” It’s a curated sequence: - Design Interview with a senior peer - Cross-functional Interview with a partner - Reverse Interview (yes, the candidate asks the questions—30–40% of the time) - Optional: CEO or founder convo, if and only if it adds real value. You want to interview for culture? Do this: Let the candidate ask real questions. That’s where culture shows up. Score for values (like transparency, collaboration, data use) across every stage—not with “culture fit” questions, but with observable behavior and evidence. This process works. It’s repeatable. It gives candidates clarity. It gives companies signal. And you can run it—start to finish—in 10 to 20 business days, consistently. If you’re still doing the 5-7 round circus with no structure and poor alignment? Give this a shot. You’ll never go back.

One of the most exciting aspects of writing "Make Work Fair" with my coauthor, Iris Bohnet, has been turning behavioral science insights and research evidence into practical, data-driven organizational design. Today, I want to share a powerful tip for improving hiring processes: structured decision-making. Unstructured interviews are notoriously poor predictors of job performance and rife with bias. But by adding structure to our hiring processes, we can significantly improve both fairness and —importantly—effectiveness. Here's a simple three-step approach you can implement: 📋 Define clear evaluation criteria before reviewing any applications. 🔢 Use a standardized scoring rubric for all candidates. ↔️ Compare candidates’s answers horizontally (all answers to question 1, then all answers to question 2, etc.) rather than vertically (one full candidate at a time). This method helps mitigate the impact of unconscious bias by focusing our attention on relevant qualifications rather than subjective "fit" or first impressions. In my research, I've seen organizations implement similar approaches with promising results. While specific outcomes vary, the trend is clear: structured hiring processes tend to lead to more diverse candidate pools and better alignment between job requirements and new hire performance. Have you tried structured hiring in your organization? What was your experience? #HiringPractices #WorkplaceFairness #DataDrivenHR #MakeWorkFairBook