In this episode of Whispered Hiring, Andy Mowat speaks with Alla Mezhvinsky, VP of People at Glean, about the preparation failures that derail executive searches before a single candidate is contacted. With deep experience leading talent acquisition at Instacart, Square, ClassPass, and Zynga, Alla brings a practitioner's view on what separates searches that close fast from searches that spin. Her frameworks are direct, field-tested, and built for the pace of high-growth companies. Topics discussed: Why not having a plan before opening a search is the single biggest hiring failure Alla sees. Without a defined talk track, role scope, value proposition, and at least directional comp, teams fail twice: they attract the wrong candidates, and when the right ones show up, they cannot engage them because they cannot answer basic questions about the role. How roles evolve faster than searches can close, and why scoping for today sets you up to hire the wrong person. In hyper-growth companies, a role that opens in Q1 looks materially different by Q3. Alla recommends thinking explicitly about what the team needs at 6, 12, and 18 months out, which is often a different candidate profile entirely. How AI has flipped the recruiting intake model. Rather than waiting on hiring managers to arrive with a fully formed brief, recruiting teams are now using AI to come to the intake meeting with a proposed job description and interview plan. The hiring manager iterates on a draft instead of starting from a blank canvas, compressing weeks of delay into a single session. The best answer ever given to the question of how long a search will take. An agency recruiter told a CEO: "I can guarantee I will present the right candidate to you within the first couple of weeks. What I can't guarantee is how long it will take you to realize it is the right candidate." Alla cited this as the clearest argument for doing alignment work before the search opens. Why AI has roughly doubled the number of applicants per role in under a year, and why the industry is still figuring out how to handle it. Alla referenced data from a recent talk showing twice as many applicants per role compared to the prior year. The volume is manageable. The challenge is doing it responsibly without rejecting strong candidates or removing the human from the decision. How the AI fluency question has completely inverted in 18 months. A year and a half ago, companies were designing interview processes to detect whether candidates used AI. Today, companies want confirmation that they can. The new test is whether AI is enhancing real expertise or masking a skills gap, and Alla's team runs live, real-time assessments instead of take-home case studies to find out. How Alla uses AI to turn candidate-provided references into targeted conversations. Her team feeds the full interview loop feedback into a prompt that generates reference questions built around exactly what the panel was still uncertain about, replacing generic endorsement calls with structured, context-driven conversations. ABOUT YOUR HOST: Andy Mowat has built GTM engines for top companies throughout his career. He led Revenue Operations and Demand Gen at four unicorns, including scaling from $10M to $100M ARR at both Upwork and Culture Amp, and helping guide Box and Carta through IPO scale. With a passion for connecting people, Andy has advised executives on their careers for years and launched Whispered to make searching for executive roles less intimidating. Learn more about about Whispered: www.whispered.com Interact with AI Andy: www.whispered.com/whisper-search