In a recent LinkedIn post, 🌀 Luca Rossi highlights the increasing importance of behavioral interviews in the tech industry, particularly as artificial intelligence continues to automate certain technical tasks. Rossi, who recently spoke with Austen McDonald, a former hiring committee chair at Meta and author specializing in behavioral interviews, argues that engineers often underinvest in preparing for these crucial conversations.
Rossi shares McDonald’s thesis that as AI commoditizes technical skills, the emphasis on behavioral competencies will only grow. This shift necessitates a more rigorous approach to behavioral interviews, a preparation step that many engineers currently neglect. According to Rossi, the core of these interviews lies not in recounting entertaining anecdotes, but in demonstrating repeatable behaviors.
“There’s always a question behind the question — interviewers aren’t looking for entertaining stories. They’re assessing repeatable behaviors like how you collect data, resolve conflicts, or communicate decisions.”
The Shifting Landscape of Tech Interviews
🌀 Luca Rossi points out that the traditional focus on purely technical prowess is evolving. With AI capable of handling many coding and implementation tasks, companies are increasingly looking for candidates who possess strong soft skills and strategic thinking. This makes the behavioral interview a primary tool for assessing these critical attributes.
Understanding the Interviewer’s Goal
As Rossi explains, interviewers are not simply seeking stories; they are probing for evidence of specific, consistent behaviors. These include how a candidate approaches problem-solving, manages conflicts, communicates complex information, and handles ambiguity. The ability to demonstrate these actions repeatedly is a key indicator of future performance.
“The #1 mistake is not enough actions — candidates skip over how they broke down problems, built plans, and communicated results. Instead, that’s the part interviewers care about most.”
Strategic Preparation for Behavioral Interviews
To effectively prepare, Rossi advocates for a bottom-up approach rather than a top-down one. This involves identifying core career stories and then mapping them to the key signal areas that hiring managers look for, such as scope of responsibility, ownership, ability to handle ambiguity, and perseverance. This method ensures that preparation is targeted and relevant.
Beyond the STAR Method
🌀 Luca Rossi also suggests an alternative to the commonly used STAR (Situation, Task, Action, Result) method. He proposes the CARL (Context, Actions, Results, Learnings) framework. This approach, he argues, is simpler yet richer, incorporating a reflection layer that can showcase a candidate’s seniority and growth mindset.
“Use CARL, not STAR — Context, Actions, Results, Learnings is simpler and richer. It adds a reflection layer that showcases seniority and growth mindset.”
The Impact of AI on Hiring
The rise of AI is a significant factor influencing the future of tech hiring, according to Rossi’s post. As AI takes on more routine implementation tasks, companies will place a higher premium on end-to-end ownership, adaptability, and cultural fit – all areas that are effectively assessed through behavioral interviews.
“AI is raising the stakes — as AI handles more implementation, companies will increasingly assess end-to-end ownership, adaptability, and cultural impact — all surfaced in the behavioral round.”
In conclusion, 🌀 Luca Rossi’s recent LinkedIn post, drawing on insights from Austen McDonald, underscores the critical need for engineers to dedicate more time and strategic effort to preparing for behavioral interviews. As the technological landscape evolves, these skills are becoming paramount for career advancement in the tech sector.
📝 About This Content
This article is based on insights shared by 🌀 Luca Rossi on LinkedIn.
📅 Originally posted on February 20, 2026 | View original post on LinkedIn →