If this review feels uncomfortable, consider it entirely fictional — a personal interpretation only.
I was interviewed by a relatively inexperienced manager in his first leadership role. Early in the conversation, he spoke at length about his own marketability (claiming multiple cybersecurity companies were eager to hire him) and about the company’s culture (“everyone here is humble and sweet”).
The technical design portion was standard and somewhat unoriginal. The TypeScript interfaces he provided revealed unfamiliarity with asynchronous programming, and I got the impression he had not been coding regularly. Whenever I attempted to clarify or dive deeper into technical considerations — something most interviewers value — he appeared disengaged and repeatedly asked to skip explanations. When I discussed topics such as fault tolerance, health checks, or partition sizing to align with the time constraints, he suggested these were “unimportant” and redirected me to move on. The overall atmosphere felt rushed, with a “let’s just get this over with” vibe. He wiped the whiteboard immediately after I finished, as if it was an evidence.
He concluded with “Ahla pitaron” (“great solution”) and walked me out.
Feedback for Upper Management:
From the moment I arrived, the operational experience felt disorganized. My elevator pass did not work, and the receptionist did not open the door — creating an impression of a workplace running on autopilot, where everyone is relaxed to the point of disengagement.
Regarding the interview process: scaling an organization requires trust, but trust must be paired with validation. People have personal motives and biases, conscious or not. Appearing “sweet and humble” in front of one’s manager is not a substitute for professionalism or good judgment. Bias tends to reinforce itself — for example, interviewers from elite institutions often (consciously or unconsciously) prefer candidates with similar backgrounds, and the reverse is also true. Introducing evidence-based validation mechanisms (as opposed to: emotional-based) could significantly improve integrity.
It is becoming increasingly common for companies to use AI as an interview supervisor, especially in technical assessments. AI can post-process audio or video, compare the neutral output against the human interviewer’s evaluation, and highlight inconsistencies (“Please rank this candidate/interviewer from 1–100 across the following categories, benchmarked against prior Hires / interviewees for the same role…”).
A 1-on-1 interview is a fragile setup: easy to omit context and shift narratives. Human judgment still matters, but having objective output in your records is essential imo. Particularly when headcount has grown rapidly.
