The Last Technical Interview

Limits of Current Technical Interviews

• Many commenters agree interviews are statistically poor predictors of on‑the‑job performance: same candidate gets opposite outcomes, scores don’t correlate well with later success.
• Psychometrics concepts are invoked: interviews lack reliability (different interviewers disagree) and thus can’t have high validity (weak correlation with real ability).
• Big companies’ stated goal of minimizing “bad hires” is seen as sensible, but the tools they use (leetcode-style loops, opaque committees) are viewed as mostly random filters.

Alternative Assessment Models

• Strong support for multi‑month “provisional employment” / internships / co‑ops as the highest‑quality signal: real work in real conditions.
• Critics argue this is only practical for unemployed or financially secure candidates; few will quit a stable job for a speculative “maybe” offer.
• Some note that regular employment already functions like provisional employment via probation periods and easy firing (in some jurisdictions).

Work-Sample and Take-Home Tests

• Many see work-sample tests as the practical “gold standard”: closer to real work, more controlled, less stressful, and often more time‑efficient than full onsite loops.
• Objections: they can demand many unpaid hours, discriminate against people with limited free time, and are now easily solved or boosted via AI tools.
• Some companies counter this by: (a) strict time budgets, (b) in‑office work samples, (c) evaluating how candidates explain and extend AI‑assisted work.

Organizational and Managerial Factors

• Several argue the real failure is organizational: conflict‑averse, weak managers don’t fire poor performers, so hiring must over‑optimize against bad hires.
• “Performance management” systems are described as arbitrary; anecdotes show both promotions despite missed goals and exits despite met goals.

Candidate Experience and Fairness

• A long personal story highlights repeated big‑tech rejections despite strong skills and intense preparation, leading to bitterness and suspicion of age/diversity bias and luck.
• Many see current processes as “nerd revenge” or hazing: heavy leetcode prep, opaque culture screens, arbitrary difficulty variation between candidates.
• There’s concern that filtering (ATS, recruiters) is more broken than the technical interviews themselves, with huge variance in recruiter quality.

Standardized Tests and Professionalization

• Some advocate standardized cognitive or aptitude tests as cheaper, more reliable tools; others fear political, ethical, and class‑stratification issues.
• Comparisons to trades: multi‑year apprenticeships and formal licensing are suggested as a model, including talk of software “building codes” and professional engineer certification.

Reputation / Stamp Proposals

• The article’s idea of “stamps” from campfire/provisional stints gets mixed reactions.
• Supporters like a portable, positive‑signal history; critics see it as effectively a public ledger of rejections and an additional, employer‑skewed hoop.

Meta Reactions to the Article

• Some praise the piece as an honest “kitchen confidential” about FAANG hiring dysfunction.
• Others view it as detached from real constraints (family, mortgages, current jobs) or as setting up a commercial product/agenda.
• Several emphasize that interviewing is inherently inexact; the goal should be “good enough and humane,” not perfect.