Les entretiens de dev ont changé…

Les entretiens de dev ont changé…

Developer interviews have changed…

Title history
  • Les entretiens de dev ont changé… — observed on 20261101-0157 UTC (YouTube)

by DevArt · View the channel on PSI

Humanities, Social Sciences & Thought Economics & Finance KJMVManagement of specific areasKJMV2Personnel and human resources management
🎙 DevArt 👥 19K 📅 November 16, 2025 ⏱ 15 min 👁 2K 📄 expert opinion 🧭 2026-11-01
Available in: English (current) Français

Keywords

interviewAILLMdeveloperadvice

Summary

In this video, Arthur, a former developer from Conto and PlayStation, shares five AI-related questions he encountered during recent job interviews. He emphasizes that companies are now testing candidates’ familiarity with AI tools and their ability to explain complex concepts simply. The first question asks candidates to self-rate their AI skills on a scale from 1 to 10; he recommends choosing 6 to avoid overclaiming. The second asks to explain ’large language model’ in one minute, focusing on simplification skills. The third asks for a concrete example of how AI saved time; he suggests preparing real cases. The fourth explores using AI to learn new technologies, such as leveraging comparisons to known tools like Redux to understand Zustand. The fifth asks for a time AI was detrimental, which he illustrates with examples of code duplication or unwanted changes. He advises being honest, avoiding the ’expert AI’ label, and setting clear boundaries with AI tools. The video ends with a call to share experiences in the comments.

166 words

Critical Evaluation

Value of the Information & Strength of the Argument

The value lies in offering practical, first-hand insights into the shifting nature of technical interviews, moving toward AI literacy evaluation. The argumentation is based on personal anecdotes and specific examples (e.g., rating 6, using Cursor, learning Zustand). The reasoning behind recommending a moderate self-rating (6) is coherent: it shows situated knowledge without inviting challenging follow-ups. The examples are concrete and relatable, making the advice actionable. However, the arguments are purely anecdotal, with no empirical evidence or broader data supporting the observations. The video’s strength is its authenticity and clear practical tips, but it lacks depth in analyzing underlying trends or potential counterarguments.

Scientific Rigor, Source Quality, Title Accuracy

The video offers no scientific rigor; it is a personal vlog-style discussion. No external sources are cited, only links to related videos on the channel. The title accurately matches the content, which centers on how dev interviews now include AI questions. The adequacy is good, without exaggeration. The video does not claim to be research or review; it is explicitly a personal account. The lack of sources is consistent with the format, but it limits the reliability of the general conclusions presented as ‘changing interviews’ – this is extrapolated from a limited personal experience.

211 words

Title / Content Match

The title accurately reflects the content: the video focuses on how dev interviews now include AI-related questions, illustrating the shift.

Quality & Reliability

5/10

The video is a personal testimony and advice from a developer with 5-6 years of experience. It provides real anecdotal examples but lacks external references or scientific backing. The information is practical and plausible, but reliability is limited by the absence of verifiable sources.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

Contribution & Novelties

This video contributes a personal, candid account of how AI-related questions have entered developer interviews in 2025. It offers a list of five specific questions and strategic advice on how to answer them, such as self-rating at 6/10 and avoiding pretension. The originality lies in the concrete experience shared, which is more actionable than generic interview guides. It also highlights a common pitfall: AI tools can overreach, leading to code duplication, which is valuable for practitioners. The video encourages honest self-assessment and sets boundaries with AI tools.

Pour aller plus loin :

155 words

Radar Profile

The radar profile shows a balanced moderate performance across dimensions, with slightly higher scores in information quantity (6) and lower in reliability (4). This reflects a video that provides practical, experience-based advice but lacks rigorous sources or technical depth.

Reliability 4/10