The Changing Face of Engineering What Teams Need Now 002
summary
Hiring becomes harder because AI-generated CVs and candidates using ChatGPT appear in screening; teams add math tests, design tasks and a “McDougall method” interview structure to filter for critical thinking. Organizations adopt LLMs (OpenAI), Cursor and Perplexity for dev support while enforcing strict AI code review and licensing checks. Companies form an AI development chapter, publish guardrails, run KPI experiments (gamified retention metrics) and build central platforms to reduce toil — these measures speed delivery but require deliberate rewiring of hiring, reviews and team structure.
AI-written summary · about
chapters (10)
- 0:00Introduction and panelists
- 1:51LLMs impact on hiring and engineering
- 7:52AI’s role in team productivity
- 17:04Engineering skills becoming obsolete
- 21:43Balancing technical and business skills
- 26:23Hiring challenges and culture fit
- 30:00What motivates engineers now
- 34:21Bringing juniors up with AI
- 38:38Screening for critical thinking
- 40:01Closing remarks and Q&A
related talks
20mHow to Strategize Talent Hiring and Upskilling in the Age of AI
23mRethinking growing engineers in the age of AI
37mHow AI & automation are changing software engineering
09mLessons Learned in AI Engineering
07mHow to Hire AI Engineers when EVERYONE is cheating with AI
46mHow AI Is Transforming Data Careers
27mEngineering in the Age of AI: Making AI Work for Us, Not Replace Us
15mThe Future of Skills: Qualifications in the Age of AI