One silver bullet: Adaptability
summary
Claim: AI shifts workflows but not fundamentals; hiring for learning to learn matters more than pedigree. Gives concrete evidence: a grad builds an LM code reviewer that actually saves reviewers' time, organizations adapt existing ops to LM APIs and agents, Capgemini hires more than a hundred grads, one VP hires a junior who quickly ships unfamiliar tech. Covers prompt/context/token limits, what was built, and which numbers and hires succeeded.
AI-written summary · about
chapters (9)
- 0:00Introduction
- 1:16AI impact on software dev
- 2:40Teaching adaptability at Code Your Future
- 4:48Andre’s AI tool success
- 5:29Ley’s transition to business analysis
- 7:36AA’s adaptability overcoming education gaps
- 8:40Hiring adaptable engineers
- 10:02From pedigree to potential
- 10:43Q&A
related talks
41mThe Changing Face of Engineering What Teams Need Now 002
48mBeyond the Hammer: Diversifying Your Software Development Toolkit
53mThe Human Side of AI: Unlocking Opportunity in the New Bottlenecks of Software Development
43mAI & HR
46mMoving From Best Intentions to AI & Human Intelligence
22mAdapting to the Future of Work in Tech
30mWill AI Steal Your IT Job? Find Out How to Stay Ahead!
45mWill Skynet sort you out? An outsider's view on how to stay relevant in the era of GenAI
