PANEL: Unleashing the Future: The Impact of Gen AI on Development Productivity
summary
Panel reports developers using co-pilot and ChatGPT daily but finding concrete limits: generated code sometimes introduces SQL injection and XSS because models echo project code, junior devs learn slower when relying on AI, and copyright provenance remains unclear. Teams build a prompt microservice and fine-tune private models trained on internal docs that actually speed onboarding. Experiments include image generation for marketing, using models to craft harmful-demo exploits, and tuning JVMs with 500 JVM flags guided by AI — useful but requiring expert review.
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chapters (10)
- 0:00Gen AI productivity panel intro
- 4:57Early AI tool adoption
- 10:56AI impact on learning and productivity
- 16:17AI beyond coding in orgs
- 21:34Legal and security with public AI
- 25:30Avoiding AI burnout
- 30:10Copyright of AI code
- 37:34Future of AI hype
- 42:04Developer skills and cognitive load
- 49:24Closing thoughts on AI
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