Handling AI-Generated Code: Challenges & Best Practices • Roman Zhukov & Damian Brady

Описание: This interview was recorded for GOTO Unscripted.
https://gotopia.tech

Check out more here:
https://gotopia.tech/articles/419

Roman Zhukov - Principal Architect - Security Communities Lead at Red Hat
Damian Brady - Staff Developer Advocate at GitHub

RESOURCES
Roman
https://github.com/rozhukov
  / rozhukov  

Damian
https://bsky.app/profile/damovisa.me
https://hachyderm.io/@damovisa
https://x.com/damovisa
https://github.com/Damovisa
  / damianbrady  
https://damianbrady.com.au

Links
https://www.redhat.com/en/blog/ai-ass...

DESCRIPTION
Roman Zhukov (Red Hat) and Damian Brady (GitHub) explore the evolving landscape of AI-assisted software development. They discuss how AI tools are transforming developer workflows, making developers about 20% faster on simple tasks while being 19% slower on complex ones.

The conversation covers critical topics including code quality and trust, security concerns with AI-generated code, the importance of education and best practices, and how developer roles are shifting from syntax experts to system architects. Both experts emphasize that AI tools serve as amplifiers rather than replacements, with humans remaining essential in the loop for quality, security, and licensing compliance.

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Phil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZ
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Holden Karau, Trevor Grant, Boris Lublinsky, Richard Liu & Ilan Filonenko • Kubeflow for Machine Learning • https://amzn.to/3JVngcx
Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) • https://amzn.to/3AQmIRg
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns • https://amzn.to/2ZD7t0x
Lakshmanan, Görner & Gillard • Practical Machine Learning for Computer Vision • https://amzn.to/3m9HNjP


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