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  1. DZone
  2. Data Engineering
  3. AI/ML
  4. PlatformCon 2024 Session Recap: Platform Engineering and AI

PlatformCon 2024 Session Recap: Platform Engineering and AI

Watch this DZone moderated PlatformCon 2024 panel where you can learn more about modern AI, platform engineering, and what to expect in the future.

By 
Caitlin Candelmo
·
Kellyn Gorman
DZone Core CORE ·
Jul. 10, 24 · Presentation
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Are you curious what experienced practitioners are saying about AI and platform engineering — and its growing impact on development workflows? Look no further than DZone’s latest event with PlatformCon 2024 where our global software community answers these vital questions in an expert panel on all things platform engineering, AI, and beyond.

What Developers Must Know About AI and Platform Engineering

Moderated by DZone Core member and Director of Data and AI at Silk, Kellyn Pot’Vin-Gorman, panelists Ryan Murray, Sandra Borda, and Chiradeep Vittal discussed the most probing questions and deliberations facing AI and platform engineering today. 

Check out the panel discussion in its entirety here:



Important questions and talking points discussed include:

  • How has AI transformed the platform engineering landscape? 
  • Examples of how AI has improved developer productivity within organizations.
  • What are some of the challenges you’ve faced when integrating AI into your development workflow, and how have those been addressed?
  • What are some anti-patterns or caveats when integrating GenAI into engineering platforms and the SDLC more broadly?
  • What are some practical steps or strategies for organizations looking to start incorporating AI into their platform engineering efforts?
  • ….and more!
AI Panel discussion platform engineering

Opinions expressed by DZone contributors are their own.

Related

  • Platform Engineering 2.0: Evolve the Substrate for AI and Agents
  • A Developer-Centric Cloud Architecture Framework (DCAF) for Enterprise Platforms
  • Golden Paths for AI Workloads - Standardizing Deployment, Observability, and Trust
  • The Shift of DevOps From Automation to Intelligence

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