Closing panel: The future of platform engineering and what to build next
summary
Platform engineering is now treated as standard practice and teams are building AI-ready platforms by adding a knowledge graph and explicit ontology so agents can reason deterministically, not guess; keeping a hardened IDP as the foundation before wiring agents; continuously measuring real running state and applying policy to reduce time to know (detect drift or CVE impact immediately); tracking risk/profit/revenue impact rather than just DORA; and deploying a small MVP harness, prove value in stage, then scale to the rest of the org.
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chapters (12)
- 0:00Closing panel intro
- 0:51Platform engineering maturity
- 2:58AI's future impact
- 6:12Innovation vs technical debt
- 7:35AI governance role
- 12:30AI-powered platform blocks
- 16:05Measuring platform ROI
- 19:38AI governance trends
- 24:51AI and developer experience
- 28:25AI readiness steps
- 30:07Scaling AI adoption
- 31:00Closing remarks
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