Platform Engineering and AI - Two Buzzwords Finally Meet!
summary
Collects industry practices (not original field data) and argues the one concrete architecture choice is a gateway/broker choke point to observe, apply policy and control developer access. Recommends integrating platform-side SDKs like Spring AI so frameworks route through that broker. Identifies three customers: app integrations, developer code-assist tooling, and business users via chat (example: the open-source Goose chat app). Advises on on‑prem model hosting, a policy board of lawyers+security for fast approvals, and rapid experiment cycles.
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chapters (10)
- 0:00Introduction and Overview
- 0:21Understanding AI Workloads in Platform Engineering
- 1:23Key Practices for Supporting AI
- 3:22Roles and Responsibilities in AI Support
- 5:28Speaker's Background and Experience
- 6:18Current Trends and Tools in AI Engineering
- 8:10Platform Engineering Principles
- 17:13New Customers and Use Cases for AI
- 21:55Policy and Rapid Experimentation
- 23:43Conclusion and Resources
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