Agentic AI for Autonomous Micro-Frontend User Interfaces
summary
An Agentic Control Plane is built that runs RL agents and LLM agents over OpenTelemetry inputs and applies fixes via GitHub pipelines and service mesh controllers with canary and blue‑green deploys and auto rollback. A global ecommerce case shows adaptation latency improves 35% front‑end errors drop 40% and manual coordination halves. The system uses four planes observation cognition execution policy and faces RL training overhead and trust and sandboxing challenges for generated code.
AI-written summary · about
chapters (8)
- 0:00Introduction to the Conative Conference
- 1:12Understanding Microservices and Micro Frontends
- 2:24The Coordination Crisis in Modern Architectures
- 5:05Introducing Agent AI for Autonomous Coordination
- 6:12The Agentic Control Plane Framework
- 9:05Real-World Application and Benefits
- 10:07Challenges and Future Directions
- 12:11Conclusion and Future of Cloud Native Engineering
related talks
30mFuture of AgenticAI: Architecting the Global Control Plane (Keynote)
34mAI Agents: Transforming Autonomous Decision-Making
26mAI-first frontend architecture
18mFrom Reactive to Resilient: Agentic AI
27mAgentic Engineering: Working With AI, Not Just Using It
33mAsk Me Anything: AI Agents, Skills, Career & Growth
40mAgentic AI: The Next Evolution of Automation
33mUnlocking Agentic AI: [...]