… AI-Assisted Migration Workflow To accelerate the transition, the Alibaba engineer utilized an AI agent equipped with specialized “Skills.” This approach shifted the “grunt work” of analysis and validation to the AI, while keeping human engineers in control of the final production execution. …
… It’s about placing them where they are most likely to be acted on—and where the cost of action is lowest. The road ahead: AI agents as policy reasoning partners Review-time enforcement is a meaningful step forward—but it is still fundamentally a rule-matching exercise. …
… To use a real LLM: Get an API key from OpenAI, Anthropic, or Gemini Create a Kubernetes secret with your key Update the AgentgatewayBackend to use the real host and authentication yaml apiVersion: agentgateway.dev/v1alpha1 kind: AgentgatewayBackend metadata: name: openai namespace: agentgateway-sys… …
… Across all runs, call count was the biggest driver of both cost and latency. What I actually learned Agents fix locally, not systemically Agents are good at fixing the problem directly in front of them, but struggle to reason about the broader system. …
… Key benefits: AI-native control loop: HolmesGPT uses an agentic task list approach Open architecture: Every integration and toolset is open and extensible, works with existing runbooks and MCP servers Data privacy: Models can run locally or inside your cluster or on the cloud Community-driven: Desi… …
… In practice, this is not only a cost problem. …
… Version-controlled. …
… You feel in control. …
… Have your agents write and test full PoCs. …