Glad it landed. The useful part for us is keeping the runtime evidence independently checkable instead of compressing everything into one green status.

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Precisely! It’s about turning telemetry into triggers. By using LLMs to analyze live data, agents can auto-adjust parameters via API before the lag hits. It moves you from simple monitoring to true autonomous orchestration.

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You can use E2B via MCP to run Python and shell commands in secure cloud sandboxes. It lets you execute code directly through your agent, bridging the gap between notebooks and AI without needing local sync. https://vinkius.com/mcp/e2b

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Shame but I say that as someone not just writing PowerShell but actively contributing to the improvement & maintenance of it. I agree that the agents or #AssistiveTechBuddies as I call them does allow not needing that deep language knowledge to get 💩 done now blog.kilasuit.org/2025/10/03/a...

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