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What if your AI agents could think more like IT operations staff — and less like tools?
In this episode, we catch up with Zichuan Xiong, to explore the Model Context Protocol (MCP) — a powerful new way to give AI agents deeper awareness of the tools, information and history they need to work effectively in the operations space. Unlike traditional APIs that just trigger functions, MCP adds a semantic layer of context that helps AI understand what to do, why it matters and how to do it better.
Whether you're deep in site reliability engineering (SRE) or just curious about the next leap in AIOps, this episode unpacks how MCP could be the missing layer between today's tools and tomorrow's autonomous systems. If you want to find out more, check out this piece by Zichuan at al, https://www.thoughtworks.com/insights/blog/machine-learning-and-ai/mcp-critical-ai-driven-sre
By Thoughtworks4.4
4343 ratings
What if your AI agents could think more like IT operations staff — and less like tools?
In this episode, we catch up with Zichuan Xiong, to explore the Model Context Protocol (MCP) — a powerful new way to give AI agents deeper awareness of the tools, information and history they need to work effectively in the operations space. Unlike traditional APIs that just trigger functions, MCP adds a semantic layer of context that helps AI understand what to do, why it matters and how to do it better.
Whether you're deep in site reliability engineering (SRE) or just curious about the next leap in AIOps, this episode unpacks how MCP could be the missing layer between today's tools and tomorrow's autonomous systems. If you want to find out more, check out this piece by Zichuan at al, https://www.thoughtworks.com/insights/blog/machine-learning-and-ai/mcp-critical-ai-driven-sre

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