Agentic AI in DevOps Explained: Tools, Context, and What Changes Next

Описание: In this first episode, Fernando and Andrey set the foundation for a new series on agentic AI in DevOps.

Drawing from years of AWS consulting experience and hands-on work building an AI solution used in real production environments, they explore how AI is changing infrastructure, cloud operations, and engineering workflows.

In this conversation, they cover:

what agentic AI actually means

the difference between chatbots and agents

why the ability to take action changes everything

how AI tooling evolved from text generation to real execution

why context is critical for troubleshooting infrastructure

the rise of tools like GitHub Copilot, Cursor, Windsurf, MCP, Amazon Q CLI, Claude Code, and Kiro

what these changes mean for DevOps engineers, consultants, and technical teams

This episode is for anyone trying to understand where AI fits into DevOps today, beyond hype and beyond simple chat interfaces.

While the discussion often uses AWS examples, the ideas are broader and apply across cloud environments and modern engineering teams in general.

In upcoming episodes, Fernando and Andrey will go deeper into tools, context, workflows, RAG, and the practical lessons they are learning while building an AI DevOps teammate connected to real environments.
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Explore B.O.R.I.S, our AI DevOps teammate: https://getboris.ai
Follow Andrey Devyatkin on LinkedIn: https://www.linkedin.com/in/andreydevyatkin/
Follow Fernando Goncalves on LinkedIn: https://www.linkedin.com/in/aicloudengineer/
Follow B.O.R.I.S on LinkedIn: https://www.linkedin.com/company/sirob-tec...

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