April 21st, 2026
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Getting Started with Agentic DevOps – Part 1: Foundations

This post is the first in a 3-part series:

  1. Foundations (this post)
  2. Start shipping (context engineering, MCP servers, orchestration)
  3. App modernization (Java, .NET, PHP, microservices)

Bookmark this post for quick reference as you start exploring Agentic DevOps. It will be updated as the 3 parts become available.

Getting started with Agentic DevOps

Agentic DevOps is a new approach to software development where AI-powered agents work alongside your team across the entire software development lifecycle.

Unlike traditional AI assistance, these agents go beyond suggestions—they can take on tasks end-to-end, collaborate across tools, and operate across the lifecycle with your guidance and approval.

This series is designed as a practical entry point, using short videos to walk through the key concepts and patterns—from foundational ideas to real-world implementation.

In this first post, we focus on the fundamentals across four short videos.

Video 1: Agentic DevOps and AI-native Development

In this video, you’ll learn:

  • How DevOps is evolving into Agentic DevOps
  • What it means to have AI agents working alongside your development team
  • Why this shift is happening now

Agentic DevOps builds on DevOps and DevSecOps by introducing agents that actively collaborate in development workflows—moving from automation to true team augmentation.

Additional links:

Video 2: AI across the SDLC

In this video, you’ll learn:

  • How AI is applied across the full software development lifecycle
  • Where tools like GitHub Copilot fit beyond just coding
  • How teams can extend AI into planning, testing, deployment, and operations

AI is no longer limited to code generation. It is becoming a foundational layer across planning, coding, verification, deployment, and operations.

Additional links:

Video 3: Chat, Cloud Agent and Custom Agents

In this video, you’ll learn:

  • The difference between chat‑based assistance and agent‑driven execution
  • How cloud agents handle tasks asynchronously
  • How custom agents enable reusable, team-specific workflows

The shift from asking AI for help to delegating work to agents is a key step in adopting Agentic DevOps.

Additional links:

Video 4: Agent Types and Subagents

In this video, you’ll learn:

  • The differences between local, CLI, and cloud-based agents
  • When to use synchronous vs asynchronous execution models
  • How subagents enable specialized, scalable task execution

Not all agents behave the same way. Choosing the right type and execution model is critical to scaling agent-driven workflows effectively.

Additional links:

What’s next

In Part 2, we move from concepts to execution:

  • Context Engineering fundamentals
  • MCP servers as tool interfaces
  • Multi-agent orchestration

Stay tuned.

Reviewed by Simona Toader, Senior Global Black Belt at Microsoft.

Author

Senior Solution Engineer - AI and Developer Tools

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