“Agent As Code” is a development paradigm that applies the principles of Infrastructure as Code (IaC) to AI agent management. Just as Infrastructure as Code “uses DevOps methodology and versioning with a descriptive model to define and deploy infrastructure,” What is BMAD-METHOD™? A Simple Guide to the Future of AI-Driven Development. Agent As Code treats AI agents as declarative, version-controlled code artifacts.
The BMAD-METHOD™ revolutionizes how organizations manage and share AI agents by treating them as first-class code artifacts. Instead of fragmented configurations scattered across platforms, agents become self-contained markdown files with embedded YAML configurations — making specialized AI expertise as portable and manageable as any other piece of software.
Core Concept
Agent As Code means defining AI agents through structured configuration files that contain:
Agent behavior and personality (declaratively defined)
Capabilities and skills (as code dependencies)
Deployment instructions (platform-agnostic specifications)
Version control metadata (for tracking changes over time)
Instead of manually configuring AI assistants in each platform or maintaining separate agent setups, you write code that describes what the agent should be and how it should behave.
Each BMAD agent is a single .md file containing everything needed to recreate that agent's behavior anywhere. This isn't just about convenience; it's about fundamentally changing how organizations capture, version, and distribute AI expertise.
The Infrastructure as Code Parallel
Infrastructure as Code “refers to the practice of managing and provisioning computing infrastructure through machine-readable configuration files, rather than physical hardware configuration or interactive configuration tools.”
BMAD-METHOD™ implements agents as self-contained markdown files with embedded YAML configurations, making them truly shareable as code. Each agent file contains everything needed to define the agent’s persona, capabilities, and dependencies in a single, version-controllable file.
Similarly, Agent As Code manages AI agents through machine-readable configuration files rather than manual platform-specific setups or interactive configuration tools.
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