What Are BMad Agents?

BMad Agents are self-contained AI skills that combine a persona, capabilities, and persistent memory into a conversational partner you can return to across sessions.

What Makes an Agent an Agent

Every skill in the BMad ecosystem is ultimately a skill file, but agents carry three traits that set them apart.

Trait	What It Means
Persona	A defined role and voice — architect, therapist, game master, finance advisor — that shapes how the agent communicates
Capabilities	Actions the agent can perform, either as internal prompt commands or by calling external skills
Memory	A sidecar directory where the agent stores what it learns about you, your preferences, and past interactions

Together these create something that feels less like running a command and more like talking to a specialist who already knows you.

How Memory Works

When an agent launches for the first time in a project, it can create a sidecar memory directory at _bmad/memory/<agent-name>/. On every subsequent launch the agent loads this memory, which is how it remembers your preferences, prior decisions, and anything you told it to retain.

Agents can also include a first-run onboarding step — a set of questions the agent asks on initial launch so it can configure itself for your needs before you start working together.

Memory Lives Outside the Skill

Agent memory is stored in your project, not inside the skill folder. This prevents agents from accidentally modifying their own instructions and keeps your data portable. Also the same agent can be used with different projects or shared with others and generate their own memory space!

Capabilities: Internal and External

Agent capabilities come in two flavors.

Type	Description	Example
Internal commands	Prompt-driven actions defined inside the agent’s skill file	A Dream Agent’s “Dream Capture” command
External skills	Standalone skills or workflows the agent can invoke	Calling the create-prd workflow via a PM agent - allowing the workflow to retain customization and memory

You choose the mix when you design the agent. Internal commands keep everything self-contained; external skills let you compose agents from reusable building blocks.

Headless Mode

Agents support a headless (autonomous) wake mode. When activated — for example through a cron job or an orchestrator like Open Claw — the agent skips waiting for user input and attempts to complete its tasks independently. This makes agents suitable for background automation while still being conversational when a human is present.

When to Build an Agent vs. a Workflow

Choose an Agent When	Choose a Workflow When
The user will return to it repeatedly	The process runs once and produces an output
Remembering context across sessions adds value	Stateless execution is fine
A strong persona improves the interaction	Personality is secondary to getting the job done
The skill spans many loosely related capabilities	All steps serve a single, focused goal

If you are unsure, start with a workflow. You can always wrap it inside an agent later.

Building Agents

The BMad Agent Builder (bmad-agent-builder) walks you through a six-phase conversational discovery process — from intent through capabilities, requirements, drafting, building, and quality optimization. It produces a ready-to-use skill folder you can drop into your tools’ skills directory.

See the Builder Commands Reference for details on the build process phases and capabilities.