With the advancement of AI technology, more development work can be assisted by AI. However, a single AI assistant often struggles to handle all roles in complex projects — product managers need to understand requirements, architects need to design systems, developers need to write code, and QA needs to verify quality.
Hermes’s Profile mechanism allows us to define different identities and responsibilities for AI, building a complete AI development team. This article details how to set up and use this system.
Core Concept: Profile and Role Isolation
Hermes’s Profile is an independent configuration unit, each Profile has:
- SOUL.md — Role identity definition, determines AI’s thinking style and work boundaries
- skills/ — Dedicated skills directory, containing workflow knowledge for that role
- memories/ — Independent memory, different roles don’t interfere with each other
- workspace/ — Working directory, storing output documents
This differs from regular multi-turn conversations: the PM role won’t suddenly start writing code, architects won’t overstep to modify requirements, each role strictly works within their defined responsibilities.
1 | ~/.hermes/profiles/ |
Team Configuration: team.yaml
The team’s behavior is defined by ~/.hermes/team.yaml:
1 | team: |
Role Boundary Reference Table
| Role | Responsible For | Not Responsible For |
|---|---|---|
| PM | Requirement decisions, priorities, user stories | Code, architecture, technical selection |
| UI | Design decisions, visual standards, interaction flow | Frontend code, technical implementation |
| SA | Architecture decisions, API design, data models | Specific code, requirement analysis |
| Dev | Code implementation, unit tests | Requirements, architecture decisions |
| QA | Test strategy, bug analysis | Feature code, requirement decisions |
The benefit of clear boundaries is avoiding “role crossing” — PM won’t suddenly start writing code, Dev won’t arbitrarily modify requirements. Everything has a clear responsible person.
Standard Development Workflow
1 | ┌─────────────────┐ |
Key Points:
- UI phase cannot be skipped — Even for small features, UI design needs to confirm interaction methods
- UI and SA are parallel — After requirements are confirmed, interface design and architecture design can proceed simultaneously
- Output documentation — Each phase’s output must be documented and passed to downstream
Practice: Manual Switch Mode
The simplest usage is manually switching Profiles:
1 | # Phase 1: PM analyzes requirements |
Each role only sees information within their responsibility scope, following upstream output to work.
Advanced: Kanban Auto Coordination
For complex projects, recommend using Hermes Kanban system:
1 | # Initialize Kanban |
The Kanban system automatically manages task dependencies, unlocking downstream tasks after upstream completes.
SOUL.md Example
Example of PM role’s SOUL.md:
1 | # Product Manager |
Each role’s SOUL.md clearly defines “what can be done” and “what cannot be done”, ensuring clear role boundaries.
FAQ
Q: Why not use one全能 AI to complete all work?
One role doing everything leads to:
- Writing code without clear requirements
- Architecture decisions not documented
- Incomplete test coverage
- Confused responsibilities, difficult to trace
Role separation enforces process discipline, each phase has clear output.
Q: How do roles pass information?
Through documents in workspace/ directory:
- PM output →
workspace/requirement-analysis-*.md - UI output →
workspace/ui-design-*.md - SA output →
workspace/architecture-design-*.md
Downstream roles read upstream documents to proceed.
Q: What if issues are found?
Each role discovering issues should:
- Mark the issue in their output document
- If it’s an upstream issue, feedback to upstream role
- Don’t cross boundaries to solve issues
Example: Dev finds architecture design has issues, should mark in output and notify SA to redesign, not modify architecture themselves.
Summary
Hermes’s Profile mechanism allows us to build an AI development team with clear responsibilities:
- Role isolation: Each role has independent identity and memory
- Clear boundaries: Strictly limit each role’s responsibility scope
- Standardized workflow: Standardized development process and output passing
- Extensible: Can add new roles as needed
This approach is more suitable for complex projects than a single AI assistant, each role focuses on their domain, producing more professional and standardized output.
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