Define where agents fit into the way engineering work gets done.
Once AI agents perform engineering work, they become participants in the operating model. That raises organizational questions that cannot be solved through prompts alone.
An agent doing engineering work is an organizational question, not a configuration one.
Which role does the agent perform, which human role owns its work, what may it initiate, what outputs may it modify, how does it interact with people and other agents, and who is accountable when it reaches a decision boundary?
Define the organizational and process role of AI agents so that agent execution becomes part of the governed engineering system.
What the service can define.
- Agent roles
- Responsibilities
- Process participation
- Triggers
- Inputs and outputs
- Tool access
- Human ownership
- Escalation paths
- Interaction with other agents
- Process interfaces
- Governance expectations
- Assurance relationships
Five steps from process position to governed role.
Start from the effective process
Identify where the proposed agent participates in the process.
Define the agent role
Specify the responsibilities assigned to the agent and the outcomes it is expected to produce.
Design human-agent interaction
Clarify who initiates work, when the agent acts, when it asks for input, when it stops, and who reviews, approves, and owns the result.
Define interfaces
Specify how the agent interacts with engineering tools, process artifacts, other roles, other agents, and assurance mechanisms.
Govern the role
Connect the agent role to applicable authority, controls, provenance, and improvement mechanisms.
- Who initiates work
- When the agent acts
- When it asks for input
- When it stops
- Who reviews
- Who approves
- Who owns the result
- Agent-role definitions
- Human-agent responsibility model
- Process participation model
- Interaction and escalation model
- Tool and artifact interfaces
- Governance relationships
- Target agent operating model
- Avoid introducing agents as an unmanaged side process.
- Clarify ownership and accountability.
- Reduce ambiguity between agent actions and human responsibilities.
- Make agent behavior easier to scale across workflows and teams.
- Create the foundation for skills, rules, checkpoints, and assurance.