Decompose Responsibilities into Agents
Each agent should have:
- A narrow role
- Clear decision authority
- Defined inputs and outputs
- Explicit constraints
Examples:
- Classification agent
- Risk assessment agent
- Approval agent
- Execution agent
- Monitoring agent
Agents should not overlap responsibilities.
Introduce Central Orchestration
Orchestration becomes critical at scale.
The orchestrator:
- Activates agents
- Controls execution order
- Manages dependencies
- Prevents conflicts
- Halts workflows when risk increases
Agents decide locally.
Orchestration governs globally.
Design Shared and Isolated Memory
Agentic systems require careful memory design.
Memory strategies include:
- Shared memory for common context
- Isolated memory for agent-specific reasoning
- Episodic memory for outcomes
- Operational memory for system state
Poor memory design causes:
- Context leakage
- Conflicting decisions
- Untraceable behavior
Shared memory without rules is gossip.
Isolated memory without context is ignorance.
Coordinate Decisions, Not Just Actions
In agentic systems:
- Decisions influence other decisions
- Timing matters
- Conflicts must be resolved
Coordination mechanisms include:
- Decision hierarchies
- Confidence arbitration
- Priority rules
- Human escalation triggers
This is where most systems fail.
Embed Governance Across Agents
Governance must be:
- Centralized
- Consistent
- Enforced uniformly
This includes:
- Role-based permissions
- Action limits
- Approval thresholds
- Audit logging across agents
Without governance, agentic systems amplify risk faster than intelligence.
Design Human Oversight at System Level
Humans should oversee:
- System-level outcomes
- Cross-agent conflicts
- Policy exceptions
- Escalated decisions
Human oversight shifts from task-level to system-level governance.
At scale, humans do not manage agents.
They manage the system agents live within.
