Best practices to Create Agents

Prior to deploying an AI agent, clearly define the intended use case and measurable objectives. Identify the specific problems the agent is expected to address, along with the desired outcomes. This upfront clarity ensures that development efforts are aligned with business requirements and helps validate the agent’s effectiveness during implementation.

The following guidelines are recommended to ensure the effective design and deployment of AI agents:

  1. Start with a Clear Goal:
    • Define the specific outcome or task the agent should accomplish.
    • Break down the problem into discrete steps that can be mapped to agent behavior.

  2. Use Modular Design

    • Structure your agent using building blocks (tools, logic, memory, prompts) to isolate responsibilities.
    • Keep each function focused and loosely coupled for easier testing, maintenance, and reuse.
    • When appropriate, use sub-agents for task decomposition within complex workflows.

  3. Leverage Prebuilt Components

    • Use prebuilt agents or tools from the catalog when possible to accelerate development.
    • Customize only where necessary to avoid duplicating common logic.

  4. Integrate Guardrails Early

    • Add validation logic or filters during prompt design to regulate LLM output.
    • Define clear boundaries for the agent’s behavior to ensure secure and compliant execution.

  5. Design for Human-in-the-Loop (HITL)

    • For critical decision points, insert checkpoints for human review or approval.
    • Use conditional branching to support fallback to manual validation when required.

  6. Utilize Memory Thoughtfully

    • Enable persistent memory only when necessary to retain useful context across sessions.
    • Use vector-based retrieval to bring in relevant past knowledge without overwhelming the agent context.

  7. Plan for Multi-Agent Collaboration

    • Design agents to operate independently when possible, and coordinate through clear input/output definitions.
    • Avoid tight coupling between agents to ensure scalability and easier debugging.

  8. Test Incrementally

    • Use the application’s testing and validation tools to check agent behavior at each stage of design.
    • Start with isolated units (e.g., tool outputs, prompt responses), then test the full control flow.

  9. Name and Document Clearly

    • Use descriptive names for agents, tools, memory blocks, and logic nodes.

  10. Secure Your Agent Configuration

    • Apply role-based access control (RBAC) as appropriate, especially for production agents.
    • Minimize access to sensitive data unless absolutely required.

    Following these practices will help you build agents that are reliable, explainable, and scalable, making full use of the capabilities provided by the UnO Agentic AI Builder.