Comprehensive Requirements Gathering for an Agentic AI Agent

Core Functional Requirements

• What will the agent's primary role and function be?
• On what time interval should the agent perform the desired work?
• What specific samples or examples of the desired output from the agent?

Knowledge & Information Access

• What knowledge (i.e. documents, transcripts, decks, PDFs, etc.) will the agent need to know and be trained on?
• What systems must the agent have access to? (i.e. Gdrive, Airtable, CRM, 3rd party APIs, web scraping, etc.)
• What data sources will need regular updates versus static knowledge?
• How will the agent validate the accuracy and relevance of its information?

User Interaction Model

• Who are the primary users of this agent, and what are their technical skill levels?
• What interface(s) should users employ to interact with the agent? (chat, voice, email, etc.)
• What authentication/authorization model should be implemented?
• What level of explanation should the agent provide about its decision-making?
• What feedback mechanisms should be in place for users to correct or guide the agent?

Agent Capabilities & Limitations

• What specific tasks should the agent be able to perform autonomously vs. with human oversight?
• What are the agent's decision-making boundaries and when must it escalate to humans?
• What level of creativity or novel solutions is appropriate for the agent to generate?
• How should the agent handle uncertain or ambiguous information?
• What cognitive abilities are most important for this agent? (reasoning, memory, learning, etc.)

Technical Implementation

• What monitoring and logging requirements exist for the agent's activities?
• What recovery mechanisms should be in place if the agent fails?
• What metrics should be tracked to evaluate the agent's performance?
• What is the expected load and scalability requirements?
• What latency requirements exist for the agent's responses?

Ethical & Safety Constraints

• What potential misuses of the agent need to be prevented?
• What sensitive data might the agent encounter and how should it be handled?
• What failsafes should be implemented to prevent harmful actions?
• Are there any regulatory or compliance requirements the agent must satisfy?
• What transparency requirements exist for the agent's decision-making?

Learning & Improvement

• Should the agent improve over time based on interactions?
• What feedback loops should be established for continuous improvement?
• How should conflicting user feedback be reconciled?
• What mechanisms will evaluate the quality of the agent's outputs?
• How frequently should the agent's knowledge be updated?

Essential Assets to Create

1. User Personas: Detailed profiles of different user types who will interact with the agent
2. Task Flow Diagrams: Visual representations of the agent's decision-making processes
3. System Architecture Diagram: Technical blueprint showing how the agent integrates with other systems
4. Knowledge Base Structure: Organization of the information the agent will access
5. Authorization Matrix: Who can ask the agent to do what
6. Output Templates: Example formats for the agent's responses or deliverables
7. Error Handling Protocols: Defined responses to various failure scenarios
8. Performance Benchmarks: Specific metrics to evaluate agent effectiveness
9. Data Flow Diagrams: How information moves between the agent and other systems
10. Test Cases: Scenarios to validate the agent's capabilities match requirements