Who Should Attend &
Course FAQs

Inteq's Discovering Agentic AI Opportunities course is the recommended preparation because this course begins with a validated AI agent opportunity and moves into detailed requirements specification.

Participants with equivalent experience identifying and evaluating viable AI agent opportunities can also benefit from the course.

Programming, AI development, data science, or prompt engineering experience is not required. The emphasis is on the business analysis disciplines needed to define what an AI agent should do, how it should decide, what information and tools it requires, how it interacts with people, and where its authority begins and ends.

The Agent Requirements Package is the integrated set of business analysis artifacts that defines an AI agent with sufficient precision for engineering teams to design and build the solution without making unresolved business decisions.

Depending on the agent, the package can include:

• Agent persona, role, objectives, and responsibilities
• Decision authority and business rules
• Prompt specification and communication requirements
• Human-agent interaction and handoff requirements
• Exception, escalation, and memory requirements
• Data and tool capability requirements
• Integration specifications
• Knowledge grounding and source authority requirements

The package becomes the authoritative business specification supporting technical design, implementation, governance, validation, and audit.

Participants learn to decompose business processes into discrete, well-bounded work units at the appropriate level of granularity for agent assignment.

The analysis considers:

• Decision boundary alignment
• Atomic decision units
• Data dependencies
• Exception boundaries
• Parallelization potential

This prevents an agent from being defined too broadly or too narrowly and creates a clear business foundation for role, authority, interaction, and technical requirements.

The course treats agent identity and decision authority as explicit business requirements rather than technical implementation details.

Participants use the seven-dimension Agent Identity Model to define the agent's role and responsibilities, then establish what the agent may decide autonomously, what requires human involvement, and what remains outside its authority.

Decision logic can be documented using:

• Decision tables
• Decision trees
• Policy matrices
• Weighted scoring models
• Rule priority and conflict-resolution methods

The course also addresses deterministic rules, heuristic rules, emergent judgment, and techniques for extracting tacit knowledge from subject matter experts.

The course focuses on prompt specification from the business analysis perspective rather than teaching technical prompt-engineering implementation.

Participants learn to create the seven-component Prompt Specification Package used by engineering teams to configure agent behavior, including:

• Role definitions
• Decision rules
• Domain terminology
• Output format requirements
• Examples
• Constraints
• Acceptance criteria

Participants also specify communication and tone requirements across audiences, channels, and business situations.

Human-agent interaction is treated as a first-class design surface rather than something added after the agent has been built.

The course addresses six Human-Agent Interaction Design dimensions, including:

• Interaction initiation
• Information exchange and transparency
• Trust calibration
• Override and intervention mechanisms
• Feedback and learning integration
• Human-agent handoff design

Participants also define six exception categories, five exception-handling strategies, escalation context packages, and protocols for preserving the information humans need when intervention becomes necessary.

Memory requirements are specified across four tiers: ephemeral, session, persistent, and shared.

Reliable agent behavior depends on more than decision logic. The agent must also have appropriate data, tools, systems, integrations, and authoritative knowledge sources.

Participants evaluate data readiness across eight dimensions:

• Availability
• Quality
• Freshness
• Accessibility
• Governance
• Semantic clarity
• Security
• Agent output data

The course also covers tool and API specifications, capability gaps, error handling, fallback strategies, five integration patterns, integration touchpoints, and integration risk.

Knowledge grounding includes knowledge-base requirements, RAG architecture specifications, source authority hierarchies, knowledge-gap handling, and hallucination-prevention requirements.

You will be able to apply a disciplined, repeatable methodology for translating a validated AI agent opportunity into an integrated, engineering-ready Agent Requirements Package.

• Decompose processes into appropriate agent-assignable work units
• Define agent personas, roles, responsibilities, and boundaries
• Specify decision authority, business rules, and judgment logic
• Develop business requirements for agent prompts and communication
• Design human-agent interactions, overrides, and handoffs
• Specify exception, escalation, memory, and context requirements
• Evaluate data readiness and required tools and systems
• Define integration and knowledge-grounding requirements
• Recognize common specification anti-patterns
• Conduct an engineering handoff and identify specification gaps before implementation

The course includes professional development credentials, completion recognition, and the frameworks and resources used throughout the program.

• 2.1 CEUs
• 21 IIBA PDUs or CDUs
• Personalized Analyzing and Specifying AI Agent Business Requirements digital badge
• Certificate of completion
• Comprehensive course materials
• Agent specification frameworks, models, matrices, assessment tools, and templates used throughout the course

Inteq is an IIBA Endorsed Education Provider.

Live Team Training is available now, and the self-paced Anytime eLearning™ version is coming soon.

Team Training : Live onsite or virtual training for enterprise teams, with delivery aligned to your organization's objectives, participants, and business context. Contact Inteq for Team Training scope and pricing.

Anytime eLearning™ : The self-paced version is currently in development. Individuals can request notification when enrollment becomes available.

Government purchasing: Inteq is an approved GSA prime contractor, and Inteq training and consulting are available to U.S. Government organizations through applicable GSA Professional Services Schedule offerings.