JITA Learning · Microsoft · Field Guide
AB-100 · Agentic AI Business Solutions Architect
Build working judgment for agentic AI business solution architecture.
What you should expect
Build working judgment for agentic AI business solution architecture.
This Field Guide develops a working mental model of agentic AI business solution architecture. You will connect decompose business goals into agent workflows, tools, data, and human handoffs, choose where agents, automation, applications, and people should own the work, reason about model, grounding, memory, tool, and integration boundaries, and design governance, security, accountability, and lifecycle controls for agentic solutions. You are not just memorizing feature names; you are learning what owns the requirement, what can fail, and how to verify the outcome.
What you will learn
- decompose business goals into agent workflows, tools, data, and human handoffs
- choose where agents, automation, applications, and people should own the work
- reason about model, grounding, memory, tool, and integration boundaries
- design governance, security, accountability, and lifecycle controls for agentic solutions
- recognize why one technically plausible alternative loses under the stated requirement
- apply Changed Fact reasoning and verify the design or implementation through operational evidence
Decision skills you will practice
- identify the governing requirement
- compare the nearest plausible alternative
- apply Changed Fact reasoning
- trace prerequisites, dependencies, and failure paths
- verify configured state, effective state, runtime outcome, and negative-path evidence
Who this is for
solution architects, consultants, and transformation leaders who need to turn business processes into governed agentic solutions
Use this when you need to learn the architecture, mechanics, dependencies, tradeoffs, failure paths, and verification logic behind the certification.
Decisions you will learn to distinguish
- agent automation vs conventional workflow automation
- single-agent vs coordinated multi-agent ownership
- technical feasibility vs business-value and governance readiness
Why JITA is different
Microsoft explains the platform. JITA teaches the decision.
Microsoft Learn explains the services, features, and documented behavior that support agentic AI business solution architecture. JITA connects those capabilities into decisions: what owns the requirement, what the nearest alternative is, what changes when one fact changes, and what evidence proves the implementation worked.
How to choose:
Use the Field Guide to build understanding. Use the Exam Preparation Guide to test whether that understanding survives exam-style decisions.