Exam Prep: Diagnostic Review
Domain-by-domain diagnostic to identify weak spots, with exam-day strategy, trap patterns, and a final readiness checklist.
Exam Day Mindset
This module is different. There are no new concepts — only synthesis, pattern recognition, and trap awareness. The AB-620 exam tests whether you can apply what you’ve learned under pressure, distinguishing between options that look similar but have critically different implications.
Read each section carefully. If anything feels unfamiliar, go back and review the relevant module before continuing.
Domain 1: Design and Configure Agents — Key Concepts
Agent types and when to use them: Copilot Studio agents (declarative, custom, with Copilot connector knowledge), Microsoft 365 Copilot agents (declarative agents that extend M365 Copilot). Know which scenario calls for which type.
Knowledge sources: Understand the differences between Copilot connectors (search-based, read-only, for grounding) and Power Platform connectors (action-based, can write data, for automation). This distinction is the single most tested concept in Domain 1.
Topics and triggers: How topics are triggered (by phrases, by other topics, by events). The difference between system topics and custom topics. Fallback behavior.
Generative orchestration: How the AI layer routes user messages to the right topic or knowledge source. When orchestration helps and when explicit topic routing is better.
Instructions: System-level instructions that shape agent behavior globally vs. topic-level instructions that apply within a specific topic.
| Concept | Key Distinction | Exam Trap to Watch |
|---|---|---|
| Copilot connector vs Power Platform connector | Copilot connectors are for search/knowledge grounding (read-only). PP connectors are for actions (can write data). | Questions that describe 'looking up information' — this is a Copilot connector scenario, not a PP connector, even if a PP connector could technically do it |
| System topic vs custom topic | System topics handle built-in events (greeting, fallback, escalation). Custom topics handle business logic. | Questions asking 'where should this logic go?' — if it's a standard event, use system topics; if it's business-specific, create a custom topic |
| Instructions vs topics | Instructions shape behavior globally. Topics define specific conversation flows. | Questions where the answer seems like it could be either — instructions for tone/style/rules, topics for multi-step workflows |
Domain 2: Build and Enhance Agents — Key Concepts
Actions and connectors: How agents call external systems. The difference between topic-level HTTP requests (inline, one-off) and tool-type REST API actions (reusable, configured once).
Generative AI features: AI-generated responses from knowledge, generative answers, generative actions. When to let the AI generate vs. when to author explicit responses.
Authentication: Delegated (user’s identity, user’s permissions) vs. application (app’s identity, app’s permissions). Critical for questions about “who sees what data.”
Channels and deployment: Where agents are published — Teams, web, custom canvas. Channel-specific capabilities and limitations.
Security and DLP: Data Loss Prevention policies, environment security, connector permissions. How to restrict what agents can access.
Autonomous triggers: Agents that act without user initiation — triggered by events, schedules, or conditions. The difference between reactive (user asks) and proactive (agent initiates) patterns.
MCP and A2A protocols: Model Context Protocol (tools for agents — agent calls an MCP server to use a tool) vs. Agent-to-Agent (agent delegates to another agent as a peer). MCP is about tools. A2A is about agent collaboration.
| Concept | Key Distinction | Exam Trap to Watch |
|---|---|---|
| Topic HTTP request vs tool REST API action | Topic HTTP is inline within a topic (one-off use). Tool REST API is configured once and reusable across topics. | Questions describing 'reusable' or 'multiple topics need this' — that's a tool-type action, not an inline HTTP request |
| Delegated vs app-only authentication | Delegated: user's identity, user's permissions, user must be signed in. App-only: app's identity, app's permissions, no user sign-in needed. | Questions about 'background processing' or 'autonomous agents' — these typically need app-only since no user is present to authenticate |
| MCP vs A2A | MCP: agent uses tools via an MCP server (tool access). A2A: agent delegates tasks to another agent (peer collaboration). | Questions describing 'agent needs to use a calculator tool' (MCP) vs 'agent needs help from a specialist agent' (A2A) |
| API connector vs Computer Use connector | API connector calls structured APIs (reliable, fast, scoped). Computer Use connector automates UI interactions in a browser (last resort for systems without APIs). | The exam answer is almost ALWAYS API connector. Computer Use is only correct when the question explicitly states 'no API available' |
Domain 3: Test and Manage Agents — Key Concepts
Test sets and evaluation: Creating test sets (manual, auto-generate, import from logs). Evaluation methods (accuracy, grounding quality, topic matching, response quality). Snapshot comparison.
Solutions and environment variables: Packaging agents in Dataverse solutions. Managed vs. unmanaged. Environment variable types (text, number, boolean, data source, secret). Definition vs. current value.
Power Platform Pipelines: Host environment architecture. Stages and approval gates. Extensibility with Power Automate flows. Pre-deployment and post-deployment automation.
Agent lifecycle: Plan → build → test → package → deploy → monitor → iterate. The lifecycle is a loop, not a line.
| Concept | Key Distinction | Exam Trap to Watch |
|---|---|---|
| Accuracy vs grounding quality | Accuracy: is the answer correct? Grounding: is the answer from your data? | An agent can have high grounding but low accuracy (correctly using outdated data). Don't conflate 'grounded' with 'accurate'. |
| Managed vs unmanaged solution | Managed: locked, for UAT/prod. Unmanaged: editable, for dev. | Questions about 'letting stakeholders adjust' in UAT — the answer is still managed. Feedback goes back to dev as requirements, not direct edits in UAT. |
| Environment variable definition vs current value | Definition travels with the solution. Current value is set per environment. | Questions about 'why does production show dev values?' — current values weren't set after import, not a solution bug. |
| Pipeline host vs target environment | Host: control plane for pipeline config. Target: where solutions are deployed. | The host is NOT the dev environment — it's a separate dedicated environment. |
Top 5 Trap Patterns
These are the patterns that catch the most people. Study each one until the distinction is automatic.
Trap 1: API Connector vs Computer Use Connector
The exam will describe a scenario where an agent needs to interact with an external system. If the system has an API (which it almost always does), the answer is API connector. Computer Use connector (browser automation) is only correct when the question explicitly states the system has no API.
Default to API connector unless the question forces you toward Computer Use.
Trap 2: Copilot Connector vs Power Platform Connector
When the scenario describes an agent “looking up” or “searching for” information, the answer is Copilot connector (search/grounding). When the scenario describes “creating,” “updating,” “sending,” or “performing an action,” the answer is Power Platform connector (action).
The trap: some questions describe “retrieving data” that could technically use a PP connector’s GET action. But if the purpose is knowledge grounding, Copilot connector is the right answer.
Trap 3: Topic HTTP Request vs Tool REST API Action
Both call external APIs. The difference is scope and reusability. If the question mentions “multiple topics need this” or “reusable across the agent,” the answer is tool-type REST API action. If it’s a one-off call within a single topic, it’s a topic HTTP request.
Trap 4: Delegated vs App-Only Permissions
If a user is present and signed in, and the agent should access data on behalf of that user, the answer is delegated. If the agent runs autonomously (scheduled, event-triggered, no user present), the answer is app-only.
The trap: questions about agents in Teams where a user is chatting. Even though it feels like automation, the user IS present — so delegated permissions apply.
Trap 5: MCP vs A2A Protocol
MCP (Model Context Protocol) gives an agent access to tools — the agent calls an MCP server to use capabilities like a calculator, database query, or file system access. A2A (Agent-to-Agent) enables agent collaboration — one agent delegates a task to another agent that has specialized knowledge.
Think: MCP = tool belt. A2A = team of specialists.
An agent needs to search a SharePoint site for policy documents to answer employee questions about company benefits. Which connector type is correct?
A claims processing agent runs on a schedule every night to review new claims and route them to adjusters. No user is signed in during processing. What authentication model should be used?
After importing a managed solution to production, the agent's welcome message still says 'Welcome to Test Corp!' instead of the client's name. What is the MOST likely cause?
An agent scores 90% on grounding quality but only 60% on accuracy for product pricing queries. The product catalog was last updated three months ago. What is the failure pattern?
Final Readiness Checklist
Use this checklist to self-assess before exam day. If you can confidently explain each item, you’re ready.
Domain 1 — Design and Configure Agents:
- I can distinguish Copilot connectors (search/grounding) from PP connectors (actions)
- I know when to use system topics vs custom topics
- I understand generative orchestration and when to override it with explicit routing
- I can explain agent types and match them to scenarios
- I know how knowledge sources are configured and prioritized
Domain 2 — Build and Enhance Agents:
- I can differentiate topic HTTP requests from tool REST API actions
- I understand delegated vs app-only authentication and when each applies
- I know MCP (tools) vs A2A (agent collaboration) protocols
- I can explain API connector vs Computer Use connector trade-offs
- I understand autonomous triggers and proactive agent patterns
- I know DLP policies and security boundaries for agent data access
Domain 3 — Test and Manage Agents:
- I can create test sets using all three methods (manual, auto-generate, import)
- I understand evaluation methods and can interpret score combinations
- I can explain Dataverse solutions, managed vs unmanaged, and the ALM pattern
- I know environment variable types and the definition vs current value distinction
- I can describe Power Platform Pipelines architecture (host + targets)
- I understand the full agent lifecycle and why it’s a loop, not a line
Exam Strategy:
- Read every option completely before selecting — the first plausible answer is often the trap
- Look for qualifier words: “MOST likely,” “BEST approach,” “FIRST step” — these narrow the correct answer
- When two options seem correct, ask yourself which one the platform was designed for
- Time management: flag difficult questions and come back — don’t spend five minutes on one question
- Trust your preparation. If you’ve completed every module, you have the knowledge to pass.
🎬 Video coming soon
Exam Prep: Final Review Session