Agentforce Testing: A Practical QA Checklist Before Launch

Agentforce 360 marked a turning point at Dreamforce. Salesforce moved beyond the concept of a conversational assistant and presented agents that can reason, act, and orchestrate across the entire platform.
For delivery and QA teams, that shift introduces new responsibilities. An autonomous agent that can update records, compose content, or call APIs needs a structured testing approach before it touches production data.
We already discussed the broader direction in our earlier post on Agentforce 360. This article focuses on what comes next: how to test these systems safely and systematically.

Hidden complexity

The hidden challenges of Agentforce testing start where traditional QA ends.
Context is no longer static. Each agent’s reasoning depends on real-time data pulled from Data 360. A change in schema or permission set can alter what the agent perceives as truth.
Autonomy multiplies risk. When an agent can perform an action, the impact is not limited to text accuracy but extends to system state and compliance.
Distribution adds uncertainty. Agents now appear in Slack, Service, and Sales applications. Each surface introduces its own triggers and data flows that must be validated.
An Agentforce testing approach that only checks output text will miss these deeper variables.
External reference: Reuters coverage of Salesforce’s model partnerships highlights how far the agentic enterprise concept now extends.

Common mistakes

Many teams start with enthusiasm and fall into predictable traps.
They test outputs but not actions or side effects.
They skip permission testing, assuming sandboxes are automatically safe.
They forget to define autonomy thresholds, leaving agents free to execute sensitive updates.
And they ignore automated regression testing when new Salesforce releases change flows, components, or APIs that agents rely on.
Each of these oversights leads to brittle systems and avoidable incidents.
For more on how release cadence affects QA, see Salesforce Release Testing: Why 3 Annual Releases Matter.

What works in practice

Salesforce has quietly introduced several building blocks that make systematic testing possible.
The Agentforce Testing Center provides a way to create Q&A-style test cases, track coverage, and run evaluations in a managed sandbox.
The Well-Architected framework now includes guidance for trusted AI, linking data governance, security, and operational excellence.
And Data 360 improvements allow teams to verify schema and permission consistency through automated checks.
Together they form a practical base for a repeatable QA process.
For official context, see Salesforce’s trusted AI foundation announcement.

The Springburst checklist

When we prepare an Agentforce rollout, we follow a consistent structure. You can adapt it for your own teams.

1. Scope and autonomy
List the top agent scenarios and define what actions each is allowed to perform. Read, draft, update, or delete. Require human confirmation for anything beyond read and draft.

2. Context and data fitness
Validate identity resolution and schema stability in Data 360. Confirm that permissions reflect least privilege and that masked fields stay masked in agent context.

3. Evaluation design
Turn each scenario into an evaluation with clear pass and fail rules. Add edge-case variants that test confidence boundaries and red-team behaviour. Capture side effects as part of the result set.

4. Safety and governance controls
Log every agent action with a readable audit trail. Enforce approval gates for risky steps. Apply the trusted AI guidelines from Salesforce for accuracy and explainability.

5. Surfaces and integration
Test across CRM and Slack. Verify that agent handoffs, message summaries, and search results respect user permissions and do not leak data between channels.
For integration work and structured validation, see our Salesforce QA Services.

6. Release and regression
Before every major Salesforce release, rerun your agent evaluations. Include LWC, Apex, Flow, and API checks so dependencies stay aligned.
For more on release testing see our related Salesforce Release Testing article.

7. Metrics and feedback
Track grounding accuracy, escalation rates, and cost per resolved task. Use weekly review cycles to refine prompts, guardrails, and autonomy levels.

Why this matters

Agentforce 360 brings scale and speed but only when quality keeps pace. The platform’s direction makes testing an operational pillar, not a compliance chore.
Teams that embed agentforce testing through evaluation, governance, and regression into their normal rhythm will ship agents that earn trust. Those that treat it as a one-off activity will spend their time fixing silent errors.
Good QA is what turns an experimental agent into a reliable teammate.

Mindset shift

Think of agents as living systems that make decisions. They deserve the same discipline you already apply to code and configuration.
Design tests before release, verify grounding and permissions, and review behaviour continuously.
When you approach Agentforce with that mindset, testing becomes not just a safeguard but the engine of sustainable innovation and Agentforce testing will be a continuous practice rather than a project milestone.