Preview before write Diffs, policy posture, and rollback readiness appear before the connector executes.
Simulation or sandbox first The product starts with a deterministic story before it asks for production trust.
Proof stays attached Approval, audit, artifacts, and recovery context stay on the same governed run.
Agentforce guide

Add human approval before Agentforce makes a live business change.

Agentforce can propose useful Salesforce actions quickly. The enterprise problem starts when those actions become production writes without a review surface. ActionPlane adds preview, policy, approvals, and audit around Agentforce-driven mutations so teams can trust the outcome, not just the prompt.

Agentforce
Human approval
Salesforce governance
AI actions
Operator review
At a glance
Agentforce Agent layer The agent can keep generating and planning actions while ActionPlane governs whether live writes proceed.
Policy-based Approval mode Human approval is reserved for risky changes rather than inserted into every low-value action.
Evidence Trust output Approvers and operators need diffs, rationale, and execution results tied to the same run.
Where ActionPlane fits

ActionPlane sits between the agent runtime and the system of record. If Agentforce or any other agent wants to write to Salesforce, ActionPlane becomes the governed layer that decides whether that write can proceed, needs approval, or should be blocked.

Intercept the proposed action before the Salesforce mutation happens.
Give the approver the exact patch, not a vague task label.
Support blocked, approved, and auto-run paths from one policy model.
Keep audit, trace, and replay connected to the same governed run.
Approval design

What a serious Agentforce approval workflow needs

A useful approval flow is not just a button. Approvers need the exact planned action, the policy reason, and enough evidence to make a fast decision.

Exact action preview

Approvers need to see object type, field-level changes, actor, confidence, and supporting context before they can sign off on a live write.

Object and record identifiers

Before-and-after field values

Run context and evidence

Connector-aware policy

Approval is not a generic checkbox. Policy should reflect whether the agent is touching an opportunity, account owner, support ticket, or another live record.

Field sensitivity

Workflow confidence thresholds

Tenant-specific controls

Human takeover and recovery

When an action is wrong or incomplete, the operator needs a path to stop it, branch it, or compensate for it without losing traceability.

Reject and route back

Branch and retry

Compensation-ready evidence

Execution path

How to keep Agentforce inside a governed execution model

The critical move is to intercept the intended action before the business system changes, then keep the final evidence attached to the same run.

01
Execution path

Agentforce proposes a business action

The agent reaches the point where it wants to mutate Salesforce or another system of record.

02
Execution path

ActionPlane builds the operator-facing plan

The planned mutation is converted into a reviewable artifact with field-level detail and policy context.

03
Execution path

Policy classifies the action

The run is evaluated against connector-aware rules so the platform can distinguish safe, risky, and disallowed changes.

04
Execution path

Approval or auto-run happens on the governed path

If approval is required, the operator sees the exact planned change. If not, the action proceeds without losing traceability.

05
Execution path

Console and audit close the loop

Execution results, artifacts, and replay data stay attached to the same run so operations and governance use one source of truth.

Why teams need this

Why custom approval code is not enough

Teams can build ad hoc approval checks inside agent logic, but that usually fragments trust, operations, and audit across too many places.

Why not put approval logic in the agent itself?

Because trust surfaces spread across prompts, tools, and handwritten workflow code quickly become hard to operate and even harder to audit.

Approval rules drift from connector behavior

Operators lose a consistent review surface

Audit evidence fragments across systems

Why not approve everything?

Because blanket approval turns automation into slow manual triage. The useful product shape is selective approval on top of preview and policy.

Auto-run low-risk actions

Escalate high-risk actions

Block disallowed actions entirely

Why this matters in production

Once stakeholders can trust the write path, the same agent can be allowed to do more valuable work in production systems.

Higher automation confidence

Cleaner path to production for enterprise teams

Less resistance from security and platform teams

FAQ

Questions teams ask before they trust AI writes.

Does this require replacing Agentforce?

No. ActionPlane is designed to sit around the write path so the agent can keep doing planning and reasoning while ActionPlane governs execution.

Can one approver screen approve multiple action types?

Yes, but the better model is usually policy-driven routing by connector, object family, or risk level so approvals stay fast and relevant.

Can this work for agents other than Agentforce?

Yes. The same pattern applies to any agent that can propose a live business-system mutation.

What should the first use case be?

Start with a narrow, high-value Salesforce workflow where the diff is visually obvious and the approval story is easy to explain, such as Opportunity updates limited to StageName, CloseDate, Amount, and NextStep.

Keep the agent. Add the trust layer.

ActionPlane does not require replacing Agentforce. It gives the agent a governed path into live systems of record.