This guide explains what the Salesforce error FIELD_CUSTOM_VALIDATION_EXCEPTION really means, why it appears, and how to fix it without randomly turning off validation rules. It’s written for Salesforce Admins, RevOps, and Business Systems teams who are tired of cryptic errors derailing releases and support tickets.

TL;DR

• FIELD_CUSTOM_VALIDATION_EXCEPTION means a custom validation rule failed during a record save or update.
• The real question isn’t “How do I get past the error?” but “Which rule is failing and why?”
• Fix it by following a repeatable workflow: reproduce → read the error message → find the validation rule → analyze dependencies → fix or adjust the logic → retest.
• Long term, these errors usually indicate metadata debt: forgotten rules, tribal knowledge, and tightly coupled fields.
• Sweep gives you a living map of your Salesforce metadata—validation rules, dependencies, and changes—so you can debug and evolve your org without breaking everything else.

What FIELD_CUSTOM_VALIDATION_EXCEPTION Actually Means

When Salesforce throws:

FIELD_CUSTOM_VALIDATION_EXCEPTION

it’s not being dramatic. It’s literally telling you:

“A custom validation rule prevented this record from being saved.”

Behind the scenes, Salesforce evaluated one or more validation rules when someone tried to create or update a record (via UI, API, automation, integration, etc.). At least one rule returned true (i.e., “this is invalid”), so Salesforce stopped the transaction and raised the error.

Key points:

• It’s not specific to any object — you’ll see this on Leads, Accounts, Opportunities, custom objects, etc.
• It’s not one single error — it’s a category of errors generated by any custom validation rule.
• The real information is usually in the error message text or in the rule definition, not in the error code itself.

If this feels vague and unhelpful, you’re not wrong. That’s why you need a better workflow than “click around until it goes away.”

Common Scenarios That Trigger the Error

Here are the most common patterns that surface FIELD_CUSTOM_VALIDATION_EXCEPTION in the wild:

1. New required fields with hidden rules
   • A field used to be optional. Someone added a validation rule requiring it for certain stages or record types.
   • Integrations, legacy Flows, or users updating old records now fail because they don’t populate that field.
2. Stage- or status-based validations
   • Rules that say: “If Stage = Closed Won, then X must be populated.”
   • Pipelines, automations, or bulk updates try to move records without filling in those fields → boom, exception.
3. Data quality rules that weren’t scoped correctly
   • Rules intended for one team or region but applied globally.
   • Example: a rule that requires “Country” for all Accounts, but your historical data is incomplete.
4. Conflicting validations and automations
   • A Flow, Process Builder, or external tool sets a field to a value that violates a validation rule.
   • No one realizes until a batch job fails or users start seeing errors.
5. Inherited orgs with unknown landmines
   • New Admin or RevOps inherits an org with years of bandaid rules: “don’t touch this validation, no idea why it exists.”
   • Every change risks tripping something forgotten.

In other words, this error is less about “one broken rule” and more about metadata that no one fully understands anymore.

In inherited orgs, this often shows up as “landmine rules” written years ago with no documentation. If that sounds familiar, you may want to skim 5 Mistakes to Avoid When You Inherit a Salesforce Org.

Step-by-Step Checklist: How to Fix FIELD_CUSTOM_VALIDATION_EXCEPTION

This is the repeatable playbook your team can use whenever this error appears.

1. Reproduce the error on purpose

• Ask the user to show you exactly what they did (object, record, fields changed, button clicked).
• Capture:
  • Object (Lead, Opportunity, custom object, etc.)
  • The fields they edited
  • Any automations involved (screen Flows, quick actions, integrations).

If you can’t reproduce it, you can’t fix it.

2. Capture the full error message

Salesforce often shows a more specific message next to the code, like:

FIELD_CUSTOM_VALIDATION_EXCEPTION: “Close Date must be in the future when Stage is ‘Proposal’.”

Copy that text verbatim. It tells you:

• Which business rule is being enforced
• Sometimes the conditions (“when Stage is…”)

If the message is unhelpful (“There was an error saving this record”), that’s a separate problem: your validation rules aren’t written for humans.

3. Locate the offending validation rule

Go to:

• Setup → Object Manager → [Object] → Validation Rules

Then:

• Search by keywords from the error message.
• Sort by Last Modified Date to check for recent changes.
• If the error message doesn’t match any rule, look for rules targeting the fields or conditions involved (e.g., ISPICKVAL(StageName, "Proposal")).

This is where metadata visibility starts to matter: in a large org, you might be working with hundreds of rules across objects.

4. Analyze the rule logic and dependencies

Open the rule and look at:

• Rule criteria — which fields and values does it care about?
• Error location — field-level vs page-level.
• Dependencies — does this rule depend on other formulas, custom metadata types, or fields populated by Flows?

Questions to ask:

• Is this rule still aligned with current business process?
• Was it written for a legacy process that no longer exists?
• Could this rule be scoped more narrowly (record type, region, lifecycle stage)?

This is often where you discover the real issue: the rule made sense two years ago, but your GTM motion has moved on.

5. Decide what to change (don’t just turn it off)

You usually have a few options:

1. Fix the data / process, keep the rule
   • If the rule is correct and the data is wrong, you may need a clean-up, a Flow fix, or integration change.
2. Scope the rule more precisely
   • Add conditions:
     • Limit to certain record types
     • Limit to active opportunities
     • Exclude internal test records
   • Example: require a field only when Stage is in a specific subset.
3. Improve the error message
   • Make the validation’s error text clear and actionable for the end user:
     • “To move to ‘Closed Won’, please fill in Contract Start Date and Primary Contact.”
4. Retire or replace the rule
   • If no one can justify why it exists, and logs show it causes more harm than good, sunset it.
   • Replace multiple overlapping rules with one clearer, well-scoped rule.

Document what you changed and why. Otherwise, you’re just adding another layer of mystery for future-you.

6. Test in a sandbox (for non-trivial changes)

For anything beyond a simple copy edit to the error text:

• Clone the rule and test in a sandbox.
• Reproduce the original scenario and confirm:
  • Valid records save cleanly
  • Invalid records show clear messages
  • Integrations and automations behave correctly.

Only then deploy back to production.

7. Close the loop with your stakeholders

Once fixed:

• Tell users what changed, in plain language.
• Log it in your internal release notes or metadata documentation.
• If it’s a recurring pattern (e.g., stage-based rules breaking imports), consider a broader cleanup project.

This is where ad-hoc fixes become governed change instead of whack-a-mole.

How to Prevent This Error from Hijacking Your Roadmap

Fixing today’s error is great. Preventing next quarter’s flood? Better.

Think of repeated FIELD_CUSTOM_VALIDATION_EXCEPTION errors as a signal:

“Your validation rules and metadata are out of sync with how people actually use Salesforce.”

To reduce the noise long-term:

1. Standardize how you write validation rules
   • Use consistent naming, comments, and patterns.
   • Write error messages as if they’re micro-UX, not system logs.
2. Review validation rules during process changes
   • New sales stage? New lifecycle? New integration?
   • Add “Review affected validation rules” to your change checklist.
3. Track who changed what, when
   • When did this rule get added? By whom? For which project?
   • Without this, you’re relying on Slack archaeology and people’s memories.
4. Map dependencies instead of guessing
   • Understand which Flows, fields, and objects are intertwined.
   • That’s impossible to do reliably with only Setup pages and static diagrams.

At scale, this moves from “error handling” to metadata governance: keeping your org’s rules, dependencies, and processes in a state where AI and humans can trust them.

How Sweep Helps You Get Ahead of Validation Rule Chaos

This is exactly where an agentic layer for your system metadata becomes the difference between “panic in production” and “controlled change.”

With Sweep, you can:

1. See every validation rule in context

Sweep’s Documentation automatically indexes and explains Salesforce metadata—objects, fields, Flows, validation rules, and dependencies—in one searchable workspace.

• Search for the error message or referenced fields.
• See what depends on what (which rules use which fields).
• Ask an AI agent: “What does this validation rule do and where could it break things?”

2. Trace changes over time

Sweep’s Change Feed gives you a real-time audit layer for configuration changes:

• See who created or modified a validation rule and when.
• Track the history of risky rules and correlate them with incident spikes.
• Get alerts in Slack when validation rules change, so you’re not surprised in production.

3. Map processes visually

With Sweep’s Visual Workspace, you can see how validation rules interact with flows, objects, and other automations:

• Visualize end-to-end processes that touch a specific field or stage.
• Understand which configurations a change might impact before you deploy it.

The result: instead of living in fear of FIELD_CUSTOM_VALIDATION_EXCEPTION, you treat it as what it really is — a signal that your metadata deserves the same care and tooling as your application code.

If you’re dealing with recurring Salesforce errors and mystery rules, it’s a sign you don’t just need better troubleshooting. You need a living, agentic map of your metadata.

Sweep automatically documents objects, fields, validation rules, dependencies, and automation. If you want a deeper walkthrough, check out our AI-powered Salesforce Documentation tool.

Conclusion: Don’t Just Silence the Error — Fix the System

FIELD_CUSTOM_VALIDATION_EXCEPTION is not a random Salesforce tantrum. It’s your org telling you:

• “This process no longer matches the rules you wrote,” or
• “Someone hard-coded a business rule two years ago and nobody remembers why.”

You can keep playing error whack-a-mole. Or you can:

• Use a clear, repeatable workflow to find and fix the actual rule.
• Treat validation rules as part of your governed metadata, not one-off guardrails.
• Bring in tools like Sweep to make your rules visible, explainable, and safe to evolve.

In an AI-first world, messy metadata is just delayed failure. Cleaning up these rules — and seeing them in context — is how you move from fragile firefighting to governed speed.