AI Best Practices for Salesforce FSC

How to validate, verify, and ensure Jarvis stays on track

Jarvis is a powerful AI tool that helps structure Salesforce decisions and generate technical guidance. However, AI is not infallible. These best practices ensure you get maximum value from Jarvis while maintaining human oversight and validation at every step.

✓
Validate
↔
Compare
⇄
Iterate
👥
Collaborate
🔍
Review
📋
Document

1. Verify Against Your Constraints

Before accepting any Jarvis output, check it against your known constraints and requirements.

  • Regulatory fit: Does this match your compliance requirements?
  • Technical feasibility: Can your team actually build this?
  • Timeline realism: Is the recommended approach achievable in your window?
  • Cost alignment: Does this match your budget constraints?
  • Org-specific limits: Is this compatible with your Salesforce edition and governor limits?

2. Test With Fresh Context

Ask Jarvis the same question multiple ways to see if the answer is consistent.

  • Ask the same question in different words
  • Add new constraints and see how the answer changes
  • Ask for the reasoning step-by-step
  • Request alternative approaches and compare them
  • If answers differ significantly, dig into why

3. Cross-Reference Official Documentation

Never rely solely on Jarvis for technical facts. Always verify against Salesforce documentation.

  • Governor limits mentioned by Jarvis—check Salesforce docs
  • API capabilities—verify in Salesforce API documentation
  • Best practices—confirm against Salesforce whitepapers
  • FSC data model—validate against official FSC architecture guides

4. Spot Common AI Mistakes

Be alert for these common AI errors:

  • Hallucinated features: AI may suggest Salesforce capabilities that don't exist
  • Outdated information: Training data may be old; verify with current docs
  • Generic advice: Advice that works for many orgs may not fit yours
  • Oversimplification: Complex problems simplified to fit in a chat box
  • Missing nuance: Context-dependent decisions treated as universal rules

Key Principle

Jarvis is a powerful thinking partner, not a decision-maker. Every piece of Jarvis output should be validated through the lens of your own expertise, constraints, and team judgment. The combination of AI speed and human judgment is far more powerful than either alone.

Always validate. Always compare. Always iterate. Always collaborate. Then document why you made your decision.