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Going Live – Migrate your AI from Sandbox to Prod

Picture of Kalanithi Balasubramanian

Kalanithi Balasubramanian

Updated on April 23, 2025

Going live with your AI application, especially in a Salesforce org, involves a sequence of crucial steps seamlessly bridging the development and production environments.

The journey from sandbox testing to a full-fledged production deployment requires meticulous planning, testing, and iteration.

This comprehensive guide outlines the process, emphasizing generative AI’s trial-and-error nature and incorporating specifics from GPTfy’s documentation on prompt migration and other relevant processes.

Step 1: Test Prompts in Sandbox with Realistic Data

Start by validating your prompts against real-world data patterns.

  • Use production-like records to evaluate prompt accuracy and response quality.

  • Include edge cases, variations in data completeness, and field discrepancies

  • Focus on performance, relevance, and hallucination prevention.


This testing phase helps uncover prompt flaws early before they reach your end users.

Step 2: Export Prompts, Data Context, and AI Models

Once validated, use GPTfy’s built-in import/export utility to package:

  • Unit-tested prompts

  • Linked data context mappings

  • AI model configurations

Export everything as a JSON file for easy import into higher environments like UAT or Production.

Note - This ensures zero rework or manual configuration errors.

Step 3: Manually Transfer Any Related Apex Classes

If you’ve written custom Apex to:

  • Call external APIs

  • Handle authentication for AI Models

  • Perform enrichment or transformation tasks


Be sure to manually copy or deploy these Apex classes to the next environment first. These are rare but critical if present.

Step 4: Import to UAT or Production

Now import your prompt package into the target org.

  • Use GPTfy’s import tool to bring in Prompts, Context Mappings, and AI Models

  • Validate the integrity of objects, fields, and model settings

  • Ensure prompts reference the correct endpoints and credentials

Note- GPTfy will validate field references when you activate the prompt—fix any invalid fields before proceeding.

Step 5: Validate AI Model Connectivity

Confirm that AI models are responsive in the new org.

  • Test Named Credentials or external auth mechanisms

  • Activate a simple test prompt

  • Review security audit logs for any failed API calls

You can also run a REST call via Apex in Developer Console to double-check connectivity.

Step 6: Add GPTfy Lightning Component to Page Layouts

Embed the GPTfy Console where users will access it.

  • Update the Record Page Layout(s) for relevant objects

  • Place the GPTfy Lightning Web Component on the desired tab or section

  • For multi-layout orgs, map components based on Profile, Record Type, or Page Assignment rules

Step 7: Assign and Test Prompts One at a Time

Take a controlled rollout approach:

  • Assign the GPTfy permission set to a test user

  • Activate and assign one prompt to their profile

  • Test it on real records and confirm the output

Once verified, expand testing to more users in the same profile group.

Step 8: Verify Functionality as a New User

Use “Login As” to impersonate users and test:

  • Prompt visibility

  • Field-level access issues

  • Unexpected behaviors due to Record Type, Profile, or custom automation

Note- If a prompt writes back to Salesforce, triple-check the test scenarios to avoid unintended updates.

Step 9: Gradually Enable for Pilot Group

Avoid enabling all prompts at once. Instead:

  • Select a group of early adopters

  • Monitor usage, feedback, and performance

  • Scale up afterthe  prompt behavior is consistent

This phased rollout improves user confidence and reduces disruption.

Step 10: Monitor and Audit Prompt Performance

Once in production:

  • Monitor GPTfy audit logs and security events

  • Use the in-product feedback option to collect user insights on prompt accuracy or bias

  • Track usage volume and any failed responses


This feedback loop helps prompt engineers to refine performance over time.

Step 11: Apply Prompt Versioning and Change Control

For any prompt updates:

  • Clone and modify the prompt in Sandbox

  • Retest thoroughly

  • Use GPTfy’s migration utility to move the updated version to Prod

  • Keep version notes for traceability

Always treat prompts like production code—with testing, approvals, and rollback strategies.

Step 12: Support Change Management with Empathy

Remember, this may be your team’s first experience with AI in Salesforce.

  • Provide user guides or short videos for using prompts

  • Offer hands-on help during the rollout

  • Be patient with questions—this helps build long-term trust in your AI rollout

Summary

A successful AI go-live with GPTfy depends on rigorous testing, structured migration, and thoughtful rollout. By following this checklist, you can confidently deploy prompts that are reliable, useful, and embraced by your end users.

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