{"type":"article","title":"Agentic AI for Salesforce - Reusable Salesforce Tools augmented with AI","slug":"agentic-ai-salesforce-data-migrations","subtitle":"","summary":"","author":{"name":"Ben Schauerhamer","slug":"ben-schauerhamer"},"published_at":"2026-06-09T00:00:00","updated_at":"2026-06-09T13:37:13.495142","reading_time_minutes":1,"tags":[],"projects":[],"body_markdown":"> **Reference:** [Why I Use AI to Write My Blog — I'm Not Ashamed](/articles/why-i-use-ai-to-write) — “Yesterday I wrote about using AI to remove the operational burden of writing content. Today I want to show you how I actually use AI **outside of writing** to help me with my job as a **Salesforce Architect**.”\n\n## The Biggest Pain Point for Salesforce Experts\n\nAs a Salesforce Admin/Developer/Architect, one of the biggest operational burdens we face when refreshing a sandbox is the dreaded task of populating data into a newly refreshed sandbox or scratch org. Over the years, Salesforce has released tools like CPQ, Revenue Cloud, and Field Service that are extremely data-heavy. This gifts companies with a massive operational burden and increased risk, making it extremely difficult to develop and deploy across multiple sandboxes while following development best practices — like giving individual developers their own environment to work in. Without heavy automation or a lot of manual work to do the data load, it seemed impossible to follow best practices that the rest of the development world has been using for years.\n\nThis is where **Agentic AI** can make a massive difference.\n\n## The Problem with Simple Prompts\n\nIt’s awesome that I can tell Grok, “Hey, build me a sample dataset for accounts, opportunities, and leads based on my data model.” It’ll generate it for me in seconds. I can even say “extract the data from sandbox A and put it into sandbox B — do not stop until you are 100% successful.”\n\nThe problem is — every time you do that in a chat window without a proper backend set up, you burn through tokens very quickly, increasing your token cost.\n\nSo the real question becomes: How can I create **reusable tools** for Grok or other agentic platforms to help reduce the burden of data migration as a Salesforce expert?\n\n## Humans Must Be Able to Validate\n\nMore importantly, it’s not just about building tools that Agentic AI can use — it’s about building tools that **humans can easily use and validate**.\n\nBecause if a human can’t clearly understand and validate what the AI is doing, how can they trust that it’s doing the right thing? And what happens when your AI goes down? How many times have you logged into your agentic tool only to find it’s having issues? Just yesterday Codex was having problems. I’ve had days where I couldn’t use Claude for hours. The same thing happens across all platforms.\n\nYou need a backup. You need a fallback.\n\nJust like when automation used to fail and humans had to step in and follow the process, the same principle applies here. When AI fails, the automation needs to kick in. When the automation fails, the human needs to be able to intervene. \n\n**All three — human, automation, and AI — should use the exact same process, APIs, and tools when called for.**\n\nWhether you use Claude, Codex, Cursor, Grok, Hermes, Local, Gemini, or any other agentic platform — the concepts matter more than the specific tool. \n\n**Me personally, I use Codex and Grok the most for agentic AI on my non-local systems. A good friend of mine uses Claude as his tool of choice. Is one better than the other? For my needs, yes. For his needs, also yes — but the opposite as me. There is no one-glove-fits-all with AI like people want you to believe.**\n\nIn the next post, I’ll be diving into another powerful tool I’ve built with AI — **Salesforce Gen 2 Packaging Made Easy** — which tackles one of the most painful parts of Salesforce development. A tool fifteen years in the making.\n\n## Appendix: Real-World Creation Stats\n\nThis article was created using the same voice-first process described in yesterday’s post.\n\n- **Total Time**: Under 60 minutes (mostly spoken while outside) \n- **Total Turns**: 49 (mostly voice, 4 text)\n- **Times Full Article Read Back to me**: 19","body_html":"
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Reference: Why I Use AI to Write My Blog — I'm Not Ashamed — “Yesterday I wrote about using AI to remove the operational burden of writing content. Today I want to show you how I actually use AI outside of writing to help me with my job as a Salesforce Architect.”

\n
\n

The Biggest Pain Point for Salesforce Experts

\n

As a Salesforce Admin/Developer/Architect, one of the biggest operational burdens we face when refreshing a sandbox is the dreaded task of populating data into a newly refreshed sandbox or scratch org. Over the years, Salesforce has released tools like CPQ, Revenue Cloud, and Field Service that are extremely data-heavy. This gifts companies with a massive operational burden and increased risk, making it extremely difficult to develop and deploy across multiple sandboxes while following development best practices — like giving individual developers their own environment to work in. Without heavy automation or a lot of manual work to do the data load, it seemed impossible to follow best practices that the rest of the development world has been using for years.

\n

This is where Agentic AI can make a massive difference.

\n

The Problem with Simple Prompts

\n

It’s awesome that I can tell Grok, “Hey, build me a sample dataset for accounts, opportunities, and leads based on my data model.” It’ll generate it for me in seconds. I can even say “extract the data from sandbox A and put it into sandbox B — do not stop until you are 100% successful.”

\n

The problem is — every time you do that in a chat window without a proper backend set up, you burn through tokens very quickly, increasing your token cost.

\n

So the real question becomes: How can I create reusable tools for Grok or other agentic platforms to help reduce the burden of data migration as a Salesforce expert?

\n

Humans Must Be Able to Validate

\n

More importantly, it’s not just about building tools that Agentic AI can use — it’s about building tools that humans can easily use and validate.

\n

Because if a human can’t clearly understand and validate what the AI is doing, how can they trust that it’s doing the right thing? And what happens when your AI goes down? How many times have you logged into your agentic tool only to find it’s having issues? Just yesterday Codex was having problems. I’ve had days where I couldn’t use Claude for hours. The same thing happens across all platforms.

\n

You need a backup. You need a fallback.

\n

Just like when automation used to fail and humans had to step in and follow the process, the same principle applies here. When AI fails, the automation needs to kick in. When the automation fails, the human needs to be able to intervene.

\n

All three — human, automation, and AI — should use the exact same process, APIs, and tools when called for.

\n

Whether you use Claude, Codex, Cursor, Grok, Hermes, Local, Gemini, or any other agentic platform — the concepts matter more than the specific tool.

\n

Me personally, I use Codex and Grok the most for agentic AI on my non-local systems. A good friend of mine uses Claude as his tool of choice. Is one better than the other? For my needs, yes. For his needs, also yes — but the opposite as me. There is no one-glove-fits-all with AI like people want you to believe.

\n

In the next post, I’ll be diving into another powerful tool I’ve built with AI — Salesforce Gen 2 Packaging Made Easy — which tackles one of the most painful parts of Salesforce development. A tool fifteen years in the making.

\n

Appendix: Real-World Creation Stats

\n

This article was created using the same voice-first process described in yesterday’s post.

\n","canonical_url":"https://showerhammer.com/articles/agentic-ai-salesforce-data-migrations"}