GHL Workflow Version History: Restore AI Edits Fast

Wait Action Enhancement: TikTok DM Replies  

What’s New:
Instead of continuing after a fixed delay, your workflow can pause until someone replies to your TikTok DM.

Where in GHL:
Found in Automation → Workflows using the Wait action after sending a TikTok DM.

Impact:
Your automation responds when someone actually joins the conversation, rather than after a timer runs out.

Recommended For:
Anyone using TikTok DMs to start conversations with potential customers.

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India Recurring Mandate Support for Affiliate Indian Signup Pages  

What’s New:
Supports recurring payment mandates for Indian affiliates, helping subscriptions comply with local banking requirements.

Where in GHL:
Available on Affiliate Program signup pages for users in India.

Impact:
Creates a smoother signup experience while reducing payment failures for recurring subscriptions.

Recommended For:
Agencies, SaaS businesses, and affiliate programs onboarding customers in India.

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Housecall Pro – More Workflow Actions & Triggers  

What’s New:
Adds new workflow triggers and actions for the Housecall Pro integration, giving you more ways to automate field service processes.

Where in GHL:
Inside Automation → Workflows when using the Housecall Pro integration.

Impact:
Expands automation possibilities between HighLevel and Housecall Pro, reducing manual work and improving operational efficiency.

Recommended For:
Home service businesses, field service companies, and agencies managing Housecall Pro clients.

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Email Services Dashboard for Agencies  

What’s New:
Introduces a centralized dashboard where agencies can monitor email services across their accounts.

Where in GHL:
Found in the Agency View under the new Email Services Dashboard.

Impact:
Makes it easier to monitor email health, identify issues, and manage deliverability from one place.

Recommended For:
Agency owners, support teams, and admins managing multiple client email services.

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Email Sequences Now Available in Beta Labs  

What’s New:
Introduces Email Sequences as a Beta Labs feature, providing another way to create structured email follow-up campaigns.

Where in GHL:
Enable it from Settings → Labs, then access Email Sequences after activation.

Impact:
Cuts down the time spent checking different areas just to see how your email services are performing.

Recommended For:
Marketers, agencies, coaches, and businesses running nurture campaigns or onboarding emails.

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Group Your Contacts by Source in Dashboards & Reporting  

What’s New:
Lets you organize contact reports based on where your leads originated.

Where in GHL:
Available within Dashboards & Reporting when viewing contact analytics.

Impact:
Makes it easier to compare lead sources and identify which marketing channels are producing the best results.

Recommended For:
Marketing teams, agency owners, and businesses tracking campaign performance across multiple lead sources.

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MMLite Adoption Banner in Conversations  

What’s New:
Displays a helpful banner inside Conversations to encourage users to adopt the new MMLite messaging experience.

Where in GHL:
Appears within the Conversations module for eligible accounts.

Impact:
Helps users discover and transition to MMLite while highlighting its benefits directly inside the messaging interface.

Recommended For:
Current HighLevel users exploring the latest messaging experience and teams preparing to migrate to MMLite.

Workflow Version History now tracks the changes created by the Workflow AI Builder right inside your AI Assistant conversation. Instead of an AI edit simply changing the workflow canvas, each build or edit creates its own artifact card in the chat.

These cards appear at the point where each AI change was made. That gives you a visual trail of the different workflow iterations you’ve created while working with the AI Assistant.

GHL also makes it easy to see which iteration you’re currently using. The artifact card that matches the workflow on your canvas has a purple border. When you ask AI to make another change, the new card becomes the current version and takes the purple border.

The biggest improvement is one-click restoration. Open the three-dot menu on an older artifact card and select “Restore this version.” GHL immediately returns the workflow canvas to that iteration.

And Workflow Version History is non-destructive. Restoring an older AI iteration doesn’t wipe out the versions you created after it. Those newer iterations remain available, so you can move backward and forward between them.

You may also see an “Unsaved” pill on an artifact card when auto-save is turned off for that location. It stays there until you manually save the workflow. When auto-save is enabled, the Unsaved pill won’t appear.

Finally, AI versions aren’t being kept in a separate silo. Select “Show in version history” to open GHL Version History, where AI and manual versions appear in one unified timeline. Version History remains the main source of truth for workflow version numbering.

Workflow Version History removes one of the biggest risks of using AI to make changes inside an important automation: losing a setup that was already working.

Before this update, an AI edit didn’t have the same easy recovery path. If the AI Assistant removed a trigger, changed an action configuration, or took the workflow in the wrong direction, you could end up rebuilding parts of the automation by hand.

AI can build a workflow fast, but speed doesn’t help much if you’re nervous about changing something that already works.

The new Workflow Version History changes that.

Each AI iteration now gives you a point you can return to. You can ask the AI Assistant to try a different workflow setup, review the result, and restore an earlier iteration if the new approach isn’t better. Because restoring is non-destructive, the newer iterations remain available too.

That’s especially useful for agencies managing client workflows. Imagine using AI to restructure a lead follow-up automation. The new version might look promising, but after reviewing it, you realize the previous trigger and action setup was better.

Instead of trying to remember exactly how everything was configured, you can restore that earlier AI iteration.

There’s another important benefit. AI and manual versions feed into the same GHL Version History timeline. You don’t have one history for human edits and another for AI changes.

That keeps Workflow Version History useful as AI becomes a bigger part of building automations. You get the speed of AI without giving up the ability to recover, compare, and change direction.

Workflow Version History is built into the Workflow AI Builder and keeps track of the workflow changes you make with the AI Assistant. You can use the artifact cards in your AI conversation to see which iteration is active, restore an earlier version, and access the full Version History.

Here are the steps to create, review, and restore AI workflow iterations using Workflow Version History in GoHighLevel.

• Create an AI Workflow Iteration.
• Identify Your Current Workflow Version.
• Create Another AI Version.
• Restore an Older AI Workflow.
• Open the Full Version History.

Before you begin, make sure you’re logged in to your GoHighLevel sub-account and have a workflow you’d like to update.

• Start by using the Workflow AI Builder to create your first workflow. Once the AI finishes building it, GHL creates an artifact card for that iteration in the AI Assistant chat.

1.1 Click Automation in the menu

• This opens the main automation area where you can manage your workflows.

1.2 Click Workflows in the sub-menu

• This takes you to the Workflows section where you can create or edit your automations.

1.3 Click Build Using AI

• This opens the Workflow AI Builder so you can create a workflow using a simple prompt.

1.4 Prompt the AI Assistant to build your workflow

• Enter a clear instruction describing the workflow you want the AI Assistant to create.

1.5 Click the arrow or Build button

• Submit your prompt so the AI Assistant can generate your workflow and create the first artifact card.

• After the AI Assistant creates your workflow, use the artifact card to confirm which version is currently active on the workflow canvas.

2.1 Look at the artifact card created by the AI Assistant. Find the purple border around the card

• The card represents the workflow iteration that was created from your AI prompt.The purple border shows that this artifact card matches the workflow currently displayed on your canvas. This makes it easy to confirm which AI version you’re working with before making another change.

• Now make a second change with the AI Assistant so GHL creates another workflow iteration you can compare with the first one.

3.1 Give the AI Assistant another prompt asking it to change the workflow

• Enter a new instruction that updates or adds something to the workflow you just created.

• If you prefer an earlier AI-generated version, you can restore it directly from its artifact card without deleting the newer iterations.

4.1 Find the older artifact card you want to restore. Click the three-dot menu on that card

• Scroll through the AI Assistant conversation and locate the workflow version you want to return to.This opens the available options for that specific workflow iteration.

4.2 Select “Restore this version”

• Choose this option to make the older AI iteration active again. GHL will revert the workflow canvas to that AI iteration

• Use the full Version History when you want to view AI-generated and manual workflow versions together in one timeline.

5.1 Open the three-dot menu on the relevant artifact card

• Choose the artifact card for the workflow iteration you want to review in more detail.

5.2 Select “Show in version history”

• This opens the Version History tab, where you can see that AI iteration alongside other saved workflow versions. Version History remains the main source of truth for workflow version numbering.

GHL will open the Version History tab. Here you can view AI-created and manually created workflow versions together in one unified timeline.

Remember, the artifact cards make AI iterations easy to work with inside the conversation, but GHL Version History remains the main source of truth for workflow version numbering.

Workflow Version History gives you more freedom to experiment with the Workflow AI Builder. But a few simple habits will make those AI iterations much easier to manage.

First, try making one meaningful AI change at a time. Instead of asking the AI Assistant to completely rebuild several parts of an automation in one prompt, make focused changes. Your artifact cards will then represent clearer stages of the workflow, making it easier to decide which iteration you want to restore.

Always check the purple border before making your next move. That border tells you which artifact card matches the workflow currently displayed on your canvas. If you’ve been jumping between iterations, this quick check can prevent confusion.

Pay attention to the “Unsaved” pill too. If auto-save is turned off for your location, an artifact card can show that the workflow still needs to be manually saved. Don’t assume every AI change has already been saved just because you can see its card in the conversation.

For bigger workflow experiments, use the restore feature as a testing tool. You could ask AI to change a follow-up sequence, adjust the workflow structure, or try another approach. If you don’t like the result, restore the earlier iteration. The newer iteration remains available if you change your mind again.

Finally, remember the difference between the artifact cards and the main Version History. Artifact cards make AI iterations easy to access from your conversation, while GHL Version History keeps AI and manual versions together and remains the source of truth for version numbering.

That combination makes Workflow Version History much more useful than a simple undo button. You can experiment, compare different approaches, and return to previous AI iterations without destroying the versions you created along the way.

Workflow Version History can make the GHL Workflow AI Builder much more practical for agencies managing real client automations.

Think about a lead follow-up workflow that’s already running well. You want to improve it, so you ask the AI Assistant to change part of the automation. Maybe you want a different follow-up structure or need AI to adjust how the workflow is built.

The new version looks good at first. Then you notice the previous setup was actually better.

That’s exactly where Workflow Version History earns its keep.

Instead of manually rebuilding the previous workflow setup, you can find its artifact card and restore that AI iteration. If you later decide the newer approach was better after all, that version hasn’t been destroyed either.

For an agency, this can reduce the risk that comes with experimenting on important workflows. Your team can test AI-assisted changes while keeping earlier iterations within reach.

It can also make reviewing AI changes easier. Rather than treating every new AI edit as the final answer, you can use the different iterations to test ideas and decide which direction works best for the workflow.

The unified Version History adds another useful layer. AI and manual versions appear within the same timeline instead of creating separate histories for different ways of editing the workflow.

The big win is simple: GHL users can take advantage of faster AI-assisted workflow building while having a clearer recovery path when an edit doesn’t work out.

For agencies building and managing automations across multiple clients, that makes experimenting with AI a lot less risky.

Workflow Version History takes some of the risk out of building and editing GoHighLevel automations with AI.

Every AI build or edit now creates an artifact card inside your conversation. You can quickly see which iteration is active, restore an older version, and even return to a newer iteration later without destroying your previous work.

For agencies, that means you can be more confident when experimenting with the Workflow AI Builder. If AI changes a trigger, overwrites an action setup, or simply creates a version you don’t like, you have a much easier recovery path.

The connection with GHL Version History makes the update even more useful. AI-generated and manual versions stay together in one timeline, while Version History remains the source of truth for workflow version numbering.

So don’t treat Workflow Version History as just another undo button.

Use it to test ideas. Try different AI prompts. Compare different workflow approaches. And if an experiment doesn’t work, restore the version that did.

That’s a simple update, but it removes a major headache from AI-assisted workflow building.

Give the new Workflow AI Builder version controls a try the next time you’re working on an automation. You may find yourself a lot more willing to experiment when you know your previous AI iterations are still within reach.

Have you tried GHL Workflow Version History yet? What kind of workflow will you test it on first?