Now Assist for Creator

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Gain implementation best practices and answers to common Creator questions.

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Now Assist App Generation

What's Inside

Now Assist Flow Generation

Now Assist Code Generation

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Now Assist Catalog and Playbook Generation

Creator Best Practices

Now Assist App Generation

Now Assist App Generation

Watch Justin Abbott, AI Implementation Engineer, discuss Now Assist App Generation feedback & enhancements.

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Now Assist App Generation

Review the highlights

Customers have requested a feature to support extending existing tables, specifically the Task table in App GenerationWithout the support of extending tables, Customers may not find App Generation helpful and resort to creating applications manually

Error message: "Sorry, there was a problem on my side trying to complete the request. Try asking again later."Recommendation: check Syslog for errors

After the app is generated, carefully check for inconsistencies or inaccurate fields within testing phase

Generic Error Message in Now Assist Panel

Support for Extending Tables

Inconsistent and Incorrect Field Types Generated

Now Assist Flow Generation

Now Assist Flow Generation

Gain insights and troubleshoot common issues with Now Assist for Creator Flow Generation.

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Now Assist Flow Generation

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Creators need to fill in what Now Assist didn't

Flow edit experience

Now Assist Code Generation

Now Assist Code Generation

Justin Abbott explains areas of feedback received from customers around Now Assist Code Generation.

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Now Assist Code Generation

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Code Generation not equating to Best Practice measures

Prompt modal box blocks the generated code

Now Assist for Creator Demo

Now Assist for Creator Demo

Check out the full demo that include App Generation, Flow Generation, and Code Generation!

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Now Assist Catalog & Playbook Generation

Now Assist Catalog & Playbook Generation

Watch as Sanjana Joshi, Sr. AI Implementation Engineer, discusses insights and common issues with Now Assist Catalog & Playbook Generation

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Now Assist Catalog & Playbook Generation

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Error Messages Not Meaningful

Dynamic Behavior and UI Policies

Prompt Field Limited to 2048

Description Similar to Prompt

Prompt Not Editable

Variable Types Handling

Now Assist Catalog & Playbook Generation

Catalog & Playbook Generation Demo

Check out the full demo that includes Now Assist Catalog & Playbook Demo!

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Now Assist for Creator

Now Assist for Creator Best Practices

Watch as the ServiceNow AI Solution Success team recaps Now Assist for Creator Best Practices.

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Now Assist Skills Resources

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Prompt Field Limited to 2048

• The Playbook Now Assist prompt field is limited to 2048 characters
• If customers add more than the allowed character amount, the result would be truncated/incomplete

Error Messages Not Meaningful

• The current error handling experience thrown during generation are very standard and do not surface meaningful information
• Does not provide any actual insight into the problem leaving the users unaware of what to correct
• Currently there is a need to manually search the logs
• Future release will address the issue

Code Generation

• The modal box blocks the area that the generated code goes into
• Creators need to move the box to view the full code to decide if they want to keep it

Description Similar to Prompt

• AI generated description of catalog item is very similar to the prompt
• Customers expect a simpler and user-friendly description that can be consumed by the end user

Variable Types Handling

• Now Assist catalog builder prompt only supports a fixed set of variable
• AI can occasionally produce radio button variable types instead of the intended dropdown variable types, leading to discrepancies in the results

Prompt Not Editable

• Now Assist prompt after generation is read-only
• Will be resolved in future release

Dynamic Behavior and UI Policies

• AI skill does not generate dynamic behavior for dependent questions when mentioned in the prompt
• Customers frequently use these features to hide fields or create dependent fields

Code Generation

Customers helped identify where generated code does not follow best practice. Frequent model updates addressed quality concern over time.