Creating AI-Powered Forms

Creating an AI-powered form in Aimogen means building a structured input interface that feeds clean data into AI reasoning and workflows, instead of relying on free-form chat or static submissions. The form defines what is collected, while AI defines how it is interpreted.

An AI Form is created intentionally, not improvised.

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What You Are Building #

When you create an AI Form, you are defining:

• structured input fields
• validation and constraints
• an AI reasoning layer (model or assistant)
• optional workflows or actions
• a response strategy

The form itself is deterministic. AI operates on top of it.

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Where AI Forms Are Created #

AI Forms are created from the Aimogen admin interface.

Path:
Aimogen → AI Forms

From there you can:

• create new forms
• edit existing forms
• assign AI engines
• configure actions
• embed forms on pages or posts

AI Forms are standalone objects, reusable across the site.

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Step 1: Define the Form’s Purpose #

Before adding fields, define exactly what problem the form solves.

Good examples:

• quote request with intelligent estimation
• lead qualification with scoring
• product recommendation input
• support issue classification
• onboarding data collection
• AI-assisted content briefing

Bad examples:

• generic contact form
• simple email capture
• anything that doesn’t need reasoning

If no interpretation is needed, AI is unnecessary.

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Step 2: Add Structured Fields #

Fields are the backbone of AI Forms.

Each field:

• has a clear meaning
• collects one piece of information
• may be required or optional
• may have validation rules

Examples:

• company size
• budget range
• product interest
• problem description
• deadline
• technical level

Avoid large free-text fields unless necessary. Structure improves reliability.

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Step 3: Apply Validation and Constraints #

Validation should happen before AI is involved.

You can enforce:

• required fields
• value ranges
• formats (email, numbers)
• logical constraints

AI should interpret valid data, not fix broken input.

This reduces hallucinations and improves consistency.

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Step 4: Choose the AI Engine #

An AI Form can use:

• a raw AI model
• or an AI Assistant

Using an assistant is recommended when:

• reasoning must be consistent
• tools or files are required
• logic is reused elsewhere

The AI engine interprets the form data, not the UI.

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Step 5: Define AI Instructions #

AI instructions describe how the input should be interpreted.

Typical instruction goals:

• classify the request
• summarize user needs
• generate recommendations
• calculate estimates
• decide next steps
• produce structured output

Instructions should reference the form data, not imagined conversation.

They are system-level rules, not user prompts.

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Step 6: Configure the Output #

AI Forms can return:

• generated text
• summaries
• recommendations
• calculated values
• structured results
• confirmation messages

The output can be:

• shown to the user
• stored internally
• passed to workflows
• used to trigger actions

Output is intentional, not automatic.

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Step 7: Trigger Actions (Optional) #

AI Forms can trigger actions once processing completes.

Common actions:

• send data to a webhook
• start an OmniBlocks execution stream
• notify administrators
• create internal records
• feed CRM or automation systems

Actions are rule-based and deterministic. AI does not decide whether they run.

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Step 8: Embed the Form #

Once created, the form can be embedded:

• via shortcode
• via block
• inside pages or posts
• inside custom layouts

The form UI is separate from the AI logic. Placement does not change behavior.

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Using AI Forms with OmniBlocks #

For advanced use cases:

• the form collects structured input
• OmniBlocks validate and normalize data
• AI steps reason or transform
• actions execute downstream logic

This is ideal for complex business workflows.

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Using AI Forms with Assistants #

When paired with assistants:

• reasoning stays consistent
• tools and files are reusable
• logic scales across forms and features

The same assistant can power multiple forms.

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Frontend vs Backend Usage #

AI Forms can be used:

• publicly on the frontend
• internally in the admin
• as workflow entry points
• as internal tools

Behavior is the same in all contexts.

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What Creating an AI Form Does Not Do #

Creating an AI Form does not:

• create a chatbot
• train a model
• automate publishing
• bypass validation
• store permanent memory
• enforce compliance automatically

It defines structure and reasoning flow.

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Common Mistakes #

• using AI Forms for simple submissions
• collecting too much personal data
• relying on AI for validation
• vague or overloaded fields
• unclear output goals
• skipping testing before deployment

AI Forms reward clarity.

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Best Practices #

Design AI Forms like intelligent workflows. Keep fields explicit, validation strict, AI scoped to interpretation, and actions deterministic. Test forms in controlled environments, reuse assistants where possible, and only introduce AI where it adds real value.

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Summary #

Creating AI-powered forms in Aimogen means building structured, intelligent input systems where form fields define data and AI defines meaning. AI Forms collect clean input, apply reasoning, generate dynamic responses, and trigger workflows — all with predictability and control. When designed properly, they bridge static forms and conversational systems without sacrificing reliability.