Using Assistants Across Aimogen Features

AI Assistants in Aimogen are shared, reusable reasoning components. Once created, an assistant is not locked to a single feature. It can be used consistently across content generation, chatbots, OmniBlocks, bulk workflows, and backend tools, ensuring the same logic, tone, and rules apply everywhere.

This section explains how assistants are reused and how they interact with different Aimogen features.

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Assistants as a Global AI Layer #

Assistants sit above raw models and below execution logic.

That means:

• features decide when and how AI is used
• assistants decide how the AI thinks and behaves

Once an assistant exists, any feature that supports AI engines can use it.

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Using Assistants in Chatbots #

When a chatbot uses an assistant:

• the assistant replaces the raw model
• assistant instructions define reasoning and limits
• chatbot persona adds presentation and role
• triggers and workflows still apply
• system prompts can still be appended dynamically

The assistant becomes the chatbot’s brain, while the chatbot system controls flow and UI.

This is ideal for:

• support bots
• documentation bots
• policy-aware chatbots
• product advisors

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Using Assistants in OmniBlocks #

In OmniBlocks, assistants are used as AI execution steps.

Typical pattern:

• OmniBlocks prepares structured input
• assistant interprets, summarizes, rewrites, or reasons
• outputs are passed to later blocks
• assistant behavior remains consistent across runs

Because assistants encapsulate logic, OmniBlocks workflows become:

• cleaner
• easier to maintain
• less prompt-heavy

The same assistant can power multiple execution streams.

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Using Assistants in Single Post Generation #

For single AI post creation:

• the assistant replaces the selected model
• instructions are inherited automatically
• post-specific prompts are layered on top

This ensures:

• consistent tone across posts
• consistent formatting rules
• stable editorial behavior

Changing the assistant updates behavior across all single-post usage.

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Using Assistants in Bulk Content Generation #

In bulk generators:

• each post uses the same assistant
• behavior remains consistent across hundreds or thousands of runs
• assistant instructions are not duplicated per item

This is especially valuable for:

• large content sites
• affiliate networks
• multilingual publishing
• structured editorial pipelines

Assistants prevent drift during long-running bulk jobs.

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Using Assistants in the AI Content Editor #

When used in AI Content Editing:

• the assistant controls rewrite behavior
• editing rules stay consistent
• transformations follow predefined logic

Because edits apply immediately, assistants reduce risk by enforcing predictable transformations.

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Using Assistants in the Backend Playground #

The Playground is where assistants should be:

• tested
• validated
• debugged
• refined

Backend testing:

• avoids frontend context noise
• allows fast iteration
• prevents accidental production changes

Playground testing is strongly recommended before wide reuse.

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Assistants and Model Independence #

Assistants abstract away the model choice.

This means:

• you can change the model without rewriting prompts
• workflows remain intact
• logic stays consistent

Model changes affect performance and cost, not structure.

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Assistants vs Feature Logic #

Important boundary:

• Assistants handle reasoning and transformation
• Features handle execution, structure, and rules

Assistants should not:

• decide publishing rules
• control loops or branching
• manage permissions
• replace workflows or triggers

They complement features, not replace them.

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Updating Assistants Safely #

Because assistants are shared:

• edits affect all usages instantly
• changes can have wide impact

Recommended approach:

• duplicate assistants for major changes
• test in Playground
• swap assistants in features deliberately

Treat assistants like shared services.

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Common Cross-Feature Patterns #

Typical reuse patterns include:

• one assistant for all editorial content
• one assistant for all support chatbots
• one assistant for data analysis tasks
• specialized assistants per domain or language

Avoid “one assistant for everything”.

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What Using Assistants Across Features Does Not Do #

It does not:

• synchronize state between features automatically
• merge conversations across contexts
• override feature-level limits
• bypass workflows or rules
• auto-publish content

Assistants provide behavior, not orchestration.

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Best Practices #

Design assistants narrowly, reuse them widely, test them centrally, and change them carefully. Combine assistants with OmniBlocks for structure and with chatbots for interaction. Let assistants think, let features execute.

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Summary #

Using AI Assistants across Aimogen features allows you to centralize AI behavior and reuse it consistently in chatbots, OmniBlocks, content generators, bulk workflows, and editors. Assistants provide stable reasoning and transformation logic, while features control execution and structure. When designed and reused correctly, assistants dramatically reduce complexity, prevent behavior drift, and make large-scale AI systems predictable and maintainable.