Routing, Logic, & Checkpoint Blocks

Learn how to control the flow of your AI workflows using Menu, Jump, Logic, and Checkpoint blocks.

MindStudio provides four powerful block types that enable dynamic routing and decision-making in workflows. These are ideal for tailoring responses, segmenting processes, and incorporating human feedback.

Menu Block

Purpose: Presents users with a selectable menu to route them to different parts of a workflow.

How It Works:

• Add a Menu Block to your workflow.

• Define a label (e.g., "What would you like to do?").

• Add options such as "Generate Text", "Generate Image", and "Generate Video".

• For each option, connect it to a corresponding block using the output node.

Use Case: Allows the end-user to choose an action or path, similar to a multi-choice interface.

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Jump Block

Purpose: Transfers control from one workflow to another, optionally passing variables between them.

How It Works:

• Add a Jump Block at the end of a workflow.

• Select the destination workflow.

• Variables (e.g., topic) from the original workflow are automatically passed to the destination.

Use Case: Ideal for reusing workflows across multiple agents or modularizing large projects.

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Logic Block

Purpose: Allows the AI to make a decision between multiple branches using its own reasoning.

How It Works:

• Add a Logic Block with instructions (e.g., "Decide whether the comment is positive or negative").

• Define your conditions (e.g., "The comment is positive", "The comment is negative").

• Pass input (like a comment variable) and route based on AI's decision.

Use Case: When you want AI to evaluate inputs and choose an appropriate response path automatically.

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Checkpoint Block

Purpose: Inserts a human-in-the-loop approval or revision step in the workflow.

Modes:

1. Approve/Reject: Route based on user approval.

2. Revise Variable: Let users manually or interactively revise the AI’s output.

How It Works:

• Use after a generation block (e.g., a LinkedIn post draft).

• If revision is enabled:

  • Display the generated result.

  • Allow manual editing or chat-based revision with the AI.

  • Once satisfied, the user can approve to continue the workflow or reject to halt it.

Use Case: Perfect for QA workflows, content approvals, or publishing pipelines where manual oversight is needed.

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Summary

Block Type	Purpose	Key Features
Menu	Let users choose between actions	Multiple choice UI
Jump	Call and switch to another workflow	Modular design
Logic	Let AI make a decision between paths	AI-powered branching
Checkpoint	Insert human approval or revision steps	Human-in-the-loop control

By combining these blocks strategically, you can build workflows that are flexible, intelligent, and user-aware—essential for creating production-grade AI agents.

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