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Documentation Index

Fetch the complete documentation index at: https://docs.tensorstax.com/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

TensorStax offers two execution modes to match your workflow preferences and project requirements. Choose between full autonomous execution or human-in-the-loop mode for greater control over the agent’s actions.

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Mode Options

Interactive Control: The agent asks for confirmation after every plan step and before the session begins.
  • Review and approve each step before execution
  • Request plan updates before the agent starts
  • Redo any step as many times as needed
  • Move to the next step only when you’re satisfied
Even in human-in-the-loop mode, TensorStax will automatically attempt to fix dbt model errors on its own before asking for your input.
End-to-End Execution: The agent executes the complete plan without interruptions.
  • Runs the entire plan from start to finish
  • Self-corrects when errors occur
  • Automatically retries failed steps
  • Continues until the expected result is achieved
Flexible Corrections: Regardless of execution mode, you can always make changes afterward.
  • Use Quick Edit for simple modifications
  • Access Open Editor View for comprehensive changes
  • Manual file editing is always available
  • Make adjustments even after autonomous completion

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Choosing the Right Mode

Use Human-in-the-Loop When:

  • Working on critical production models
  • Learning how TensorStax approaches problems
  • Need to review each step for compliance
  • Want to customize the approach mid-execution

Use Autonomous When:

  • Prototyping or exploring data
  • Working on non-critical development tasks
  • Trust the agent’s decision-making
  • Need fast iteration and results
Best Practice: Start with human-in-the-loop mode for new projects to understand TensorStax’s approach, then switch to autonomous mode for similar tasks once you’re comfortable with the patterns.