RE2 Feedback Loops

Apply the RE2 Feedback Loops transformation to create mechanisms where system outputs influence future inputs.

What is RE2?

RE2 (Feedback Loops) Create mechanisms where system outputs influence future inputs.

When to Use RE2

Ideal Situations

• Iterate toward a better solution using feedback loops
• Refine a process through repeated cycles
• Scale a pattern through repetition and standardization

Trigger Questions

• "How can we use Feedback Loops here?"
• "What changes if we apply RE2 to this iterating a workflow over several cycles?"
• "Which assumptions does RE2 help us surface?"

The RE2 Process

Step 1: Define the focus

// Using RE2 (Feedback Loops) - Establish the focus
const focus = "Create mechanisms where system outputs influence future inputs";

Step 2: Apply the model

// Using RE2 (Feedback Loops) - Apply the transformation
const output = applyModel("RE2", focus);

Step 3: Synthesize outcomes

// Using RE2 (Feedback Loops) - Capture insights and decisions
const insights = summarize(output);

Practical Example

// Using RE2 (Feedback Loops) - Example in a iterating a workflow over several cycles
const result = applyModel("RE2", "Create mechanisms where system outputs influence future inputs" );

Integration with Other Transformations

• RE2 -> CO5: Pair with CO5 when sequencing matters.
• RE2 -> SY8: Use SY8 to validate or stress-test.
• RE2 -> IN3: Apply IN3 to compose the output.

Implementation Checklist

• [ ] Identify the context that requires RE2
• [ ] Apply the model using explicit RE2 references
• [ ] Document assumptions and outputs
• [ ] Confirm alignment with stakeholders or owners

Common Pitfalls

• Treating the model as a checklist instead of a lens
• Skipping documentation of assumptions or rationale
• Over-applying the model without validating impact

Best Practices

• Use explicit RE2 references in comments and docs
• Keep the output focused and actionable
• Combine with adjacent transformations when needed

Measurement and Success

• Clearer decisions and fewer unresolved assumptions
• Faster alignment across stakeholders
• Reusable artifacts for future iterations

Installation and Usage

Nix Installation

{
  programs.moltbot.plugins = [
    { source = "github:hummbl-dev/hummbl-agent?dir=skills/RE-recursion/re2-feedback-loops"; }
  ];
}

Manual Installation

moltbot-registry install hummbl-agent/re2-feedback-loops

Usage with Commands

/apply-transformation RE2 "Create mechanisms where system outputs influence future inputs"

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Apply RE2 to create repeatable, explicit mental model reasoning.