Reflection and self-critique pattern in Agentic AI

Introduction

This pattern helps AI agents think about their own answers and find ways to improve them. It makes AI smarter by learning from mistakes.

When an AI agent needs to check if its answer is good enough before giving it.

When you want the AI to learn from its own errors and improve over time.

When solving complex problems that need careful thinking and correction.

When building AI that can explain why it made a decision.

When you want to reduce mistakes in AI-generated responses.

Syntax

Agentic AI

def reflect_and_critique(agent_output):
    reflection = analyze(agent_output)
    critique = find_errors(reflection)
    improved_output = fix_errors(agent_output, critique)
    return improved_output

This is a simple function showing the pattern steps: reflection, critique, and improvement.

Each step helps the AI review and improve its own work.

Examples

This example shows a basic check for the word 'error' and fixes it.

Agentic AI

def reflect_and_critique(answer):
    print('Reflection: Checking answer quality...')
    if 'error' in answer:
        print('Critique: Found errors, fixing...')
        answer = answer.replace('error', 'correct')
    return answer

Here, the AI reflects on how confident it is and tries to improve if confidence is low.

Agentic AI

def reflect_and_critique(prediction):
    confidence = evaluate_confidence(prediction)
    if confidence < 0.7:
        prediction = improve_prediction(prediction)
    return prediction

Sample Model

This program shows an AI agent reflecting on its output, finding a mistake, and fixing it before sharing the final answer.

Agentic AI

def reflect_and_critique(agent_output):
    # Reflection step: check if output contains mistakes
    mistakes = []
    if 'mistake' in agent_output:
        mistakes.append('Found the word mistake')
    # Critique step: decide if output needs fixing
    if mistakes:
        improved_output = agent_output.replace('mistake', 'correction')
    else:
        improved_output = agent_output
    return improved_output

# Example usage
initial_output = 'This is a mistake in the answer.'
final_output = reflect_and_critique(initial_output)
print('Initial output:', initial_output)
print('Final output:', final_output)

Important Notes

Reflection helps AI pause and think about its own work.

Self-critique means finding what can be better or wrong.

Improvement is fixing mistakes to give better answers.

Summary

The reflection and self-critique pattern helps AI improve by reviewing its own answers.

It works by reflecting, finding errors, and fixing them.

This makes AI more reliable and smarter over time.