Reflection and self-critique pattern in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the agent's reflection step.

Agentic AI

agent.reflection = [1]()

Drag options to blanks, or click blank then click option'

AReflectionStep

BObservationStep

CActionStep

DCritiqueStep

Attempts:

3 left

💡 Hint

Common Mistakes

Using CritiqueStep instead of ReflectionStep.

Confusing ActionStep with reflection.

Forgetting to initialize the reflection attribute.

The ReflectionStep class is used to enable the agent to reflect on its actions and outcomes.

2fill in blank

medium

Complete the code to add a self-critique after the agent's action.

Agentic AI

agent.add_step([1]())

Drag options to blanks, or click blank then click option'

AReflectionStep

BActionStep

CSelfCritiqueStep

DObservationStep

Attempts:

3 left

💡 Hint

Common Mistakes

Using ReflectionStep instead of SelfCritiqueStep.

Adding ActionStep instead of critique.

Skipping the critique step.

SelfCritiqueStep is the step where the agent evaluates its own previous action to improve.

3fill in blank

hard

Fix the error in the code to correctly perform reflection and critique.

Agentic AI

result = agent.perform_step([1])

Drag options to blanks, or click blank then click option'

ACritiqueStep

BSelfCritiqueStep()

CReflectionStep()

DActionStep()

Attempts:

3 left

💡 Hint

Common Mistakes

Using CritiqueStep without parentheses causes an error.

Passing class name instead of instance.

Using wrong step type.

SelfCritiqueStep() must be instantiated with parentheses to create an object before performing the step.

4fill in blank

hard

Fill both blanks to create a dictionary that stores reflection and critique results.

Agentic AI

results = {
  'reflection': agent.[1](),
  'critique': agent.[2]()
}

Drag options to blanks, or click blank then click option'

Areflect

Bself_critique

Caction

Dobserve

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'action' or 'observe' methods instead of reflection or critique.

Mixing up the method names.

Forgetting parentheses to call methods.

The agent.reflect() method returns reflection results, and agent.self_critique() returns critique results.

5fill in blank

hard

Fill all three blanks to define a function that runs reflection, critique, and returns combined feedback.

Agentic AI

def run_feedback(agent):
    reflection = agent.[1]()
    critique = agent.[2]()
    return {'reflection': reflection, 'critique': critique, 'summary': [3]

Drag options to blanks, or click blank then click option'

Areflect

Bself_critique

Creflection + ' and ' + critique

Dreflection + critique

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong method names.

Concatenating without spaces or connectors.

Forgetting to call methods with parentheses.

The function calls reflect() and self_critique(), then combines their strings with ' and ' for a readable summary.

Practice

1. What is the main purpose of the Reflection and self-critique pattern in AI?

easy

A. To store large amounts of data

B. To speed up AI computations

C. To help AI review and improve its own answers

D. To create new AI models automatically

Solution

1. Step 1: Understand the pattern's goal

   The reflection and self-critique pattern is designed to let AI look back at its answers and find mistakes.

2. Step 2: Identify the main benefit

   By reviewing its own work, AI can fix errors and improve future responses.

3. Final Answer:

   To help AI review and improve its own answers -> Option C

4. Quick Check:

   Reflection and self-critique = improve answers [OK]

Hint: Focus on improvement through self-review [OK]

Common Mistakes:

• Confusing speed with accuracy
• Thinking it stores data
• Assuming it creates new models

2. Which of the following is the correct way to describe the reflection step in the pattern?

easy

A. AI reviews its previous answers to find mistakes

B. AI ignores previous answers and generates new ones

C. AI deletes all previous data to start fresh

D. AI copies answers from other models without checking

Solution

1. Step 1: Define reflection in AI context

   Reflection means looking back at past answers to check for errors or improvements.

2. Step 2: Match options to definition

   Only AI reviews its previous answers to find mistakes correctly states that AI reviews previous answers to find mistakes.

3. Final Answer:

   AI reviews its previous answers to find mistakes -> Option A

4. Quick Check:

   Reflection = review past answers [OK]

Hint: Reflection means reviewing past work carefully [OK]

Common Mistakes:

• Thinking reflection means ignoring past answers
• Confusing reflection with deleting data
• Assuming copying answers is reflection

3. Consider this simple AI pseudo-code using reflection and self-critique:

answer = AI.generate_answer(question)
errors = AI.reflect(answer)
if errors:
    answer = AI.fix_errors(answer, errors)
print(answer)

What will print(answer) show if the AI finds errors?

medium

A. The original answer without changes

B. The corrected answer after fixing errors

C. No output because the program stops

D. An error message instead of an answer

Solution

1. Step 1: Understand the code flow

   The AI first generates an answer, then reflects to find errors. If errors exist, it fixes them.

2. Step 2: Determine the final printed output

   Since errors are fixed before printing, the output is the corrected answer.

3. Final Answer:

   The corrected answer after fixing errors -> Option B

4. Quick Check:

   Errors fixed before print = corrected answer [OK]

Hint: Errors fixed before print means corrected output [OK]

Common Mistakes:

• Assuming original answer prints despite errors
• Thinking program stops on errors
• Confusing error message with fixed answer

4. You have this AI code snippet:

answer = AI.generate_answer(question)
errors = AI.reflect(answer)
if errors:
    AI.fix_errors(answer, errors)
print(answer)

Why might this code fail to print the corrected answer?

medium

A. Because fix_errors does not update answer variable

B. Because reflect never finds errors

C. Because print is called before generating answer

D. Because answer is not defined

Solution

1. Step 1: Analyze variable updates

   The fix_errors function is called but its result is not assigned back to answer.

2. Step 2: Understand impact on output

   Since answer is unchanged, print shows the original, not corrected, answer.

3. Final Answer:

   Because fix_errors does not update answer variable -> Option A

4. Quick Check:

   Fix must assign back to answer [OK]

Hint: Assign fixed answer back to variable before printing [OK]

Common Mistakes:

• Assuming reflect never finds errors
• Thinking print is called too early
• Ignoring variable assignment after fixing

5. You want to improve an AI assistant using the reflection and self-critique pattern. Which approach best applies this pattern to reduce repeated mistakes over time?

hard

A. AI copies answers from a fixed database without checking

B. AI generates answers randomly to explore new possibilities

C. AI deletes old answers to save memory without review

D. After each answer, AI reviews its response, identifies errors, fixes them, and updates its knowledge base

Solution

1. Step 1: Identify key steps in the pattern

   The pattern involves reviewing answers, finding errors, fixing them, and learning from mistakes.

2. Step 2: Match approach to pattern goals

   After each answer, AI reviews its response, identifies errors, fixes them, and updates its knowledge base describes reviewing, fixing, and updating knowledge, which fits the pattern perfectly.

3. Final Answer:

   After each answer, AI reviews its response, identifies errors, fixes them, and updates its knowledge base -> Option D

4. Quick Check:

   Review + fix + learn = improved AI [OK]

Hint: Choose option with review, fix, and learning steps [OK]

Common Mistakes:

• Ignoring learning from errors
• Choosing random or fixed answers
• Skipping error identification