Tracing agent reasoning chains in Agentic Ai - Practice Problems & Coding Challenges

Challenge - 5 Problems

💻 code output

intermediate

What is the output of this agent reasoning chain?

Consider an agent that processes input through three reasoning steps, each appending a letter to a string. The initial input is an empty string.
Step 1 appends 'A', Step 2 appends 'B', Step 3 appends 'C'. What is the final output string?

Agentic_ai

def agent_chain(input_str):
    step1 = input_str + 'A'
    step2 = step1 + 'B'
    step3 = step2 + 'C'
    return step3

output = agent_chain('')
print(output)

A "ABC"

B "CBA"

C "A"

D "AB"

❓ model choice

intermediate

Which model architecture best supports tracing agent reasoning chains?

You want to build an AI agent that can explain its reasoning step-by-step. Which model architecture is best suited for this task?

A Convolutional Neural Network (CNN) for image classification

B Feedforward Neural Network without memory

C Recurrent Neural Network (RNN) with attention

D K-Nearest Neighbors (KNN) algorithm

❓ hyperparameter

advanced

Which hyperparameter adjustment improves agent reasoning chain clarity?

You have a transformer-based agent that generates reasoning chains. You want to improve the clarity and coherence of each reasoning step. Which hyperparameter change is most effective?

A Remove positional encoding

B Increase the number of attention heads

C Reduce the batch size to 1

D Decrease the learning rate drastically

❓ metrics

advanced

Which metric best evaluates the quality of agent reasoning chains?

You want to measure how well an AI agent explains its reasoning step-by-step. Which metric is most appropriate?

A Confusion matrix of classification labels

B Accuracy of final answer only

C Mean Squared Error on input features

D BLEU score comparing generated reasoning steps to reference explanations

🔧 debug

expert

What error does this agent reasoning chain code raise?

Examine the following code snippet for an agent reasoning chain. What error occurs when running it?

Agentic_ai

def reasoning_chain(input_list):
    result = []
    for i in range(len(input_list)):
        step = input_list[i] + i
        result.append(step)
    return result

output = reasoning_chain(['a', 'b', 'c'])
print(output)

A TypeError: can only concatenate str (not "int") to str

B IndexError: list index out of range

C NameError: name 'result' is not defined

D No error, output is ['a0', 'b1', 'c2']