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Author: Jelin

April 3, 2025April 3, 2025AgileBodhi blogs

Elevate Your Agile Coaching: Master AI with the AI-ACF Course

Agile coaching has always been about guiding teams towards continuous improvement and adaptability. But in the age of AI, the landscape is […]

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AIQ #40: Tools

/1

AI quiz 3

AIQ #40: Vibe Coding

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1 / 1

Which framework aligns well with Vibe Coding principles?

Bootstrap

jQuery

Flask

Framer Motion with React

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0%

AIQ #39: Tools

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AI quiz 3

AIQ #39: Vibe Coding

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1 / 1

What differentiates Vibe Coding from general front-end development?

Use of HTML tags

Focus on emotional tone and engagement

Use of CSS

SEO optimization only

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0%

AIQ #38: Tools

/1

AI quiz 3

AIQ #38: Vibe Coding

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1 / 1

In Vibe Coding, ‘delightful interaction’ usually means:

Smooth transitions, microinteractions, and animations

High contrast alerts

Loud sound effects

Functional redundancy

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0%

AIQ #37: Tools

/1

AI quiz 3

AIQ #37: Vibe Coding

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1 / 1

Vibe Coding often incorporates:

Backend-heavy features

Spreadsheet rendering

Monospaced designs only

Emotionally resonant visuals

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0%

AIQ #36: Tools

/1

AI quiz 3

AIQ #36: Vibe Coding

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1 / 1

What is an important aspect of Vibe Coding?

Strict functional logic only

Database query optimization

Prioritizing minimalism with expressive UI

Avoiding color theory

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0%

AIQ #35: Tools

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AI quiz 3

AIQ #35: Agent

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1 / 1

Cross-channel orchestration in MCP refers to:

Siloed marketing

Sending duplicate alerts

Centralizing billing

Seamless messaging across devices and platforms

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0%

AIQ #34: Tools

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AI quiz 3

AIQ #34: Agent

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1 / 1

MCP platforms often integrate with which technologies?

Antivirus tools

Image compressors

Blockchain wallets

CDPs and CRM systems

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0%

AIQ #33: Tools

/1

AI quiz 3

AIQ #33: Agent

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1 / 1

What data drives personalization in MCP strategies?

Only demographic data

Behavioral, transactional, and contextual data

Hardcoded tags

Static HTML templates

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0%

AIQ #32: Tools

/1

AI quiz 3

AIQ #32: Agent

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1 / 1

What is a key KPI for measuring MCP success?

Bounce Rate

Session Duration

Customer Lifetime Value (CLV)

Load Time

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0%

AIQ #31: Tools

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AI quiz 3

AIQ #31: Agent

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1 / 1

Which of these reflects MCP in a retail environment?

Outbound cold-calling

Same discount for all users

User-specific email and website customization

One-time SMS blast

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0%

AIQ #30: Tools

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AI quiz 3

AIQ #30: Agent

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1 / 1

What ensures factual accuracy in a RAG response?

Sampling randomness

Larger model size

Token pruning

Context retrieved from reliable sources

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0%

AIQ #29: Tools

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AI quiz 3

AIQ #29: Agent

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1 / 1

Which architecture typically supports retrieval in a RAG system?

FAISS or Pinecone vector search

XML parser

Neural Network only

REST API

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0%

AIQ #28: Tools

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AI quiz 3

AIQ #28: Agent

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1 / 1

What’s one challenge of integrating RAG in production systems?

Too few dependencies

Latency introduced by the retrieval step

Token inflation in prompts

Output lacks coherence

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0%

AIQ #27: Tools

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AI quiz 3

AIQ #27: Agent

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1 / 1

Why does RAG outperform standard prompting for niche knowledge tasks?

It has a longer token limit

It injects domain-specific context into responses

It supports parallel processing

It provides up-to-date internet searches

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0%

AIQ #26: Tools

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AI quiz 3

AIQ #26: Agent

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1 / 1

In RAG pipelines, what’s the typical role of embeddings?

Visualize neural layers

Compile code

Encrypt model weights

Represent semantics in vector form for retrieval

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0%

AIQ #25: Tools

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AI quiz 3

AIQ #25: Agent

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1 / 1

An autonomous agent with self-healing capabilities would likely use:

Reinforcement learning and diagnostics

Deterministic scripts

UX design patterns

Static control logic

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0%

AIQ #24: Tools

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AI quiz 3

AIQ #24: Agent

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1 / 1

What is a limitation of reactive agents?

No learning or long-term planning

High memory use

Slow execution

Inability to sense

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0%

AIQ #23: Tools

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AI quiz 3

AIQ #23: Agent

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1 / 1

Multi-agent collaboration challenges often include:

Intra-agent communication and coordination

Static file errors

Improved UI consistency

Shared GPU access

Your score is

0%

AIQ #22: Tools

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AI quiz 3

AIQ #22: Agent

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1 / 1

Which component is essential in a deliberative agent?

Perception logic only

Planning and decision-making module

GUI interface

Static response table

Your score is

0%

AIQ #21: Tools

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AI quiz 3

AIQ #21: Agent

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1 / 1

What makes a reflex-based AI agent unique?

Stores historical data

Responds only to current perceptions without memory

Depends on rule engines

Maintains long-term goals

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0%

AIQ #20: Tools

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AI quiz 3

AIQ #20: Tools

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1 / 1

What is a key risk in AI-driven automation?

Lack of data input

Automation bias and unpredictable errors

Slow process time

Excessive human intervention

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0%

AIQ #19: Tools

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AI quiz 3

AIQ #19: Tools

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1 / 1

An example of event-driven automation would be:

Restarting a service hourly

Triggering a workflow upon receiving an email

A scheduled daily backup

Clicking a button manually

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0%

AIQ #18: Tools

/1

AI quiz 3

AIQ #18: Tools

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1 / 1

Which type of automation is best for handling unstructured data?

Workflow automation

Intelligent document processing

CI/CD automation

Static scripts

Your score is

0%

AIQ #17: Tools

/1

AI quiz 3

AIQ #17: Tools

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1 / 1

What distinguishes hyperautomation from traditional automation?

It’s based on hardware

It focuses only on code automation

It uses command-line interfaces

It combines AI, RPA, and ML for scalable end-to-end processes

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0%

AIQ #15: Tools

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AI quiz 3

AIQ #15: Tools

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1 / 1

What is the use of OpenAI’s ‘function calling’ feature?

Triggering external APIs within an LLM context

Model fine-tuning

Data encryption

API latency optimization

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0%

AIQ #16: Tools

/1

AI quiz 3

AIQ #15: Tools

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1 / 1

What is the use of OpenAI’s ‘function calling’ feature?

Data encryption

API latency optimization

Model fine-tuning

Triggering external APIs within an LLM context

Your score is

0%

AIQ #14: Tools

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AI quiz 3

AIQ #14: Tools

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1 / 1

Why is Hugging Face Transformers library widely adopted?

GPU Management

Web Hosting

Pretrained access to a wide range of NLP models

Database Sharding

Your score is

0%

/1

AI quiz 3

AIQ #15: Tools

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1 / 1

What is the use of OpenAI’s ‘function calling’ feature?

Model fine-tuning

Triggering external APIs within an LLM context

API latency optimization

Data encryption

Your score is

0%

AIQ #13: Tools

/1

AI quiz 3

AIQ #13: Tools

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1 / 1

Which of the following tools specializes in UI-based automation?

PyTorchDVC

Selenium

UiPath

PyTorch

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0%

AIQ #12: Tools

/1

AI quiz 3

AIQ #12: Tools

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1 / 1

In AI tooling, what role does a vector database play?

Stores indexed document embeddings for retrieval

Hosts website frontends

Converts images to code

Acts as a data warehouse

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0%

AIQ #11: Tools

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AI quiz 3

AIQ #11: Tools

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1 / 1

Which feature distinguishes LangChain from basic LLM interfaces?

Pre-trained data sets

Real-time video streaming

Chaining of multiple prompts with memory support

File conversion capabilities

Your score is

0%

AIQ #10: Prompt Engineering

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AI quiz 3

AIQ #10: Prompt Engineering

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1 / 1

Which of the following improves prompt robustness?

Embedding random noise

Minimizing the tokens used

Using ambiguous phrasing

Adding structured examples

Your score is

0%

AI #9: Factual Data

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AI quiz 3

AI #9: Factual Data

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1 / 1

What helps most in grounding a model’s output to factual data?

Retrieval Augmented Generation

Few-shot learning

Larger models

Context-free prompts

Your score is

0%

AI #8: Prompting

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AI quiz 3

AI #8: Prompting

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1 / 1

Prompt leakage typically refers to:

Compression errors

Prompt information being revealed in the output

Network latency

Data loss in storage

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0%

AI #7: AI Prompting

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AI quiz 3

AI #7: AI Prompting

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1 / 1

What's the downside of overly long prompts in LLMs ?

Faster processing

Token limit constraits

Higher Accuracy

Better creativity

Your score is

0%

AI #6: AI Prompting

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AI quiz 3

AI #6: AI Prompting

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1 / 1

Zero-shot prompting is best suited when

The model has access to external APIs

You are fine tuning the model

No task-specific examples are provided

The prompt is too vague

Your score is

0%

AI #5: AI Learning

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AI quiz 3

AI #5: AI Learning

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1 / 1

Which of the following is NOT a type of learning in AI?

Supervised

Reinforcement

Patterned

Unsupervised

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0%

AIQ #2: Traditional rule-based

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AI quiz 2

AIQ #2: Traditional rule-based

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1 / 1

Which of these is a limitation of traditional rule-based systems?

They learn from data

They are easy to scale

They generalize well

They struggle with uncertainty and complex patterns

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0%

AIQ #4: AI models

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AI quiz 3

AIQ #4: AI models

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1 / 1

Bias in AI models typically arises due to?

Biased training data

Algorithm complexity

Unlabeled data

Overfitting

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0%

AIQ #3: Machine Learning

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AI quiz 3

AIQ #3: Machine Learning

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1 / 1

Which mathematical concept is foundational to machine learning?

Geometry

Statistics

Algebra

Trigonometry

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AIQ #1: 'Strong AI'

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AI-image

AIQ #1: 'Strong AI'

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Which of the following best describes 'strong AI'?

AI with consciousness and self-awareness

AI that can simulate human behavior

AI trained only on labeled data

AI focused on narrow tasks

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QOW #3: Mid Sprint

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QOW #3: Mid Sprint

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1 / 1

In an Agile environment, what is the most effective way to handle an unexpected technical dependency discovered mid-sprint?

Modify the user story acceptance criteria to exclude functionality impacted by the dependency.

Assign the dependency to a respective team outside the current sprint cycle.

Continue with the sprint as planned, accepting potential delays in dependent tasks.

Halt the sprint and re-plan the backlog to accommodate the dependency.

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QOW #2: Kanban-WIP Limits

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QOW #2: Kanban-WIP Limits

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In Kanban, what is the purpose of "WIP limits" (Work in Progress)?

To track the overall velocity of the team

To define the maximum number of tasks allowed in each stage of the workflow

To estimate the effort required for each task

To prioritize high-impact user stories

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0%

QOW #1: Technical UserStory

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QOW #1: Technical UserStory

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1 / 1

Case Study: Analysing a team backlog, coach finds that user stories are technical. What should a coach do?

A. Speak with PM to rewrite functional user stories

C. Coach should ask scrum master to rewrite the user stories

B. Encourage team with technical execution

D. Speak with the engineering manager to write functional user stories

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0%