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    - AI Bootcamp
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Tag: AI in consulting

November 14, 2025AgileBodhi blogs

AI Meets Agile: A New Era of Digital Consulting

AI Meets Agile: A New Era of Digital Consulting The consulting world is undergoing a massive shift. Traditional methods are no longer […]

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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?

Framer Motion with React

Flask

jQuery

Bootstrap

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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

SEO optimization only

Use of CSS

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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:

Loud sound effects

High contrast alerts

Functional redundancy

Smooth transitions, microinteractions, and animations

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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:

Emotionally resonant visuals

Monospaced designs only

Backend-heavy features

Spreadsheet rendering

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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?

Prioritizing minimalism with expressive UI

Avoiding color theory

Strict functional logic only

Database query optimization

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0%

AIQ #35: Tools

/1

AI quiz 3

AIQ #35: Agent

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1 / 1

Cross-channel orchestration in MCP refers to:

Seamless messaging across devices and platforms

Siloed marketing

Sending duplicate alerts

Centralizing billing

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0%

AIQ #34: Tools

/1

AI quiz 3

AIQ #34: Agent

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1 / 1

MCP platforms often integrate with which technologies?

Blockchain wallets

CDPs and CRM systems

Image compressors

Antivirus tools

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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?

Static HTML templates

Hardcoded tags

Behavioral, transactional, and contextual data

Only demographic data

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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?

Load Time

Bounce Rate

Session Duration

Customer Lifetime Value (CLV)

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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?

User-specific email and website customization

Outbound cold-calling

Same discount for all users

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?

Larger model size

Sampling randomness

Context retrieved from reliable sources

Token pruning

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0%

AIQ #29: Tools

/1

AI quiz 3

AIQ #29: Agent

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1 / 1

Which architecture typically supports retrieval in a RAG system?

XML parser

FAISS or Pinecone vector search

Neural Network only

REST API

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0%

AIQ #28: Tools

/1

AI quiz 3

AIQ #28: Agent

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1 / 1

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

Output lacks coherence

Token inflation in prompts

Too few dependencies

Latency introduced by the retrieval step

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0%

AIQ #27: Tools

/1

AI quiz 3

AIQ #27: Agent

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1 / 1

Why does RAG outperform standard prompting for niche knowledge tasks?

It supports parallel processing

It has a longer token limit

It injects domain-specific context into responses

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?

Compile code

Encrypt model weights

Visualize neural layers

Represent semantics in vector form for retrieval

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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

Static control logic

Deterministic scripts

UX design patterns

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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?

High memory use

Inability to sense

Slow execution

No learning or long-term planning

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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

Shared GPU access

Static file errors

Improved UI consistency

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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?

Planning and decision-making module

Perception logic only

GUI interface

Static response table

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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?

Maintains long-term goals

Responds only to current perceptions without memory

Depends on rule engines

Stores historical data

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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?

Excessive human intervention

Automation bias and unpredictable errors

Slow process time

Lack of data input

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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:

Clicking a button manually

Restarting a service hourly

A scheduled daily backup

Triggering a workflow upon receiving an email

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0%

AIQ #18: Tools

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AI quiz 3

AIQ #18: Tools

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1 / 1

Which type of automation is best for handling unstructured data?

CI/CD automation

Workflow automation

Intelligent document processing

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 uses command-line interfaces

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

It’s based on hardware

It focuses only on code automation

Your score is

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?

Data encryption

Triggering external APIs within an LLM context

Model fine-tuning

API latency optimization

Your score is

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?

API latency optimization

Triggering external APIs within an LLM context

Data encryption

Model fine-tuning

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

Pretrained access to a wide range of NLP models

Web Hosting

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?

API latency optimization

Data encryption

Model fine-tuning

Triggering external APIs within an LLM context

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?

UiPath

PyTorchDVC

Selenium

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?

Converts images to code

Stores indexed document embeddings for retrieval

Acts as a data warehouse

Hosts website frontends

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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?

Real-time video streaming

Chaining of multiple prompts with memory support

File conversion capabilities

Pre-trained data sets

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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?

Adding structured examples

Using ambiguous phrasing

Minimizing the tokens used

Embedding random noise

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?

Context-free prompts

Larger models

Retrieval Augmented Generation

Few-shot learning

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:

Network latency

Data loss in storage

Compression errors

Prompt information being revealed in the output

Your score is

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 ?

Token limit constraits

Faster processing

Better creativity

Higher Accuracy

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

No task-specific examples are provided

You are fine tuning the model

The model has access to external APIs

The prompt is too vague

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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?

Unsupervised

Reinforcement

Patterned

Supervised

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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 generalize well

They struggle with uncertainty and complex patterns

They are easy to scale

They learn from data

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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?

Algorithm complexity

Biased training data

Overfitting

Unlabeled data

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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?

Statistics

Geometry

Algebra

Trigonometry

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AIQ #1: 'Strong AI'

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AI-image

AIQ #1: 'Strong AI'

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1 / 1

Which of the following best describes 'strong AI'?

AI that can simulate human behavior

AI trained only on labeled data

AI with consciousness and self-awareness

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.

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

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

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

To track the overall velocity of the team

To prioritize high-impact user stories

To estimate the effort required for each task

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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?

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

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

A. Speak with PM to rewrite functional user stories

B. Encourage team with technical execution

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0%