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Hands-On Exercise Creation AI Agents - PRD

1. Product Overview

Hands-On Exercise Creation AI Agents - PRD

1.1 Product Name

Hands-On Exercise Creation AI Agents (HECA-Agent)


1.2 Product Summary

HECA-Agent is an AI-powered system that automatically generates high-quality hands-on exercises, coding tasks, labs, quizzes, datasets, projects, and assessments for education, training, and skill development. It serves educators, EdTech platforms, universities, bootcamps, corporate L&D trainers, and self-learners.


The system consists of multiple specialized agent modules capable of:

  • Generating tasks based on skill level, instructions, curriculum, or uploaded documents.

  • Producing solutions, hints, rubrics, and test cases.

  • Exporting exercises into LMS-ready formats such as PDF, Jupyter Notebook, HTML, and JSON.

  • Providing auto-grading, feedback, and difficulty scaling.



2. Problem Statement

Creating high-quality hands-on exercises is:

  • Time-consuming

  • Repetitive

  • Expensive

  • Inconsistent across instructors


Educators spend 40–60% of preparation time manually generating:

  • Coding assignments

  • STEM exercises

  • Mini-projects

  • Weekly practice sets

  • MCQs and quizzes

  • Lab instructions


Bootcamps and corporate L&D also require custom hands-on tasks for evolving technologies. Existing tools offer content, but not personalized, structured, auto-verified exercises.


There is no unified solution that can generate tasks fast, accurate, contextual, and LMS-ready.



3. Goals & Objectives

Primary Goals

  • Provide instant, high-quality, customizable hands-on exercises.

  • Reduce content creation time by 80–90%.

  • Enable scalable, automated curriculum support for trainers and organizations.

  • Support multiple domains (programming, ML, data science, DevOps, math, business analytics).


Secondary Goals

  • Build a marketplace for exercise templates.

  • Provide APIs for EdTech platforms and LMS systems.

  • Offer white-label solution for enterprise use.



4. Target Users

Primary Users

  • EdTech founders

  • Coding bootcamp instructors

  • University professors & TAs

  • Corporate L&D teams

  • Freelance trainers

  • Online course creators

  • Students/individual learners


Secondary Users

  • HR teams for skill evaluation

  • Recruitment platforms

  • Content marketplaces



5. Product Scope

5.1 In-Scope Features

  • Exercise generation

  • Test case generation

  • Hint generator

  • Multi-level difficulty scaling

  • MCQ/quiz generation

  • Lab/Notebook generator

  • Rubric creation

  • Dataset generator (synthetic)

  • Auto-grading engine

  • Export options (PDF, Notebook, HTML, CSV)

  • Multi-agent orchestration


5.2 Out-of-Scope for MVP

  • Full LMS platform

  • Real-time student collaboration

  • Video-based exercise generation

  • Plagiarism detection (future roadmap)



6. Core Features

6.1 Exercise Generator Agent

  • Generates tasks for:

    • Python, Java, JS, SQL, ML, Data Science, DevOps

    • Math & logic

    • Domain-specific cases (finance, marketing analytics)

  • Allows:

    • Difficulty: Beginner/Intermediate/Advanced

    • Type: Coding/Conceptual/Project/Scenario-based

    • Length: Short/Medium/Long

    • Context-based generation


6.2 Solution & Test Case Generator Agent

  • Generates:

    • Model solution

    • Multiple solution approaches

    • Edge cases

    • Unit tests

    • Input/output samples

  • Provides runtime validation (sandbox optional)


6.3 Hint & Step-by-Step Explanation Agent

  • Provides:

    • Progressive hints

    • Breakdown of tasks

    • Concept explanation

    • Learning feedback


6.4 MCQ & Quiz Agent

  • Generates:

    • MCQs with answer keys

    • True/False

    • Fill-in-the-blanks

    • Parameterized quizzes

  • Supports Bloom taxonomy levels


6.5 Lab/Notebook Generator Agent

  • Creates:

    • Ready-to-execute Jupyter Notebooks

    • Python .py scripts

    • Instructions + expected outputs

    • Starter code and skeleton

    • Mini datasets


6.6 Dataset Generator Agent

  • Generates realistic synthetic datasets:

    • CSV

    • JSON

    • SQL inserts

  • Industry domains: healthcare, retail, finance, HR, education


6.7 Auto-Grading Agent

  • Code execution sandbox (MVP light version using deterministic tests)

  • Compares learner output with test cases

  • Provides instant feedback

  • Summary of mistakes


6.8 Export Engine

Supports export to:

  • PDF

  • Jupyter (.ipynb)

  • HTML

  • JSON (API)

  • CSV (for datasets)




7. Multi-Agent Architecture

7.1 Agent Roles

Agent

Responsibility

Exercise Generator Agent

Creates tasks and assignments

Solution Agent

Generates and validates solutions

TestCase Agent

Creates unit tests & I/O

Notebook Agent

Converts tasks to runnable labs

Dataset Agent

Produces synthetic datasets

Hint Agent

Provides explanations

Grading Agent

Evaluates code (sandbox)


7.2 Flow

  1. User request →

  2. Exercise Agent drafts task →

  3. Solution Agent creates solution →

  4. TestCase Agent validates →

  5. Dataset Agent generates (if needed) →

  6. Notebook Agent organizes →

  7. Export engine outputs final package




8. User Stories


Educator

"As an instructor, I want to generate weekly coding exercises so I can save time preparing content."

Student

"As a learner, I want auto-graded exercises so I can know whether my understanding is correct."

EdTech Platform

"As a product owner, I want an API to generate tasks dynamically based on course progress."

Trainer

"As a corporate trainer, I want industry-case-based labs to provide real project simulations."


9. Functional Requirements

FR-1: User inputs topics, examples, or curriculum → system generates exercises.

FR-2: System generates multiple difficulty levels.

FR-3: System produces solutions + test cases.

FR-4: System exports to Notebook/PDF/HTML.

FR-5: System stores templates for future use.

FR-6: API endpoints allow integration.

FR-7: Multi-agent orchestration ensures accuracy.

FR-8: Support for 10+ programming languages.

FR-9: Auto-grading engine runs code (light sandbox).



10. Non-Functional Requirements (NFRs)

NFR-1: Performance

  • Exercise generation < 10 seconds

  • Notebook creation < 5 seconds


NFR-2: Availability

  • 99.5% uptime


NFR-3: Scalability

  • Handle 10,000 requests/day initially

  • Load balanced API


NFR-4: Security

  • No harmful code

  • Safe dataset generation

  • No student data stored


NFR-5: UX/UI

  • Minimal, clean dashboard

  • Templates

  • Quick preview



11. Competitive Analysis

Competitors

  • ChatGPT (non-structured)

  • Code.org (limited domains)

  • HackerRank / LeetCode (closed ecosystem)

  • Udemy internal AI tools

  • EdTech-specific generators


Differentiators

  • Customizable

  • Multi-domain

  • Auto-grading + dataset generation

  • Multi-agent accuracy

  • LMS-ready export

  • EdTech API-first



12. Monetization Strategy

SaaS Pricing

  • Starter: $9/mo

  • Pro: $29/mo

  • Trainer: $99/mo

  • Enterprise: Custom API


Enterprise/API

  • $500–$5,000/month depending on usage


Custom Integration (Codersarts Services)

  • $1,500–$20,000 per project

  • White-labelled agent builder



13. Risks & Mitigation

Risk

Mitigation

Incorrect exercises

Multi-agent validation

Hallucination

Test-case cross-checking

Unsafe code generation

Sanitization filters

Low adoption

Build free demo

EdTech integration complexity

API + documentation



14. Roadmap

Week 1–2

  • Multi-agent setup

  • Exercise generator MVP

  • Notebook export


Week 3–4

  • Solution + test-case agents

  • Dataset generator

  • Basic auto-grader


Week 5–6

  • UI dashboard

  • PDF/HTML export

  • Templates library


Week 7–8

  • API release

  • Enterprise customization options



15. MVP Definition (Launch-Ready)

Included:

  • Exercise creator (programming + ML basics)

  • Solutions + tests

  • Export to Notebook and PDF

  • Hint generator

  • Dataset generator (basic synthetic)

  • Simple UI dashboard

  • 5 exercise templates

  • API endpoints


Excluded:

  • Full sandbox runtime

  • Student accounts

  • Ranking/leaderboard

  • LMS automation



16. Success Metrics (KPIs)

Usage Metrics

  • Exercises generated per user/week

  • Time saved per instructor

  • API call volume


Quality Metrics

  • User rating on generated tasks

  • Pass rate on auto-grading validation


Business Metrics

  • Monthly recurring revenue (MRR)

  • Conversion from free → paid

  • Enterprise deals closed



What Codersarts Can Build as MVP (2–3 weeks)

MVP Features

  • Exercise Generator (prompt-based)

  • Difficulty scaling

  • Test case + solution generator

  • Automatic MCQ creator

  • Notebook or PDF export

  • Code evaluation sandbox (optional)


UI

  • Simple dashboard

  • Generate → Review → Export workflow

  • Saved templates


Target First Version

Programming exercises + ML labs, fully generative.






Different AI Agents Within the Product

  1. Exercise Generator Agent

  2. Task Breakdown Agent

  3. Auto-Grading Agent

  4. Hint Generator Agent

  5. Dataset Generator Agent

  6. Notebook Creator Agent

  7. Progress Evaluation Agent

  8. Teacher/Trainer Agent

  9. Exam/Quiz Generator Agent

  10. Scenario Simulation Agent(Example: "E-commerce customer churn dataset and SQL tasks")

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