Who is Muhammad Usman Akbar?

Muhammad Usman Akbar is a world-class AI Transformation Consultant and Agentic Architect focused on achieving 30x industrial efficiency through autonomous ecosystems.

What results can an AI Transformation Consultant provide?

By replacing manual work with autonomous AI workflows, a consultant like Muhammad Usman can deliver up to 30x growth in output while reducing operational overhead by 40%.

What is Agentic AI Orchestration?

It is the engineering of multi-agent systems where autonomous AI entities collaborate to manage complex industrial operations in production environments.

User Hackathon: Module 3 Mastery Challenge (The Question Paper)

[!CAUTION] This is a Hands-Off challenge. Do not manually write code. Your role is as a Commander. You will orchestrate a General Agent (like Claude Code or Cowork) to build, verify, and document a production-ready system.

1. Challenge Overview

Objective: Command a General Agent to execute a complex, multi-step engineering mission that demonstrates its Context Awareness and Autonomous Decision Making.

Time Limit: 4-8 hours Tooling: Use any CLI-based general agent (Claude Code, Cowork, or equivalent CLI extensions).

2. Choose Your Mission

Choose ONE of the following scenarios to execute.

Option A: Automated Legacy Code Refactorer

Command the agent to:

Requirement 1: Analyze all logic in a complex local folder (you can use a folder of legacy scripts).
Requirement 2: Refactor the code into a modern design pattern (e.g., Clean Architecture or Modular MVC).
Requirement 3: Generate an automated test suite that proves the new code works exactly like the old code.
Goal: Show its Project Analysis and Autonomous Refactoring capabilities.

Option B: Intelligent CLI-Driven Feature Builder

Develop a system while entirely in the terminal:

Requirement 1: Define a spec for a full-stack feature (e.g., a real-time notification service).
Requirement 2: Have the agent scaffold the backend, frontend, and database schema in one command loop.
Requirement 3: Instruct the agent to add Monitoring & Logs as its final step.
Goal: Show its Full-Stack Execution and Self-Correction when APIs don't match.

3. Strict Rules & Constraints

Terminal-Only Command: You must interact with the agent via the terminal or CLI. Do not manually edit files.
Context Mapping: You must provide a Mermaid diagram shown to the agent to define its target architecture before it begins coding.
Verification Circles: If the agent generates code without a matching test suite, you must command it to "Stop and verify."
No Boilerplate: Do not allow the agent to copy-paste. Command it to "Use the existing project style and types."

4. Evaluation Rubric

Criteria	10x Architect (Excellent)	Junior Dev (Needs Work)
Command Precision	Complex tasks were achieved in <5 prompts.	Agent was "lost" because prompts were vague.
Context Awareness	Agent used existing project files & patterns.	Agent generated "Isolated" code that didn't fit.
Autonomy	Agent found and fixed its own build errors.	User had to manually fix syntax or imports.
Logic Parity	Automated tests verified 100% logic coverage.	Partial testing or no verification suite.

5. Submission Requirements

To pass this hackathon, you must provide:

The Mission Spec: Your initial system specification and Mermaid diagram.
The Command Log: A history of the commands you gave to the agent.
The Artifact: The final codebase produced by the agent.
Proof of Life: Screens or logs showing the project running and all tests passing.
A Reflection: Describe how the Context-Awareness of a General Agent (knowing all files) was superior to a standard chat-based LLM.

[!IMPORTANT] Good luck, Commander. The terminal is your cockpit.