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.

Practical Orchestration: Commanding General Agents Examples

In the era of Generative AI, the most critical skill for an engineer is moving from chatting to commanding. This lesson explores three high-impact orchestration examples where General Agents (like Claude Code and Cowork) demonstrate autonomous reasoning, filesystem mastery, and cross-platform execution.

Example 1: Bootstrapping persistent project memory with CLAUDE.md

The Scenario

You are starting a new Next.js project with a complex set of requirements: Tailwind CSS, Supabase for the backend, and a strict "Functional Components only" rule. Traditionally, you would have to remind a chat-based AI of these rules in every new thread.

The Agentic Solution

Instead of coding first, you command the agent: "Initialize this project and create a CLAUDE.md file that captures our architecture, styling guidelines, and build commands."

The "How" (The OODA Loop in Action):

Observe: The agent scans the filesystem to see what's already there (package.json, tsconfig.json).
Orient: It identifies that this is a TypeScript-heavy environment and realizes that without a project guide, it might make stylistic errors later.
Decide: It determines that a "Project Brain" (CLAUDE.md) is required for long-term consistency.
Act: It writes a comprehensive CLAUDE.md mapping:
- Build/Dev Commands: npm run dev, npm run lint.
- Testing: How to run Vitest or Playwright.
- Styling: Pre-defined color palettes and utility-first patterns.
- Context: A summary of what the app does (e.g., "AI-driven CRM").

Detailed Analysis: This isn't just "creating a file." It's an agent managing its own context. By establishing these boundaries early, the agent ensures that every developer (human or AI) who joins the project later adheres to the same standards.

Example 2: Deep Repository Surgery (Cross-File Orchestration)

The Scenario

The project needs a breaking change: you are migrating from a REST-based API structure to a GraphQL-based one. This affects types, frontend components, API routes, and environment variables.

The Agentic Solution

You command the agent: "Refactor all existing 'User' data fetching from REST to GraphQL. Use the new Apollo client setup and update all components that rely on the old fetchUser function."

The "How" (The OODA Loop in Action):

Observe: The agent uses grep and find to map every instance of fetchUser across the /app and /components directories.
Orient: It understands the dependency graph. It realizes that if it changes the API route but forgets a single component, the build will fail.
Decide: It creates a multi-step execution plan: (1) Define GraphQL schema, (2) Update API route, (3) Update hooks, (4) Verify with npm run build.
Act: It performs the surgery. It modifies 12 files in sequence. After every few files, it runs a background check to ensure no "lint" errors were introduced.

Detailed Analysis: A simple assistant would provide a code block for one file and tell you "do this for the others." A General Agent understands that its job is the outcome, not just the code. It takes responsibility for the entire refactor.

Example 3: Browser Core Automation with Cowork

The Scenario

You need to perform a "Competitor Intelligence" report. You need to check 5 different SaaS websites, find their pricing for "Enterprise" tiers (which are often hidden), and update a shared Notion database for the marketing team.

The Agentic Solution

Using Claude Cowork, you command: "Visit these 5 URLs, find the Enterprise pricing or contact-sales triggers, summarize their key features, and add this to our 'Competitor Research' Notion page. Then, ping the #marketing-alerts Slack channel."

The "How" (The OODA Loop in Action):

Observe: Cowork uses Browser Control to navigate to the live websites. It doesn't just "read" text; it interacts with the UI (clicking "Pricing", scrolling to the bottom).
Orient: It extracts structured data from unstructured web pages. It recognizes meaningful patterns (e.g., "Custom" usually means Enterprise).
Decide: It synthesizes the findings into a clean table format optimized for Notion.
Act:
- It uses a Notion MCP (Model Context Protocol) connector to write directly to your database.
- It triggers an Event Hook to send the Slack message once the database update is confirmed.

Detailed Analysis: This represents the "Digital FTE" (Full-Time Equivalent). The agent bridges the gap between the Open Web (Browser) and Internal Business Tools (Notion/Slack) without a human ever copy-pasting a single piece of data.

Key Takeaway

Practical Orchestration is about Decomposition. You provide the Intent, and the General Agent handles the Execution via the OODA loop. Whether it's the filesystem (Claude Code) or the desktop (Cowork), the agent is your autonomous partner in delivering production-ready outcomes.