Hedi Manai AI Agent Builder.
Production AI systems that handle real workloads — not demos. Deep technical lessons on LangGraph, CrewAI, and MCP, plus open-source tools built to run in the real world.
About
Engineering systems that run in the real world.
With a background spanning machine learning, R&D leadership, and backend engineering, I bridge the gap between AI research and production reality. I specialize in architecting autonomous multi-agent systems that solve complex tasks through intelligent orchestration and coordination.
By leveraging the Model Context Protocol (MCP) and frameworks like LangGraph and CrewAI, I build stateful, resilient systems that move beyond prototypes. Whether it's a LangGraph tutorial for python or a complex CrewAI production deployment, I focus on delivering true operational value through scalable Python and FastAPI infrastructure.
Technical Stack & Expertise
The Agent Engineering Playbook
Mastering the art of agentic systems.
A structured curriculum for engineers building real AI systems. Short, honest breakdowns on LangGraph, CrewAI, MCP, and production prompting — what works, what breaks, and why. No fluff, no theory for its own sake.
What Is Prompt Engineering? A First Principles Introduction
A rigorous first-principles introduction to how prompts work, why they fail, and the core techniques that matter in practice.
Building the Production System Prompt — Coming Soon
Master the five-component anatomy and decision protocols required to build reliable system prompts for production agents.
Chain-of-Thought and Self-Consistency — Coming Soon
The technique that changed how we think about AI reasoning. Explore the mechanism, seven variants, and self-consistency sampling.
Prompt Chaining and Pipeline Design — Coming Soon
Decompose complex tasks into chains of focused prompts. Learn architecture choices, state management, and error handling.
RAG and Context Injection — Coming Soon
Master retrieval-augmented generation, chunking strategies, and embedding mechanics to build context-aware AI systems.
Evaluation and Testing — Coming Soon
The discipline that turns prompt engineering into engineering. Build eval datasets, choose metrics, and run regression tests.
Projects
Building AI that actually works.
A collection of autonomous agents, custom MCP servers, and automation loops. These aren't just experiments — they are functional systems designed to handle real data.
Testimonials
Words from those building the future.
From builders and teams who applied these approaches in production. Honest accounts of what these systems changed, what they simplified, and what they made possible.
Contact
Got a system to build?
If you're building a RAG pipeline, an AI agent workflow, or an MCP integration and want to compare notes, swap ideas, or just avoid the mistakes I've already made — reach out.