A Real Multi-Agent System
This program centers on building a working multi-agent system from the ground up.
You'll design agents with distinct roles and responsibilities.
The focus is on coordination, decision-making, and system behavior.
Trusted by 50,000+ learners worldwide
Design Multi-Agent AI Systems
Move beyond single AI assistants and start building coordinated systems of agents that reason, use tools, and collaborate.
How real agentic systems are designed and orchestrated
What You'll Learn
Advanced Agentic System Concepts
- When to move beyond workflows to autonomous agents
- How agent architectures manage state and execution flow
- How agents reason, plan, and make decisions
- How tools expand agent capabilities
- How agent behavior is evaluated and improved
Tools & Frameworks
- Proprietary and open-weight LLM providers
- Agent orchestration frameworks (LangGraph and similar)
- Toolkits for agent actions and decision loops
- Agentic evaluation tools and libraries
- Observability and debugging for agent behavior
Learn and showcase the AI skills top employers are hiring for
Real Projects From Our Program Participants
Custom RAG Workflow
LangGraph RAG Assistant
A LangGraph-powered assistant that answers complex questions using real documentation. Built with Qdrant, and ReAct-based reasoning.
Knowledge RAG Assistant
RAG System with FAISS
A production-ready RAG assistant built with LangChain and FAISS to answer questions from a structured JSON knowledge base.
Multi-Agent Research System
Cerebral Collective
A multi-agent research assistant with human oversight, built using FastAPI and local LLM inference.
Multi-Agent RAG Assistant
Lumigo Academic Q&A
A modular Q&A system for academic documents with transparent citations, fallback thesis search, and multi-agent orchestration.
Build your own multi-agent AI with Mastering AI Agents
Inspired by These Multi-Agent Systems?
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Build and publish a real multi-agent system — earn a credential if you choose
Earn Certificates and Badges (Optional)
Recognition Backed by Real Systems
- Mastering AI Agents is a hands-on program focused on designing and orchestrating multi-agent systems.
- You'll complete a substantial project and publish your work publicly — the same way professional AI engineers share their systems.
- For those who want formal recognition, an optional certificate is issued after successful project review.
Certificates and Badges (Optional)
- If you opt in, you'll receive a shareable certificate and digital badge linked to your completed project.
- Your published system remains the primary signal — something employers and collaborators can inspect.
- No multiple-choice exams. Your proof is what you build.
Multi-agent systems are becoming a core AI engineering role
Build the Skills AI Teams Are Hiring For
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What You'll Build and How It Works
How Project Review and Recognition Work
This is a self-paced, project-driven program.
You'll get full access to lessons, walkthroughs, and reference implementations.
The program culminates in one major project: a multi-agent AI system.
For those who want formal recognition, earning the Agentic AI Builder Certificate requires:
- Design and implement the system
- Publish your project with a clear write-up and GitHub repository
- Submit it for expert review
- Meet the evaluation bar based on system design and behavior
Revisions are allowed — iteration is part of real agentic development.
Learn from an Industry Leader Building Agentic Systems
Meet Your Instructor
Abhyuday Desai, Ph.D. — CEO, Ready Tensor
- Abhyuday Desai leads the design and deployment of real-world agentic AI systems at Ready Tensor.
- His work focuses on multi-agent coordination, evaluation, and real-world system reliability.
- This program reflects how agentic systems are actually designed and built in practice.
Frequently Asked Questions
Answers to common questions about the Mastering AI Agents Program.
- Who is this program for?
This program is for developers who want to move beyond single AI assistants and start building systems where multiple agents coordinate to solve complex problems. It's ideal for engineers, product builders, and AI practitioners designing multi-step or decision-driven AI workflows. You should be comfortable with Python and have some experience building AI or LLM-based applications.
- I'm new to agentic AI. Can I still take this program?
You can, but the program moves quickly into multi-agent coordination and assumes familiarity with basic agent concepts like prompts, tools, and state. If you're completely new to building AI systems, we recommend starting with Agentic AI Essentials Program first.
- What level of Python knowledge is required?
You should be comfortable with intermediate Python, including functions, classes, control flow, and working with libraries. Experience with async code is helpful but not required.
- Do I need prior experience with machine learning or data science?
No prior AI/ML or data science background is required — basic programming and API familiarity is sufficient
- How long does the program take to complete?
Most learners complete the program in about 3-4 weeks, depending on their pace, prior experience, and the complexity of their multi-agent project.
- Is the program self-paced, or are there deadlines?
The learning is fully self-paced. Project submissions are reviewed in monthly cycles, but you can submit your project whenever you're ready.
- Do I need to pay for API keys or cloud services to complete the project?
You'll need an LLM API key. Most learners stay within free or very low-cost tiers, though multi-agent systems may generate more API calls during testing.
- What happens if my project doesn't pass on the first submission?
You'll receive detailed feedback on your system design and coordination approach and can revise and resubmit your project for another review.
- Is a certificate included?
Completing the Mastering AI Agents program gives you the option to earn the Agentic AI Builder certificate after successful project review. Regardless of certification, you'll finish with a publicly published, portfolio-ready multi-agent system.
- What types of roles or projects does this program prepare me for?
This program prepares you for roles focused on AI system design and orchestration, such as AI Engineer, ML Engineer, or AI Product Engineer positions. You'll be well equipped to work on multi-agent workflows, task delegation systems, and intelligent automation projects.
Put agent orchestration and system design into practice.
Ready to Build Multi-Agent AI Systems?
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