Building Real-World
AI Agents
Learn to design, build, evaluate and deploy real-world AI agents.
Go beyond agent demos. Build systems that use tools, maintain context, handle failures, retrieve knowledge, get evaluated and move toward production.
Early-bird offer closes 8 November 2026
Join the waitlist before the deadline to get early access at ₹3,999.
Building an AI agent demo is easy.
Building one that works reliably is the real challenge.
A basic agent can call a tool and produce an impressive demo. Real systems have to keep working when things don't go to plan.
This cohort focuses on what comes after the first working demo.
# the demo
user llm tool answer
# what real systems deal with
Wrong tool calls
Bad arguments
Missing context
Tool failures
Retrieval mistakes
Repeated actions & loops
Sensitive actions
Unreliable outputs
This is for you if…
You want to build production-oriented AI agents, not just demos.
You want a strong AI project for your resume and interviews.
You want to build skills relevant to real-world AI roles.
You want to stand out beyond basic LLM and RAG projects.
You want to stay ahead as AI roles increasingly move towards agentic systems.
You're serious about building real AI engineering skills, not just collecting another course certificate.
One agent. Four weeks.
Continuously evolving.
Instead of several disconnected toy agents, you build one agentic system and make it more capable and more reliable every week.
An agent that can act
- Basic Agentnew
- Tool Usenew
- State
- Context + Memory
- RAG
- Guardrails
- Human-in-the-Loop
- Evaluation
- Observability
- API
- Deployment
An agent that remembers
- Basic Agent
- Tool Use
- Statenew
- Context + Memorynew
- RAG
- Guardrails
- Human-in-the-Loop
- Evaluation
- Observability
- API
- Deployment
An agent you can trust
- Basic Agent
- Tool Use
- State
- Context + Memory
- RAGnew
- Guardrailsnew
- Human-in-the-Loopnew
- Evaluation
- Observability
- API
- Deployment
An agent you can ship
- Basic Agent
- Tool Use
- State
- Context + Memory
- RAG
- Guardrails
- Human-in-the-Loop
- Evaluationnew
- Observabilitynew
- APInew
- Deploymentnew
Basic agent → tool-using → stateful → memory → RAG → guardrails → evaluated → deployed
From first agent loop to deployment
- 01
Agent Foundations
How agents actually work — agent loops, reasoning and actions.
- 02
Tool-Using Agents
Design tools and let agents decide which actions to take.
- 03
Stateful Agents with LangGraph
Controlled workflows using graphs, state and conditional execution.
- 04
Context & Memory
Handle multi-turn conversations and preserve useful context.
- 05
Agentic RAG
Give agents external knowledge and let them decide when to retrieve.
- 06
Reliability & Guardrails
Handle failures, validate actions and add human approval where needed.
- 07
Evaluation & Observability
Test whether agents actually work and see what happened during a run.
- 08
Deployment
Take the agent from local prototype to an API-based deployed application.
Live, hands-on, built around one project
Live code-along sessions
Build alongside me during every session. Ask questions and follow the implementation step by step.
One evolving AI agent project
One serious agentic system across all 4 weeks instead of disconnected toy projects.
Hands-on coding
Every session involves building. Not slides, not theory lectures.
Notes & study material
Intuitive concept notes for every session to understand and revise the reasoning behind the code.
Complete codebase & checkpoints
Starter code, checkpoints, scripts and the final implementation, so you can revisit every stage.
Practice assignments
A practical build task after every session to extend what you learned.
Agent failure & evaluation cases
Realistic failure scenarios to learn how agents are tested beyond happy-path demos.
Session recordings
Every session recorded, with lifetime access for revision or missed sessions.
Doubt support
A dedicated group for cohort-related questions between sessions.
Small batch, more interaction
More room for questions and interaction than a large lecture-style batch.
Live on weekends, 28 November – 20 December 2026 · 8 sessions, 2 hours each.
What you need to join
- Comfortable with basic Python
- Basic understanding of LLMs and Generative AI
- Familiarity with APIs is helpful, but not required
- No prior experience with AI agents, LangGraph or RAG required
- A laptop and willingness to code along during the sessions
What you walk away with
- One complete end-to-end AI agent project
- A project you can showcase and discuss in interviews
- Practical experience building agentic systems
- An understanding of how agents move beyond demos toward reliable applications
- The complete cohort codebase
- Concept notes and architecture diagrams
- Practice implementations
- Evaluation and failure scenarios
- Lifetime access to session recordings
Akash Gupta
I build AI systems professionally as an AI Scientist. I created Concepts of AI to help learners move beyond tutorials and understand how AI systems are actually built.
In this cohort I'll build the agent live with you, explain the decisions behind each step, and show you what changes when an agent has to work outside a demo.
AI Scientist at Yal
M.Tech in Artificial Intelligence, IIT Kharagpur
B.Tech, IIT (BHU) Varanasi
Founder, Concepts of AI
What past learners said
This was a beautiful experience. I was able to learn about new platforms and was able to view all parts of deploying a project. The speaker is highly knowledgeable and experienced in this field and he was patient enough to address and explain all our queries. The sessions were insightful.
Sheba
PhD Scholar · Cohort 1
Joining CoAI was very fruitful for me personally. What sets this program apart is its intense focus on practical, real-world application. Instead of just learning isolated concepts, I was guided through building a complete, end-to-end project from scratch. This hands-on experience bridged the gap between theory and execution, giving me a deep understanding of the entire development lifecycle. I didn't just walk away with a certificate; I walked away with a production-ready portfolio piece and the confidence to tackle complex, full-scale challenges on my own.
Rudra
B.Tech · Cohort 1
Join Cohort 2
Waitlist / early-bird price
₹3,999
Regular price ₹4,999
Early-bird deadline: 8 November 2026. Join the waitlist before then to get early access at ₹3,999.
- 8 live code-along sessions · 16 hours
- Complete codebase, notes & assignments
- Lifetime access to recordings
Common questions
Ready to build beyond the demo?
Join the waitlist for early access to Cohort 2 and the ₹3,999 early-bird price.Early-bird closes 8 November 2026.