Introduction to Agentic AI (Cohort #3)
You Can Code. But Can You Build AI Agents That Think?
Here's the reality most Python developers are missing right now: you can prompt ChatGPT for a year and still be unemployable as an Agentic AI developer when companies are hiring at ₹23-25 lakhs for this exact skill.
The difference isn't just knowing LLMs. It's understanding how to architect autonomous systems that plan, decide, and execute without constant human babysitting.
While you're writing prompts, Agentic AI developers are building multi-agent systems that replace entire workflows. While you're using Copilot, they're designing agents that autonomously handle customer service, execute marketing campaigns, and write production-ready code end-to-end.
The market has already split.
The Job Market Isn't Waiting For You
Right now, startups and enterprises are scrambling to hire Agentic AI developers. Not "AI-curious" developers. Not prompt engineers. Developers who can build production-grade agentic systems using LangChain, OpenAI, and Python.
Here's what's happening in 2026:
→ Companies building multi-agent architectures for autonomous workflows → Roles paying ₹23-25 lakhs in India for Agentic AI developers (source: Glassdoor, Nov 2025) → 47% of executives prioritizing talent strategies around agentic AI for ROI in 2025 → Demand exploding for multi-agent orchestration, tool-use patterns, and RAG implementations → New hybrid roles emerging: AI Systems Orchestrator, Agent Workflow Designer, AI Governance Analyst
But here's what's not happening: companies training people from scratch. They're hiring developers who already understand agent loops, memory stores, tool integration, and multi-agent collaboration patterns.
If you're still in "learning LLM basics" mode, you're already 18 months behind the curve.
What's Actually Stopping You
You've probably used ChatGPT. Maybe you've even fine-tuned a model or built a simple RAG system.
But do you understand how to architect an agent that can: → Plan multi-step workflows autonomously? → Use external tools and APIs without explicit instructions? → Store and retrieve memory across sessions? → Collaborate with other agents in a multi-agent system? → Handle failures with reasoning and retry logic?
More importantly: can you build a production-grade multi-agent chatroom that orchestrates multiple specialized agents, manages state, and deploys as both a console app and Streamlit web UI?
If you're hesitating, you already know the answer.
The gap isn't in your Python skills. It's in your understanding of agentic architecture—the patterns, frameworks, and workflows that make autonomous AI systems actually work.
This Isn't Another LLM Course
On 04th July 11 AM IST, Vishwanathan Narayanan (Head of Software at NMIMS, Former Associate VP at JP Morgan Chase, 16+ years building enterprise AI systems) will walk you through the exact architectural thinking that separates prompt engineers from Agentic AI developers.
This isn't about writing better prompts. It's about understanding how to design systems that act autonomously.
What You'll Discover in This Introduction Session
→ Why 90% of developers misunderstand Agentic AI (and how to think like an architect instead) → The difference between assistive AI and autonomous agents (and why companies are paying 2x for the latter) → Multi-agent architectures that actually work in production (no theory—real patterns from banking, fintech, and EdTech) → Why LangChain alone won't make you employable (and what you're missing about agent orchestration) → The brutal truth about OpenAI's Agent SDK vs. building from scratch (when to use what) → How to build a multi-agent chatroom (the exact capstone project structure you'll build in the full course)
What This 20-Hour Crash Course Covers (Full Syllabus)
Module 1: Introduction to Agentic AI (2 hours)
→ Concepts, environment setup, first OpenAI API call → Understanding the shift from assistive to autonomous AI → Hands-on: Your first agent interaction
Module 2: LLM Fundamentals & Prompt Engineering (2 hours)
→ Prompts, templates, few-shot learning → Structured outputs and function calling → Hands-on: Building prompt chains
Module 3: Building Simple Agents (2 hours)
→ Agent loops and decision-making → LangChain basics and agent anatomy → Hands-on: Your first autonomous agent
Module 4: Tools, Memory & Reasoning (3 hours)
→ Tool integration and API calling → Memory stores (short-term, long-term, conversational) → ReAct (Reasoning + Acting) pattern → Hands-on: Building agents with memory and tools
Module 5: Multi-Agent Systems (2 hours)
→ Agent collaboration patterns → Orchestration vs. choreography → Agent communication protocols → Hands-on: Multi-agent workflows
Module 6: Integrating APIs & External Tools (3 hours)
→ Connecting to external APIs → File handling and data processing → Error handling in agent workflows → Hands-on: Building API-integrated agents
Module 7: Custom Agent Workflows & Planning (3 hours)
→ Task decomposition and planning algorithms → Vector stores and semantic search → Retrieval-Augmented Generation (RAG) for agents → Hands-on: Advanced agent architectures
Module 8: Capstone — Multi-Agent Chatroom (3 hours)
→ Design and build a production-ready multi-agent system → Console-based implementation → Streamlit web UI implementation → Deployment strategies
Total: 20 hours of hands-on, project-based learning
Who Should Attend This Introduction Session
→ Python developers who want to move into the fastest-growing AI niche → ML engineers tired of building models that never see production → Software engineers watching AI developer roles pay ₹23-25 lakhs while they're stuck at ₹12-18 lakhs → Tech leads who need to understand multi-agent architectures to lead AI projects → Anyone who's used ChatGPT and realized prompt engineering isn't a career path
Who This Is NOT For
→ Complete beginners with no Python experience (you need solid programming fundamentals first) → Developers looking for quick shortcuts (agentic AI requires deep architectural understanding) → Anyone expecting to "master multi-agent systems" in one session (this is an introduction; the real work comes in the full 20-hour course) → People who just want to use AI tools, not build them
Free Introduction Session Details
📅 Date: Saturday, 04th July 2026 🕐 Time: 11:00 AM IST ⏱️ Duration: 60 minutes 💰 Cost: Free 📍 Format: Live Online Session (Interactive Q&A included)
What Happens Next
This introduction session gives you the architectural thinking framework and shows you exactly what production-grade agentic AI looks like.
At the end, you'll have the option to join Batch #1 of the Complete 20-Hour Training Program.
This is a paid course with: → Comprehensive hands-on implementation across all 8 modules → Real-world capstone project (multi-agent chatroom with console + Streamlit UI) → Lifetime access to all course materials and code repositories → Direct access to Vishwanathan Narayanan for doubt resolution → Jupyter notebooks for every module → Complete project structure and deployment guides
Full transparency: This introduction session is designed to show you what's possible. The complete training is a paid program starting immediately after this session for Batch #1 participants.
No pressure. No hard sell. Just a clear pathway if you're serious about making the jump to Agentic AI development and positioning yourself for those ₹23-25 lakh roles.
About Your Instructor: Vishwanathan Narayanan
Current: Head of Software, NMIMS Previous: Associate Vice President, JP Morgan Chase Experience: 16+ years building enterprise AI systems, microservices, LMS platforms
Career Highlights: → Won Global Distinction Award at General Mills for developing first digital worker → 2x Code Wars winner → Led multi-million dollar automation solutions at JP Morgan Chase (75% efficiency increase) → Architect of LMS Portal on cloud with microservices integration → Expert in multi-agent systems, SAP integration, Spring-based workflows
Teaching Portfolio: → 260+ training programs conducted → 3000+ professionals trained → Technologies: Python, Node.js, React, Angular, Java/JEE, Data Science, Cloud (AWS/Azure), Agentic AI → Average rating: 4+ across all programs
Vishu doesn't just teach theory. He builds production systems—and he'll show you exactly how the systems he architects for enterprise clients actually work.
The Bottom Line
The Agentic AI job market is splitting right now into two categories:
Category A: Developers who understand autonomous multi-agent architectures → ₹23-25 lakhs, getting hired by startups and enterprises building the future
Category B: Everyone else → watching from the sidelines while companies build AI teams without them
04th July, 11:00 AM IST 60 minutes. Free.
You'll either see exactly what you're missing—or you'll confirm you're already on the right path.
Either way, you'll know where you stand.
Register for the Free Introduction Session Date: 04th July 2026 at 11:00 AM IST.
This is Batch #1. The seats are limited because this is a hands-on, interactive session—not a webinar where you're muted.
If you're serious about understanding what Agentic AI development actually requires, this is where it starts.
See you there.
Note: At the end of this introduction session, you'll be offered enrollment in the complete 20-hour paid training program for Batch #1. No obligation to join, but the option will be available for those who want to go deeper into building production-grade agentic systems.