​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 28th February at 06 PM 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, 28th February 2026
🕐 Time: 06:00 PM 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

​28th February, 06:00 PM.
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: 28th February 2026
Time: 06:00 PM

​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.