🧠 Masterclass in Agentic RAG & Agent Deployment:

Build Autonomous Systems with Routers, Agents, and Real-World LLMs

Welcome to the AI builder's dojo — a technically rigorous, unapologetically hands-on course for those who are done watching tutorials and ready to build autonomous, production-grade AI systems.

This isn't another passive online course. It's 15 live sessions — 7 deep-dive classes, 7 interactive office hours, and 1 epic Demo Day where you’ll present real builds.

We’ve stretched the course across 10 weeks so you can properly design, implement, and refine Agentic RAG systems with custom agents and routing logic — not just copy and paste pipelines.

🔧 What Makes This Course Different?

Other courses teach you what RAG is.

We go further — into Agentic RAG with intelligent routers, agent collaboration, and context-aware decision making.

Other courses demo CrewAI or AutoGen.

We teach you to build your own autonomous agents — and ship them to production.

Other courses use cosine similarity.

We’ll show you how to build retrieval systems that adapt, scale, and reason.

🧩 Who This Is For

If you’ve already built basic RAG apps, understand cosine similarity, vector databases, encoder-decoder models, and have some comfort with APIs and cloud infra — this is the advanced course you've been waiting for.

💥 What You Get

-10 weeks of live, high-signal content

-Weekly office hours for deep-dive help

-Real-world projects that you actually ship

-Guest lectures from AI industry leaders

-Early access to Traversaal.ai experimental tools

-Lifetime access to all materials & future updates

🚀 What You’ll Build and Learn

🧠 Agentic RAG: Beyond Just Retrieval

Design full-stack retrieval systems with autonomous agents, semantic chunking, and dynamic routers that reason about context and orchestrate multi-step tasks across tools and APIs.

🧭 Build Your Own Agent & Router Framework

No CrewAI, no wrappers. Build agents and decision routers from scratch. Understand how they communicate, choose tasks, and act — like actual autonomous systems.

📦 Hosting & Deploying LLMs

Deploy LLMs across cloud and serverless infrastructure, create inference endpoints, and understand how to monitor and scale them in real-world settings.

🔁 Continual Pretraining & Fine-Tuning

Avoid catastrophic forgetting while building pipelines for continual learning using causal language modeling and domain-specific corpora.

🧬 Model Merging & MoEs

Merge models with mergekit, use Mixture of Experts (MoE), and build adaptive routing strategies for better performance at scale.

🧮 Quantization & Inference Optimization

Speed things up and slim things down. Use quantization strategies that make your models faster and lighter without losing performance.

🛡️ Responsible AI Guardrails

Integrate ethics and safety using tools like NeMo, Colang, and Llama Guard to make sure your AI systems stay aligned and compliant.

🧠 Knowledge Graphs & DSPy

Structure your world with knowledge graphs and tap into DSPy to add logic and transparency to your AI’s decisions.

Throughout the course, we’ll reverse-engineer some of the most innovative AI systems out there — and give you exclusive access to early-stage tools being developed at Traversaal.ai, my AI startup.

📌 Prerequisites

Hands-on experience building RAG-based apps

Understanding of LLMs, encoders/decoders, and APIs

Some exposure to cloud platforms and basic DevOps

👉 Need a foundational course first? Try my other offering:

Building LLM Applications

✨ This Course Is For Builders

If you're looking for a shortcut, this isn’t it.

If you're ready to build autonomous AI systems that route intelligently, retrieve precisely, and reason like humans —