Track B • 15 Day Bootcamp

AI &
AGENT ENGINEERING.

Move from passive LLM usage to building autonomous agentic systems.

Program Goal

Design and build intelligent AI systems using LLMs, RAG architectures, and autonomous agent workflows capable of executing complex tasks and business automation pipelines.

The Journey

15 Days of Agentic Mastery.

01
Foundations
Days 1–3
D1

Introduction to LLM Engineering

Understand the mechanics of LLMs, their architectures, and master prompt engineering techniques.

Tools: OpenAI API, Google AI Studio, LangChain
Activity: Build a simple AI assistant tool
D2

AI Tool Integration

Connect LLMs with external tools via function calling and structured outputs. Build a tool-enabled assistant.

D3

LLM Application Design

Learn design patterns for AI products, including prompt chaining, guardrails, and output validation.

02
RAG Systems
Days 4–6
D4

Introduction to RAG

Build Retrieval-Augmented Generation systems. Design knowledge bases and implement semantic search.

D5

Document Processing

Create ingestion pipelines. Master text chunking and embedding generation from PDFs and websites.

D6

Production RAG

Optimize retrieval with hybrid search and prompt grounding. Build a production-ready research assistant.

03
Agents
Days 7–9
D7

Introduction to AI Agents

Implement agent architectures with planning and reasoning. Master tool-use in autonomous agents.

D8

Agent Workflows

Build decision loops and task planning systems. Develop an autonomous research agent.

D9

Agent Memory Systems

Implement short-term and long-term memory using vector databases for context-aware agents.

04
Multi-Agents
Days 10–12
D10

Multi-Agent Collaboration

Design role-based agents (Planner, Researcher, Writer) that communicate to solve complex tasks.

D11

Autonomous Task Pipelines

Orchestrate AI workflows using LangGraph. Build event-driven pipelines for business automation.

D12

Business Automation

Integrate AI agents with SaaS tools for automated reporting, lead qualification, and document processing.

05
Autonomous Systems
Days 13–15
D13

Productionizing Agents

Implement monitoring, error handling, and safety guardrails for robust production deployment.

D14

Performance & Cost

Master token optimization, caching strategies, and response evaluation for efficient agent systems.

D15

Capstone Demo

Build and showcase a complete AI agent system. Present your autonomous business analyst or researcher.

Capstone: AI Agent Demo & Project Launch
Outcomes

What you will deliver.

  • Complete AI Agent System
  • Deployed Application
  • GitHub Repository
  • Architecture Documentation

Assessment Weights

RAG Implementation30%
Agent Architecture25%
Multi-agent Workflows20%
Deployment15%
Code Quality10%

Ready to build the
Future of Agents?

Design systems that think, plan, and execute autonomously.

Apply for Track B