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Learning Path

Overview Level 0Environment & Foundations Level 1LLM Fundamentals & APIs Level 2Building Simple GenAI Applications Level 3RAG Systems & Intelligent Agents Level 4Production Systems & Deployment Level 5Advanced GenAI Techniques Level 6Choose Your Specialization Path

Resources

Resources Career Paths Documentation

Your Progress

Level 2 in progress

Home RoadmapLevel 3

3

RAG Systems & Intelligent Agents

Build retrieval-augmented generation systems and multi-step autonomous agents with modern tracing and handoffs.

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Duration

3-4 weeks

📊

Difficulty

Intermediate

✓

Checkpoints

4

⚡

Est. Hours

25h

Learning Outcomes

Implement RAG systems from scratch
Build intelligent agents that make decisions
Orchestrate multiple agents working together
Trace and evaluate agent behavior
Evaluate RAG and agent performance
Handle complex multi-step reasoning

Topics to Master

•Vector databases (Pinecone, Weaviate, Qdrant)

•Embeddings and semantic search

•Retrieval-augmented generation (RAG)

•Agent architectures and handoffs

•Tool calling and function execution

•Multi-agent orchestration

•Memory strategies for agents

•Tracing and evaluation metrics

Featured Projects

OpenAI Agents Quickstart

Build triage, handoff, and tool-calling workflows with the OpenAI Agents SDK.

BeginnerLevel 0

#agents#handoffs#tool-calling

Promptfoo GPT-5.4 Evaluation Cookbook

Compare frontier models with cost, latency, and red-team checks using Promptfoo.

IntermediateLevel 1

#promptfoo#evals#red-team

Gemini 3.1 Flash-Lite Guide

Route simple tasks to Flash-Lite and harder ones to Pro with a practical hybrid router.

IntermediateLevel 2

#gemini#routing#efficiency

Opik LLM Evaluation and Monitoring

Track traces, metrics, and evaluation runs for LLM and agent workflows.

IntermediateLevel 3

#opik#monitoring#evaluation

AgentOps Evaluation

Add replay analytics, benchmarking, and monitoring to multi-agent systems.

IntermediateLevel 3

#agentops#monitoring#agents

RAG-Powered Chatbot

Build a chatbot that retrieves and references documents in its responses.

IntermediateLevel 3

#rag#vector-db#retrieval

View all 17 projects

Checkpoints & Milestones

This level includes 4 structured checkpoints with hands-on tasks, validation criteria, and portfolio pieces. Complete these to solidify your understanding.

View Checkpoints →

Level 2: Building Simple GenAI Applications

Level 4: Production Systems & Deployment