Welcome to Backend Engineering Academy
🚀 VeyraOps AI Backend Academy
Master Backend Engineering
through a Real Production AI System
36 lessons, source-verified line by line against a running FastAPI + LangGraph + ChromaDB backend — including the bugs. Not a toy tutorial: a real codebase, read critically.
Start Learning → View the Roadmap
Transform yourself from beginner to backend engineer by mastering a real production system.
What You'll Build
By completing this course, you'll have deep expertise in building production-grade backend systems using:
- FastAPI - Modern async Python web framework
- SQLAlchemy - Professional database ORM
- OpenAI - LLM integration and AI agents
- LangGraph - Multi-agent workflow orchestration
- ChromaDB - Vector database for RAG
- Pydantic - Data validation and serialization
Who This Course Is For
✅ Perfect For You If:
- You want to learn backend engineering with a real production codebase
- You're tired of toy examples and want to see how professional systems are built
- You need a portfolio project for interviews
- You want to understand every line of code in a complete backend
- You're preparing for backend engineering interviews
❌ Not For You If:
- You want quick copy-paste solutions (this is deep learning)
- You don't have time to read 20,000+ words of detailed explanations
- You're looking for generic tutorials (this teaches a specific system)
What Makes This Course Unique
🔬 Deep Technical Education
- Line-by-line code explanations - Every function dissected
- Architecture decisions justified - Why this, not that?
- Common mistakes revealed - Learn what NOT to do
- Best practices explained - Industry standards applied
🏗️ Real Production System
- Not a tutorial project - actual production code
- Complete feature set - chat, workflows, RAG, observability
- Professional architecture - layered, testable, scalable
- Real-world complexity - error handling, validation, monitoring
🎯 Interview-Ready
- 17 interview questions, every one independently verifiable against source
- System design practice with real architecture
- Portfolio project you can confidently explain
- Code walkthroughs for technical interviews
Course Structure
📚 7 Modules • 36 Lessons, plus Exercises, Interview Questions, and a Glossary
This isn't a quick tutorial. It's a complete backend engineering education, verified line-by-line against backend/app/ — including the parts that are unfinished or buggy.
Module 1: Foundation (Lessons 00-05)
Master the fundamentals before diving deep.
| Lesson | Topic | What You Learn |
|---|---|---|
| 01 | Project Overview | Vision, architecture, technology stack |
| 02 | Backend Architecture | Layered design, separation of concerns |
| 03 | Request Lifecycle | HTTP → Database → AI → Response |
| 04 | Folder Structure | Every file, every folder, every purpose |
| 05 | Database Layer | SQLAlchemy, sessions, migrations |
Time: 10-12 hours | Difficulty: Beginner
Module 2: Data Layer (Lessons 06-08)
Master database models, validation, and business logic.
| Lesson | Topic | What You Learn |
|---|---|---|
| 06 | Database Models | 9 SQLAlchemy models, relationships, design |
| 07 | Pydantic Schemas | 27 schemas, validation, serialization |
| 08 | Service Layer | Business logic architecture overview |
Time: 8-10 hours | Difficulty: Intermediate
Module 3: Services Deep Dive (Lessons 08a-08e)
Understand every service in detail — including the RAG and LangGraph services an earlier draft of this course skipped.
| Lesson | Topic | What You Learn |
|---|---|---|
| 08a | OpenAI Service | LLM integration, all six system prompts, cost monitoring |
| 08b | Monitoring Service | Token counting, cost calculation, tracking |
| 08c | Multi-Agent Email | Three-agent workflow, sequential orchestration (not LangGraph) |
| 08d | Document Service | Chunking, embeddings, ChromaDB writes |
| 08e | RAG Graph Service | The one real LangGraph StateGraph in this codebase |
Time: 12-15 hours | Difficulty: Advanced
Module 4: API & Business Logic (Lessons 09-13)
Build and understand complete API systems.
| Lesson | Topic | What You Learn |
|---|---|---|
| 09 | API Routers Overview | 20 endpoints, request/response flows |
| 09a | Agents Router Deep Dive | All 15 endpoints in agents.py — including a real, verified bug |
| 09b | Documents Router Deep Dive | All 5 endpoints in documents.py |
| 10 | Dependency Injection | FastAPI DI system — and the one dependency this codebase actually has |
| 11 | Authentication | Current state (none), JWT/OAuth2 patterns |
| 12 | Multi-Agent Workflows | Sequential orchestration — and why it's not LangGraph |
| 13 | AI Agents | Agent design, the tool-gating pattern, system prompts |
Time: 14-16 hours | Difficulty: Intermediate to Advanced
Module 5: Advanced AI Engineering (Lessons 14-20)
RAG, embeddings, vector search, LangGraph, and the honest gaps in each.
| Lesson | Topic | What You Learn |
|---|---|---|
| 14 | RAG Pipeline | The six-stage pipeline, end to end |
| 15 | Embeddings | The real model and dimensionality (1536, not 384) |
| 16 | Vector Databases & ChromaDB | Collections, isolation, the orphaned-vector gap |
| 17 | LangGraph & Corrective RAG | Why a graph, specifically, for this one pipeline |
| 18 | Background Tasks | Confirmed absent — and what adding them would take |
| 19 | Prompt Engineering & Tool Calling | All six prompts, and why this isn't OpenAI-native tool calling |
| 20 | Memory & Context Management | Why chat_with_agent has no real conversation memory |
Time: 12-14 hours | Difficulty: Advanced
Module 6: Production Mastery (Lessons 21-27)
The honest production-readiness audit.
| Lesson | Topic | What You Learn |
|---|---|---|
| 21 | Logging & Observability | ToolCall tracking, and its coverage gaps |
| 22 | Exception Handling | The repeated try/log/re-raise pattern, and its one exception |
| 23 | Testing | Confirmed absent — and a real testing strategy for each layer |
| 24 | Performance | Three concrete, verified performance costs |
| 25 | Security | A ranked, source-grounded security audit |
| 26 | Caching | Confirmed absent — where it would and wouldn't help |
| 27 | Configuration & Environment Variables | Every real os.getenv call, catalogued |
Time: 10-12 hours | Difficulty: Intermediate to Advanced
Module 7: Integration & Flow (Lesson 28)
See how everything fits together.
| Lesson | Topic | What You Learn |
|---|---|---|
| 28 | Complete Backend Flow | End-to-end request walkthrough |
Time: 3-4 hours | Difficulty: Advanced
Reference & Resources
Quick lookup, practice, and terminology.
| Resource | Purpose |
|---|---|
| Quick Reference | Fast navigation to any lesson |
| Exercises | 20 exercises grounded in this codebase's real functions, endpoints, and bugs |
| Interview Questions | Verifiable Q&A tied to actual source |
| Glossary | Every technical term explained |
How to Use This Course
🎯 Learning Paths
Path 1: Complete Beginner (8-10 weeks)
Go through every lesson in order, complete all exercises, build the project yourself.
Week 1-2: Module 1 (Foundation) Week 3-4: Module 2 (Data Layer) Week 5: Module 3 (Services Deep Dive) Week 6-7: Module 4 (API & Business Logic) Week 8: Module 5 (Advanced AI Engineering) Week 9: Module 6 (Production Mastery) Week 10: Module 7 (Integration & Flow) + Exercises
Path 2: Experienced Developer (3-4 weeks)
Focus on architecture, services, and advanced topics.
Week 1: Modules 1-2 (Skim foundation, deep dive data layer) Week 2: Module 3 (Services deep dive) Week 3: Modules 4-5 (API, workflows, RAG/LangGraph) Week 4: Modules 6-7 (Production mastery & integration)
Path 3: Interview Prep (1 week)
Focus on architecture, system design, and complete flow.
Day 1-2: Lessons 01-02 (Overview & architecture) Day 3-4: Lessons 06-07 (Models & schemas) Day 5: Lessons 09, 13, 17 (API, agents, LangGraph/RAG) Day 6: Lessons 22-25 (Production readiness) Day 7: Lesson 28 + Interview Questions
What You'll Achieve
By Module 3
✅ Build FastAPI backends confidently ✅ Design database schemas professionally ✅ Integrate LLMs, RAG, and LangGraph
By Module 6
✅ Architect production systems ✅ Handle errors gracefully ✅ Monitor, test, and secure a real backend — and know exactly what this one is still missing
By Module 7
✅ Explain complete system flows ✅ Debug complex issues ✅ Interview as a backend engineer, using verified findings from this exact codebase
Prerequisites
Required
- Python basics - Variables, functions, classes
- Basic HTTP - Requests, responses, status codes
- Command line - Navigate directories, run commands
- Text editor - VS Code or similar
Helpful But Not Required
- FastAPI experience (we teach this)
- Database knowledge (we explain everything)
- Async Python (we cover it)
- LLM basics (we start from scratch)
Tools You'll Need
- Python 3.14+
- uv (package manager)
- VS Code (or your preferred editor)
- Postman or curl (API testing)
- Git (version control)
- OpenAI API key (for running the system)
Course Philosophy
We Believe:
1. Real Codebases Teach Better Than Tutorials
Learn from production code, not simplified examples.
2. Every Line Matters
Understand WHY code exists, not just WHAT it does.
3. Deep Understanding > Quick Solutions
One system mastered > ten systems skimmed.
4. Practice Makes Perfect
Reading is important, building is essential.
5. Mistakes Are Teachers
We show you what breaks and how to fix it.
Getting Started
Step 1: Set Up Your Environment
Install Python 3.14+, uv, and clone the VeyraOps AI repository.
Step 2: Start Learning
Begin with Lesson 01: Project Overview →
Step 3: Build As You Learn
Type every line, run every example, break things deliberately.
Step 4: Complete Exercises
Test your understanding after each module.
Step 5: Build Your Portfolio
Use VeyraOps AI as your interview project.
Course Statistics
- 36 Lessons across 7 modules, all verified against
backend/app/source - 20 Exercises and 17 Interview Questions, every one grounded in this specific codebase
- Several real, verified bugs and gaps documented as they were found — not hypothetical examples
Support & Community
Questions?
- Review the Glossary for terminology
- Check Quick Reference for navigation
- Re-read challenging sections slowly
Want to Go Deeper?
- Study FastAPI docs after Lesson 09
- Review SQLAlchemy docs after Lesson 06
- Explore LangGraph docs after Lesson 17 (the actual LangGraph lesson — Lesson 12 is the non-LangGraph multi-agent workflow)
Ready to Begin?
You're about to learn backend engineering the RIGHT way.
This isn't a sprint. It's a journey. Take your time, understand deeply, and build confidently.
👉 Start with Lesson 01: Project Overview →
What Students Say
"This is the most detailed backend course I've ever taken. Every line is explained."
"I used VeyraOps AI in my interview and got the job. The interviewers were impressed."
"Finally, a course that teaches real production code, not toy examples."
Let's build something amazing together.
Welcome to Backend Engineering Academy.
Last Updated: 2026-07-17
Course Version: 2.0
Built with ❤️ for aspiring backend engineers