Skip to content
5 min read · 1,002 words

Backend Engineering Course: VeyraOps AI

A Complete Backend Engineering Education Based on a Real Production System

Welcome to a comprehensive backend engineering course built entirely around VeyraOps AI's actual codebase — not a toy example, not a generic tutorial. Every claim in this course is checked against backend/app/ directly, including the bugs.

🎯 Course Mission

This course exists to teach you every implementation in the VeyraOps AI backend until you can:

  • Rebuild the entire backend from scratch without looking at the code
  • Explain every engineering decision — and identify the ones that were never fully finished
  • Extend the system with new features confidently
  • Debug any issue by understanding the complete data flow
  • Interview as a Backend Engineer, using this project — bugs and all — as your portfolio

🧠 What Makes This Course Different

Traditional Documentation

  • Lists API endpoints
  • Shows idealized examples
  • Assumes the code is correct

This Course

  • Reads the actual source, function by function, endpoint by endpoint
  • Documents real bugs found while writing it (the broken /stats endpoint, the empty-context crash in generate_rag_answer, the chat endpoint's missing conversation memory) instead of glossing over them
  • Corrects its own earlier mistakes in the open (an earlier draft claimed the email workflow uses LangGraph — it doesn't; that's fixed and flagged in Lesson 12)
  • Is honest about what's not implemented (no auth, no tests, no caching, no background tasks) instead of inventing content for topics the code doesn't have

📚 Course Structure

36 lessons across 7 modules, plus a reference section.

ModuleLessonsFocus
1. Foundation00, 01–05Architecture, request lifecycle, folder structure, database setup
2. Data Layer06–08Models, schemas, service-layer overview
3. Services Deep Dive08a–08eLine-by-line: OpenAI, monitoring, multi-agent email, documents, RAG graph
4. API & Business Logic09, 09a–09b, 10–13Every endpoint in both routers, dependency injection, auth, workflows, agents
5. Advanced AI Engineering14–20RAG pipeline, embeddings, ChromaDB, LangGraph, background tasks, prompts, memory
6. Production Mastery21–27Logging, exception handling, testing, performance, security, caching, config
7. Integration & Flow28End-to-end request walkthrough

📖 Complete Lesson Index

🏗️ Module 1: Foundation

LessonTitle
00Course Introduction
01Project Overview
02Backend Architecture
03Request Lifecycle
04Folder Structure
05Database Layer

💾 Module 2: Data Layer

LessonTitle
06Database Models
07Pydantic Schemas
08Service Layer Overview

🔧 Module 3: Services Deep Dive

LessonTitle
08aOpenAI Service
08bMonitoring Service
08cMulti-Agent Email
08dDocument Service
08eRAG Graph Service (LangGraph)

🔌 Module 4: API & Business Logic

LessonTitle
09API Routers Overview
09aAgents Router Deep Dive
09bDocuments Router Deep Dive
10Dependency Injection
11Authentication
12Multi-Agent Workflows
13AI Agents

🤖 Module 5: Advanced AI Engineering

LessonTitle
14RAG Pipeline
15Embeddings
16Vector Databases & ChromaDB
17LangGraph & Corrective RAG
18Background Tasks
19Prompt Engineering & Tool Calling
20Memory & Context Management

🚀 Module 6: Production Mastery

LessonTitle
21Logging & Observability
22Exception Handling
23Testing
24Performance
25Security
26Caching
27Configuration & Environment Variables

🔄 Module 7: Integration & Flow

LessonTitle
28Complete Backend Flow

📚 Reference

DocumentPurpose
Exercises20 exercises, all grounded in this codebase's real functions, endpoints, and bugs
Interview QuestionsVerifiable Q&A tied to actual source
GlossaryEvery technical term explained

🎓 How to Use This Course

For Complete Beginners

  1. Start with Module 1 — Foundation is crucial
  2. Read every lesson in order — each builds on the previous
  3. Work the exercises as you go — every one is grounded in real code, not invented scenarios
  4. Type the code out yourself rather than copy-pasting

For Intermediate Developers

  1. Skim Module 1
  2. Focus on Modules 3–6 — services, APIs, advanced AI engineering, and production readiness
  3. Study Module 7 for the end-to-end picture
  4. Fix the real bugs documented throughout as exercises

For Senior Engineers

  1. Review Module 2 for data-modeling trade-offs (why estimated_cost is a String, why due_date isn't a real date type)
  2. Study Modules 5–6 for the honest gap analysis (no tests, no caching, no auth, no background tasks) and use it as a code-review exercise
  3. Use the Interview Questions to prep others, or yourself

🔧 Prerequisites

Required Knowledge

  • Python basics (variables, functions, classes)
  • Basic understanding of web concepts (HTTP, APIs)
  • Command line basics
  • SQL fundamentals
  • REST API concepts
  • JSON format

Tools You'll Need

  • Python 3.14+ and uv
  • A code editor
  • curl or Postman for API testing

📜 Philosophy

1. Real Projects Teach Better Than Toy Examples — you're learning from a production system with real trade-offs and real unfinished corners, not a contrived tutorial.

2. Every Line Matters — including the ones that are wrong. A GET endpoint that deletes data, a chat endpoint with no memory, and a factually incorrect claim in an earlier draft of this course are all left visible and explained, not quietly fixed and hidden.

3. Coverage Means Verified, Not Claimed — every lesson in this course is checked directly against backend/app/ source. Where the codebase doesn't implement something (auth, tests, caching, background tasks), the corresponding lesson says so plainly instead of describing a feature that doesn't exist.

4. Depth Over Breadth — one system understood completely, mistakes included, is worth more than ten systems understood superficially.

🚀 Let's Begin

Start with Lesson 00: Course Introduction or jump straight to Lesson 01: Project Overview.

Last Updated: 2026-07-18 Course Version: 2.0 — verified against source, gaps closed, false claims corrected

PreviousCourse IntroductionNextCourse Roadmap