1. Introduction: Why GenAI Engineering 2025?

• chunk: 1.0 – Intro
• chunk: 1.1 – Trends, opportunities, challenges (Methods: AI adoption, GenAI impact; Tools: None)
• chunk: 1.2 – Motivation, goals, story setup (Methods: Learning journey, Tools: None)
• chunk: 1.3 – Summary

2. Foundations: Software Engineering, Roles & Economics

• chunk: 2.0 – Intro
• chunk: 2.1 – Software engineering basics, lifecycle, roles (Methods: Make it work/right/fast, SDLC, Agile, DevOps; Tools: None)
• chunk: 2.2 – Design thinking & AI (Methods: Design Thinking, User Stories, Ideation; Tools: Miro, Figma)
• chunk: 2.3 – Software economics, team dynamics (Methods: Cost estimation, Team roles, ROI; Tools: Excel, Jira)
• chunk: 2.4 – Summary

Make it Work – From Idea to Prototype & Alternatives

• chunk: 3.0 – Intro
• chunk: 3.1 – Python & Core Libraries (Methods: Scripting, Data wrangling, DataFrames; Tools: Python 3.12+, uv, Asyncio, JupyterLab, Pandas, Polars, PyArrow, DuckDB)
• chunk: 3.2 – LLM Basics & Prompt Engineering (Methods: Prompt templates, Zero/Few-shot, System prompts; Tools: OpenAI API, Prompt Engineering Patterns)
• chunk: 3.3 – First Toolchain Setup (Methods: Model loading, API integration, Chaining; Tools: Hugging Face Transformers, LangChain, LlamaIndex)
• chunk: 3.4 – Basic RAG Pipeline (Methods: Simple chunking, Embeddings, Retrieval; Tools: PRIMARY: Pinecone, OpenAI Embeddings)
• chunk: 3.5 – UI & Dev Environment Basics (Methods: Rapid prototyping, App scaffolding; Tools: VSCode, Streamlit, Codespaces)
• chunk: 3.6 – Alternative Approaches (No-Code, SaaS) (Methods: Workflow automation, Visual programming; Tools: Langflow, N8N, Pipedream, Bubble, FlutterFlow)
• chunk: 3.7 – Basic Monitoring & Logging (Methods: Print logging, Basic dashboards; Tools: Print, Logging, Simple Dashboards)
• chunk: 3.8 – Team Hacking & Collaboration (Methods: Git workflow, Pair programming, Async collab; Tools: Git, GitHub, Slack)
• chunk: 3.9 – Summary

Make it Right – Robust, Secure & Maintainable

• chunk: 4.0 – Intro
• chunk: 4.1 – Security Basics & Compliance (Methods: Secret management, AuthN/Z, Threat modeling; Tools: PRIMARY: .env, OAuth2, SECONDARY: Vault, JWT, Snyk)
• chunk: 4.2 – Containerization Basics (Methods: Containerization, Image building, Isolation; Tools: PRIMARY: Docker, Docker Compose)
• chunk: 4.3 – Monitoring & Testing Frameworks (Methods: Unit/integration testing, Alerting, Metrics; Tools: PRIMARY: Pytest, Python Logging, SECONDARY: Prometheus)
• chunk: 4.4 – Advanced RAG Techniques (Methods: Semantic/hierarchical chunking, Hybrid retrieval, Reranking, Fact-checking; Tools: PRIMARY: Pinecone Advanced Features, SECONDARY: Qdrant, Milvus, Cohere Embeddings)
• chunk: 4.5 – UI Deep Dive: Conversational UX & Adaptive UIs (Methods: User flows, Adaptive interfaces, Multi-modal UX; Tools: PRIMARY: React, NextJS, SECONDARY: Streamlit, Gradio)
• chunk: 4.6 – Responsible AI & Bias Mitigation (Methods: Guardrails, Bias detection, Explainability; Tools: PRIMARY: Presidio, SECONDARY: TruLens, Azure AI Content Safety)
• chunk: 4.7 – Software Economics Deep Dive (Methods: Cost modeling, Cloud billing analysis; Tools: PRIMARY: Cloud Cost Calculators, SECONDARY: AWS/Azure Billing)
• chunk: 4.8 – AI Coding Tools & Dev Environment Pro (Methods: AI code completion, Copilot patterns, Prompt-based coding; Tools: PRIMARY: Cursor, SECONDARY: GitHub Copilot, Windsurf, Claude Code, Tabnine)
• chunk: 4.9 – Team & Collaboration Best Practices (Methods: Code reviews, CI workflows, Agile retros; Tools: PRIMARY: GitHub Actions, SECONDARY: Jira, Code Review)
• chunk: 4.10 – Summary

Make it Fast – Scaling, Orchestration, Enterprise-Ready

• chunk: 5.0 – Intro
• chunk: 5.1 – Faster and more type-secure programming language (Methods: Static typing, Type-checking, Compiling; Tools: PRIMARY: Pydantic, TypeScript, SECONDARY: Go, Rust)
• chunk: 5.2 – Container Orchestration & Scheduling (Methods: Cluster management, Auto-scaling, Rolling updates; Tools: PRIMARY: Kubernetes, SECONDARY: Helm, Ray Serve)
• chunk: 5.3 – Advanced Model Serving Frameworks (Methods: Model versioning, Batching, High-throughput serving; Tools: PRIMARY: vLLM, SECONDARY: BentoML, Hugging Face TGI, NVIDIA Triton)
• chunk: 5.4 – Scaling RAG & Multi-Agent Architectures (Methods: Multi-agent orchestration, Distributed retrieval, Agent collaboration; Tools: PRIMARY: CrewAI, SECONDARY: PydanticAI, AutoGen, Langflow)
• chunk: 5.5 – Monitoring & Observability at Scale (Methods: Distributed tracing, Metrics aggregation, Alerting; Tools: PRIMARY: LangSmith, SECONDARY: Prometheus, Grafana, Langfuse, OpenTelemetry)
• chunk: 5.6 – Cloud Best Practices & Cost Optimization (Methods: Infra as Code, Autoscaling, Spot instances, Budgeting; Tools: PRIMARY: Terraform, SECONDARY: AWS Sagemaker, Azure ML, GCP Vertex AI)
• chunk: 5.7 – Advanced Security & Compliance (Methods: Audit logging, Rate limiting, Compliance automation; Tools: PRIMARY: HashiCorp Vault, SECONDARY: Rate Limiting Tools, Compliance APIs)
• chunk: 5.8 – End-to-End Deployment & CI/CD Pipelines (Methods: CI/CD, Blue-Green deploys, Rollbacks, Testing gates; Tools: PRIMARY: GitHub Actions, MLflow, SECONDARY: GitLab CI, DVC)
• chunk: 5.9 – Advanced UI & Application Integration (Methods: Mobile-first, API-first, Cross-platform, App integration; Tools: PRIMARY: React Native, REST APIs, SECONDARY: Flutter, Mobile Native Code)
• chunk: 5.10 – Summary

6. The AI Developer’s Journey (Conclusion)

• chunk: 6.0 – Intro
• chunk: 6.1 – Journey Recap & Lessons Learned (Methods: Reflection, AI maturity matrix; Tools: None)
• chunk: 6.2 – AI Career Paths, Team Building & Next Steps (Methods: Career planning, Role mapping; Tools: None)
• chunk: 6.3 – Summary