🎓 Engineer Knowledge

A personal project for organizing, consolidating, and strengthening the essential knowledge needed to grow as an engineer.

🌐 Live site: flynn3103.github.io/engineer-knowledge

Purpose

The knowledge required for modern engineering work is scattered across countless blogs, courses, and documentation. This project brings it all together in one place, in a structured way, organized around six domains:

• Craftsmanship — engineering thinking (computational, systems, critical, first-principles, probabilistic, creative, debug-thinking, scientific reasoning), code review, object-oriented design, documentation, legacy code, professionalism, and on-production practice (estimation, testing, performance, release, SRE & reliability, security, privacy, cost)
• Programming Languages — Go, Python, plus shared language/runtime internals
• Infrastructure — containers, Kubernetes, deployment strategies, CI/CD, IaC, GitOps, multi-region, disaster recovery, autoscaling, VPC, virtual machines, and network protocols
• Data Engineering — service communication and APIs, databases, distributed systems, event streaming, orchestration, storage, and concurrent processing
• AI Engineering — LLM fundamentals (including model selection/fine-tuning), RAG, agent architecture, evaluation, and MLOps
• Blog — coming soon

Project Structure

📁 engineer-knowledge
├── 📂 craftsmanship/                     # Thinking skills + practical disciplines + on-production practice
│   ├── engineering-thinking/             # 11 sections: computational → object thinking (incl. debug-thinking)
│   ├── code-review/                      # Review practices across levels
│   ├── documentation/                    # Decisions, interfaces, operations
│   ├── legacy-code/                      # Working with unfamiliar code safely
│   ├── object-oriented-design/           # Behavior, responsibility, coupling
│   ├── professionalism/                  # Reliability, growth, integrity
│   └── on-production/                    # Estimation, testing, performance, release, SRE & reliability, security, privacy, cost
├── 📂 programming-languages/
│   ├── golang/                           # Go roadmap — concurrency through production debugging
│   ├── python/                           # Python roadmap
│   └── language-internals/               # Runtime, memory, types, compilers, and interoperability
├── 📂 infrastructure/                    # Containers, orchestration, deployment, CI/CD, IaC, GitOps, VPC, VMs, and protocols
├── 📂 data-engineering/                  # Communication/APIs, databases, distributed systems, streaming, scheduling, storage, and concurrency
├── 📂 ai-engineering/                    # LLM fundamentals (incl. model selection/fine-tuning), RAG, agents, evaluation, MLOps
└── 📂 blog/                              # Coming soon

How to use

Each topic follows a consistent multi-level file structure:

File	Purpose
README.md	Topic overview and navigation
junior.md	Foundations a junior developer needs
middle.md	Mid-level depth and patterns
senior.md	Senior-level mastery
professional.md	Expert-level production knowledge

Every level guide ends with unanswered comprehension questions for active recall.

Who is this for?

This project was primarily created for personal use, but anyone looking to grow as an engineer is welcome to use it.

License

MIT — flynn3103, 2026