AI topics for builders
A structured path from AI and ML fundamentals to generative AI, production systems, security, careers, and tool selection. Each topic combines a mental model, implementation patterns, failure modes, and a practical next step.
Generative AI Fundamentals
Build a clear mental model of the models, tokens, and prompts behind modern generative AI.
8 articles →Retrieval-Augmented Generation (RAG)
Learn how retrieval connects language models to private, current, and domain-specific knowledge.
5 articles →AI Agents & Orchestration
Understand agents as model-driven workflows that plan, call tools, and complete multi-step tasks.
5 articles →Model Context Protocol (MCP)
Learn the concepts and security practices behind connecting models to tools and resources through MCP.
5 articles →Fine-Tuning Models
Learn when and how to adapt a model with examples, efficient training methods, and open models.
5 articles →Local AI & Open-Source Models
Run, optimize, serve, and evaluate open-source AI models on your own hardware, from quantization to production throughput.
5 articles →Multimodal AI
Explore models and pipelines that understand and generate combinations of text, images, audio, and more.
5 articles →LLMOps (MLOps for LLMs)
Operate LLM applications with reliable prompts, evaluations, cost controls, observability, and deployment practices.
5 articles →AI Security & Guardrails
Protect AI applications from malicious inputs, unsafe outputs, data leaks, and compliance failures.
5 articles →Python for AI Development
Build practical AI applications in Python with clean environments, APIs, data pipelines, and fast prototypes.
5 articles →Classical Machine Learning
Build the statistical foundations underneath every generative-AI system: how models learn from labeled data, how to measure them honestly, and where they go wrong.
5 articles →Neural Networks & Deep Learning
Bridge classical machine learning and modern generative AI by learning how neural networks are structured, trained, and specialized for text, images, and sequences.
5 articles →AI Careers & Job Prep
Understand the real job titles, skills, and hiring process behind AI roles, and build a plan to break in or move up.
5 articles →AI Tools & Comparisons
Compare popular AI assistants and coding tools on the dimensions that actually matter for choosing one, without chasing every new release.
4 articles →AI Coding Agents
Understand agentic coding tools like Claude Code, Cursor's agent mode, and Codex-style CLIs — how they plan, edit, run commands, and where they need a human in the loop.
4 articles →Context Engineering
Go beyond single-prompt writing to the discipline of deciding what information a model sees at each step — and what it doesn't.
4 articles →AI Evals & LLM-as-Judge
Build repeatable evaluation practices for AI features — from hand-labeled test sets to automated LLM-as-judge grading — so quality is measured, not assumed.
4 articles →Video Generation & World Models
Understand how AI video-generation and world-model systems work, what they're good at today, and where the technology is still unreliable.
3 articles →Small Language Models & On-Device AI
Learn why small, efficient language models running on-device or at the edge are a distinct design choice from large hosted models — and when that trade-off makes sense.
3 articles →AI Regulation & Compliance
Understand the regulatory landscape shaping AI products — the EU AI Act, US state laws, and sector rules — and what builders actually need to do about it.
3 articles →