Brain Drip
Concept-driven learning and hands-on builds for AI — deep dives that build intuition, and blueprints that get you shipping.
Blueprints
Step-by-step builds — skip the theory, build something real with AI.
Build Your Own MCP Server
Build a personal bookmarks server that lets Claude save, search, and organize your links — Node.js, SQLite, and the official MCP SDK.
Build a RAG Pipeline from Scratch
Build a document Q&A system with Python, LlamaIndex, and Qdrant — ingest your docs and query them with natural language.
Ship an AI Agent with Claude
Build a research agent that searches the web, summarizes articles, and compiles reports — deployed as a REST API.
Build a Code Review Bot
Create a GitHub Action that reviews pull requests with Claude — catches bugs and posts inline comments automatically.
Create a Multi-Agent System
Build a content production pipeline with CrewAI — a researcher, writer, and editor that collaborate to produce articles.
Deploy Your Own Open-Source LLM
Run Llama 3.1 locally with Ollama, benchmark it, then deploy a production API with vLLM and Docker.
Courses
Pick a course to start learning. Each concept builds on the last.
LLM Concepts
From transformer architecture to cutting-edge research — each concept explained with intuition, math, and connections to the bigger picture.
AI Agent Concepts
Foundations of autonomous AI agents — reasoning, planning, memory, tool use, multi-agent systems, and safety.
AI Agent Evaluation
Benchmarks, automated evaluation methods, trajectory analysis, and production monitoring for AI agents.
Agentic Design Patterns
Architecture selection, tool design, error resilience, multi-agent coordination, and production patterns for agentic systems.
Computer Vision Concepts
Image fundamentals through CNNs, object detection, segmentation, generative models, vision transformers, and 3D vision.
LangGraph Agents
Build production AI agents with LangGraph — tools, memory, human-in-the-loop, streaming, multi-agent systems, and deployment.
LLM Evolution
The history and trajectory of large language models — from pre-transformer foundations through the 2025 frontier.
Machine Learning Foundations
Mathematical foundations, learning theory, supervised and unsupervised methods, neural networks, and production ML systems.
Building MCP Servers with Supabase
A hands-on guide to building Model Context Protocol servers with Supabase — from architecture to production deployment.
Natural Language Processing
Text preprocessing, representation, sequence models, NLP tasks, information extraction, and multilingual NLP.
Prompt Engineering
Core prompting techniques, reasoning elicitation, system prompts, structured output, context engineering, and production safety.
Reinforcement Learning
Foundations through deep RL, policy gradients, model-based methods, RL for language models, and landmark applications.
Building a Multi-Skill AI Agent
Hands-on guide to building an AI agent with multiple skills — architecture, tool design, orchestration, error handling, and a capstone research agent project.
Agent Harnesses & Orchestration
The harness layer above LLMs — Claude Agent SDK, Codex CLI, Cursor, ruflo, LangGraph, AutoGen, CrewAI, and OpenAI Agents SDK compared concept-by-concept. Topologies, consensus, federation, planning, and the orchestration plumbing that turns models into systems.