AI

3 hours ago 1

AI Programming

AI Coding Assistants: How to Use Them Without Destroying Code Quality

An opinionated guide to using AI coding assistants without wrecking your codebase where they shine, where they hurt, review discipline, quality, security pitfalls, and team norms that prevent AI debt.

3 days ago 26

AI Programming

RAG Is Not Just Search: Chunking, Ranking, Reranking, and Hallucination Control

Go beyond naive vector search chunking strategies, hybrid keyword+semantic ranking with RRF, cross-encoder reranking, context assembly, and layered hallucination control, with each change helps.

6 days ago 52

AI Databases Programming

Building a Private RAG System: Architecture, Embeddings, Vector DBs, and Evaluation

A full architecture walkthrough for a private, self-hosted RAG system ingestion, chunking, embeddings, vector databases and the evaluation loop that makes it trustworthy.

1 week ago 54

Python AI

A Practical Introduction to LLMs and RAG in Python, and Where to Go Next

The finale: LLMs explained with the concepts you already own, tokens and prompts, your first Claude API call from Python, a toy RAG engine in the browser, and the full map into the production LLM and MCP series.

1 week ago 29

Python AI

Deep Learning Basics in Python: Neural Networks with TensorFlow and Keras

Lesson 15: deep learning without hand-waving: what neurons compute, loss and gradient descent, backpropagation built by hand in NumPy in the browser, and a complete Keras Fashion MNIST classifier with dropout and transfer learning.

1 week ago 29

Python AI

Machine Learning Foundations in Python: First Models with scikit-learn

Lesson 14: train your first real machine learning models with scikit-learn: features and labels, train/test splits, fit/predict/score, a decision tree you can read, k-nearest-neighbors, and overfitting, live in the browser.

1 week ago 75

AI Linux Programming

Local AI in 2026: Ollama, vLLM, Docker Model Runner, and When to Use Each

An honest comparison of local AI tooling in 2026 — Ollama for laptops, vLLM for high-throughput GPU serving, and Docker Model Runner for container-native models, with a decision framework and VRAM sizing advice.

1 week ago 37

AI Python

Your First MCP Server with FastMCP and uv

Stand up a real MCP server with the official Python SDK: uv setup, FastMCP tools, how type hints become schemas, the Inspector loop, and connecting to Claude Code and Claude Desktop.

1 week ago 34

AI Python

Shipping Your MCP Server: Docker, Deployment, and the MCP Registry

The last mile: typed settings, a uv-based multi-stage Dockerfile, proxy rules that keep SSE alive, publishing to the MCP registry, semantic versioning, and connecting every client.

1 week ago 26

AI Python

Testing and Debugging MCP Servers: Inspector, pytest, and In-Memory Clients

Make your MCP server provably correct: the Inspector as a debugging instrument, pytest suites with in-memory client sessions, schema snapshot tests, and the debugging playbook.