LangGraph in One Post

LangGraph is the stateful, graph-based framework that LangChain built when it realized real agent workflows need loops, not lines.

Run Your Own Model or Use the API? A Practical Guide

The honest cost breakdown for self-hosting LLMs vs. using Claude or another API — privacy, latency, capability, and the math that actually drives the decision.

Agent vs. No-Agent: A Production Decision Guide

The real cost of building agents in production — failure modes, debugging nightmares, and the five questions that tell you whether you actually need one.

How to Architect an AI ETL Pipeline

A practical guide to designing AI-powered ETL pipelines — where LLMs actually belong in extract, transform, and load, and where they just add cost.

When to Build an Agent (And When You're Overcomplicating It)

A practical decision framework for choosing between raw API calls, orchestration frameworks like LangChain, and full agentic systems — with real examples from production.

Databricks in One Post

Databricks was founded by the team that created Apache Spark. The lakehouse architecture they invented is now how most enterprise data and AI work gets done.

TensorFlow in One Post

Google Brain needed a framework to run AI at search-engine scale. What they open-sourced in 2015 became the reason deep learning left research labs and entered every industry.

FastAPI in One Post

Sebastián Ramírez was a freelance developer in Colombia who needed faster, cleaner API code. What he built in 2018 became the backbone of AI inference infrastructure worldwide.

Hugging Face in One Post

Three French founders pivoted from a Gen-Z chatbot to hosting AI models. The Transformers library they built is now where every major model in the world lives.

LangChain in One Post

Harrison Chase released LangChain six weeks after ChatGPT. The core insight — that LLM calls need to be composable — reshaped how everyone builds AI applications.

Matplotlib in One Post

John Hunter was analyzing brain scans on a research budget. What he built to replace a $1,000 license became the bedrock of Python data visualization.

Pandas in One Post

Wes McKinney was frustrated by financial data. What he built in 2008 became the single most-used tool in data science.

NumPy in One Post

The origin story of NumPy — how one developer ended a civil war in the Python community and built the array library that became the language of AI.

Scikit-Learn in One Post

The origin story of the library that taught a generation to build machine learning models — and why it still matters in the age of ChatGPT.

Build a RAG Pipeline From Scratch in Python

A complete, copy-pasteable RAG pipeline using ChromaDB, sentence-transformers, and the Claude API. No LangChain. Every step visible.

What Is RAG and Why Does Every AI App Use It?

RAG is the technique behind every AI that actually knows your data. Here's what it is, why it exists, and why it matters — no PhD required.

I Accidentally Built My Own Publishing Workflow

How trying to simplify my blog turned into a full AI-powered publishing tool I actually use every day.

Linear Regression Example

Predicting Software Reselling Profits

Tweet War

Who will win the election according to Tweeter

Estimating COVID-19s transmission rates in Georgia

This is the most current transmisison rates for Georgia

Split Variables from one column into several columns in R

Cool Tool for R

Basic Data Visualiztion in Python

https://matplotlib.org/

Start Here

Install Python

Pandas in One Post

Intro into Pandas

Python in One Post

Basic python

How this site was built

How to build a site with Github and Jekyll

R in One Post

Basic R

Cool Data Visualizations in Python (code Included)

Numpy in One Post

Python Libraries