tutorial New Post November 7, 2026 Databricks Step by Step: Serve a Model as an API A step-by-step guide to deploying a Unity Catalog model to a Databricks Model Serving endpoint, calling it over REST and Python, updating versions safely, and monitoring it. #databricks #model-serving #mlops #api #python #tutorial
tutorial New Post November 6, 2026 Databricks Step by Step: Train and Register a Model A step-by-step guide to training a machine learning model on Databricks, tracking experiments with MLflow, and registering versioned models in Unity Catalog with aliases. #databricks #mlflow #machine-learning #unity-catalog #python #tutorial
tutorial New Post November 5, 2026 Databricks Step by Step: Build a Data Pipeline A step-by-step guide to building a bronze, silver, and gold data pipeline on Databricks with Auto Loader, Lakeflow pipelines, data quality expectations, and a scheduled job. #databricks #data-engineering #lakeflow #delta-lake #python #tutorial
ai-engineering August 12, 2026 The Vibe-Coding Trap: What Building an AI Project Manager Taught Me the Hard Way A first-person account of building an AI project manager that writes and reviews its own code, and the recurring gap between "the AI says it's fixed" and "it's actually fixed" that nearly sank it. #vibe-coding #ai-agents #lessons-learned #software-engineering
ai-engineering July 14, 2026 Vector Databases in One Post Vector databases exist because traditional databases can't answer the question 'what is similar to this?' Here's the problem they solved, how they work, and when to use them. #vector-databases #rag #embeddings #pinecone #chroma #ai-engineering
ai-engineering July 13, 2026 AWS Bedrock, Azure AI Foundry, and Vertex AI in One Post AWS Bedrock, Azure AI Foundry, and Google Vertex AI are the three cloud platforms fighting for the enterprise AI market. Here's what they are, how they got here, and how to choose. #aws #azure #gcp #bedrock #vertex-ai #cloud #llm
ai-engineering July 12, 2026 MCP and A2A in One Post Model Context Protocol and Agent-to-Agent are the two protocols trying to solve AI interoperability — one for tools, one for agents. Here's what they are and why they exist. #mcp #a2a #agents #anthropic #protocols #interoperability
ai-engineering July 11, 2026 Make, n8n, and Zapier in One Post Zapier, Make, and n8n each solved the problem of connecting apps without code. Now all three are racing to become the backbone of AI agent infrastructure. #zapier #make #n8n #automation #agents #no-code
ai-engineering July 10, 2026 LangGraph in One Post LangGraph is the stateful, graph-based framework that LangChain built when it realized real agent workflows need loops, not lines. #langgraph #langchain #agents #llm #python
ai-engineering July 9, 2026 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. #llm #infrastructure #self-hosted #claude #architecture
ai-engineering July 8, 2026 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. #agents #llm #architecture #production
ai-engineering July 7, 2026 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. #etl #data-engineering #llm #architecture #pipeline
ai-engineering July 6, 2026 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. #agents #langchain #llm #architecture
tutorial June 23, 2026 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. #python #databricks #spark #data-engineering #ai #tutorial
tutorial June 22, 2026 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. #python #tensorflow #deep-learning #neural-networks #ai #tutorial
tutorial June 21, 2026 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. #python #fastapi #api #backend #ai #tutorial
tutorial June 20, 2026 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. #python #huggingface #transformers #llm #ai #tutorial
tutorial June 19, 2026 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. #python #langchain #llm #ai #tutorial #agentic
tutorial June 18, 2026 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. #python #matplotlib #data-visualization #tutorial #ai
tutorial June 17, 2026 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. #python #pandas #data-engineering #tutorial #ai
tutorial June 16, 2026 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. #python #numpy #ai #tutorial
tutorial June 15, 2026 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. #python #machine-learning #scikit-learn #ai #tutorial
blog June 3, 2026 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. #python #ai #rag #tutorial #series
blog May 27, 2026 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. #ai #rag #llm #series
blog May 25, 2026 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. #python #ai #automation #workflow
blog August 17, 2020 Estimating COVID-19s transmission rates in Georgia This is the most current transmisison rates for Georgia #Covid-19 #python
