Caleb Royer didn’t hire a data team at Techtree Partners. He became one.
How a solo developer at TechTree built a full-scale data warehouse using Mage, AI, and DBT—no team required. See Caleb’s journey from chaos to control.
Build an AI-Powered MCP pipeline with Mage Pro — Part II: Building the intelligence layer, connect your documents to Claude via MCP
Learn how to seamlessly integrate Anthropic’s Claude API with MCP and Mage Pro to automate workflows and unlock advanced prompt engineering. This step-by-step guide covers setup, code examples, and best practices for building smarter, AI-powered tools—perfect for developers and teams looking to boost productivity and stay ahead in the world of AI automation.
Build an AI-Powered MCP pipeline with Mage Pro - Part 1: Extract, Transform, and Structure PDF Data for AI Integration
This article describes how to build an AI system to answer questions about the Great Attractor using Model Context Protocol (MCP). In part 1 you’ll learn how to use Mage Pro to create a data pipeline that connects knowledge sources to AI systems, including fetching PDF data, cleaning the text, and preparing it for us with Antrhopic’s Claude. This approach allows for more accurate, source-specific AI responses rather than relying solely on general training data.
Mage Platform: Build and Deploy Data Pipelines with Python and SQL
Discover how the Mage platform simplifies data engineering workflows. Learn to build, deploy, and manage data pipelines with this powerful open-source tool.
The AI Data Tools That (Sort of) Saved My Sanity: Real Talk About Engineering Automation
Let me just say, data engineering has been a wild ride. These AI tools have been a game-changer—don’t get me wrong, they still have their moments—but they’ve honestly cut my workload in half. If you’re tired of burning the midnight oil debugging or dealing with endless pipelines, this guide might actually help. No fluff, just the tools that actually work.