In my previous article about treating architecture documentation as a first-class asset, I had a great discussion in the comments about enforcing architectural rules. I promised to share materials from my recent Google Developer Groups workshop. The workshop is now finished! Here is the story of how I built an AI Quality Gate, how it helped me solve the internal "CEO, CTO, CFO, CISO" conflict, and
Most TypeScript teams shopping for an agent framework don't need one. A single generateObject call covers classification, extraction, summarization, tagging — the 80% case for production LLM work in TS right now. But once the model starts deciding what to do next, surviving deploys, or coordinating with other agents, you start shopping. And the moment you do, you discover the TS agent ecosystem is
All frameworks are eventually replaced. React is probably the first that won’t be. It's not the best language out there, it's not the language developers love the most, it's the language the robots just won't quit. Request ChatGPT to develop a todo app for you. You'll receive React. Request Copilot to generate the basic structure of a component. React. Request Claude to design a prototype for a da
In my previous article, I documented how I installed Terraform on macOS using Homebrew and fixed a Zsh autocomplete issue. In this article, I am going to be using terraform to provision, update, and destroy a simple set of infrastructure using the sample configuration provided by hashicorp The goal is to understand the basic Terraform workflow: Write configuration Authenticate to Google Cloud Ini
On April 30th I got an email from Google about something called GEAR, their new program for building AI agents using ADK, the Agent Development Kit. I signed up, watched the intro video, and had a strange feeling of recognition. The pattern was familiar. Define tools. Write descriptions. Connect an AI model to those tools. Let the model decide which tool to call based on what the user asks. I buil
VotePath -- an AI-powered multilingual voting guide for first-time voters. The Problem: Why Don't People Vote? What is VotePath? 🤖 Gemini-Powered AI Assistant: A conversational AI built with the Google Gemini API that answers specific election queries in real-time. 🛠️ The Tech Stack Building the UI components and wiring up the Gemini SDK went smoothly using an intent-driven development approach.
For years, the dream of a truly autonomous, always-on AI assistant has felt just out of reach — a concept relegated to-fi or limited by fragile, stateless nature of most chat interfaces. We’ve grown accustomed to assistants that forget us the moment we close the browser tab. But what if we could change the fundamental architecture? What if we could build an AI agent that doesn't just converse, but
From Data Cleaning to Ambient Human-AI Co-Creation — A Research, Development, and MVP Architecture Study Author: PeacebinfLow | Organization: SAGEWORKS AI (SageX AI) | Location: Maun, Botswana | Version: 1.0, 2026 | Repository: github.com/PeacebinfLow/ecosynapse The dominant paradigm in applied artificial intelligence frames the agent as the fundamental unit of intelligent computation: a bounded s