Vibe coding is a good starting point, but it is not where serious AI-assisted development ends. The next step is agentic engineering: using AI coding agents inside a controlled engineering workflow, with context, tests, review and clear boundaries. Vibe coding often focuses on the generated output: Ask for feature -> get code -> run it -> ask for fixes Agentic engineering focuses on the system ar
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
This post was created with AI assistance and reviewed for accuracy before publishing. Cursor can use project rules and documentation to steer behavior. Exact file names and mechanisms evolve; check Cursor documentation for the current layout (for example rules in .cursor or legacy .cursorrules patterns). Short, enforceable bullets beat long essays: stack versions, test commands, “no new dependenci
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
Vibe coding is one of those terms that sounds unserious until you notice how many people are actually doing it. The basic idea is simple: describe what you want, let an AI coding tool generate the implementation, run it, adjust the prompt, and keep going. It can feel magical. It can also go wrong very quickly. Vibe coding works best when the problem is visible and forgiving: small prototypes inter
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