Hans Reinl ▁

I map my AI-in-production workflow to the software development lifecycle, from discovery to operations, with clear handoffs between AI agents and human owners. The core idea: agentic engineering is not a coding trick but a delivery system for reliable software.

I want to share my workflow for moving from vibe coding to agentic engineering. I will walk you through the process of defining a feature, exploring the UI in v0, integrating the code in Cursor, reviewing and refactoring the code, and testing, merging, and shipping the feature.

With the release of Claude Opus 4.5 and the hype surrounding "engineering-grade" models, I moved beyond frontend generation to test their capabilities as full-stack engineers. I took the three current heavyweights—GPT-5.1-Codex-Max, Gemini 3 Pro, and Claude Opus 4.5—and ran them through a rigorous MVP development cycle to build 'Speakit', a text-to-speech application, to see if benchmark numbers translate to shipping products.

For engineering teams, measuring the right things is crucial for success. This post explores how to build an effective engineering metric program that aligns with product goals and drives continuous improvement. It covers topics such as defining relevant KPIs for engineering, turning data into actionable insights, and fostering collaboration with other departments. Learn how to move beyond simply counting errors and focus on metrics that truly impact user experience and business outcomes.

Generative AI (GenAI) is revolutionizing front-end development, empowering developers to streamline workflows, enhance productivity, and unleash their creativity. This article explores the transformative potential of GenAI, delving into practical examples using ChatGPT, Bard, and v0. It highlights their capabilities in generating UI components, crafting user-friendly interfaces, and providing code generation assistance. While AI tools cannot replace human creativity, they serve as invaluable collaborators, fostering a symbiotic relationship between human ingenuity and machine intelligence. As GenAI continues to evolve, developers can anticipate even more sophisticated tools that further empower front-end development.