Hans Reinl ▁

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.

AI Frontend Generator tools are experiencing a significant surge in popularity and adoption across the industry, with what appears to be multiple new tools being released and announced each week. With the recent surge in attention around Claude Code and similar AI-powered development tools, now is the perfect time to examine these platforms in depth and understand how they truly compare.

I have taken the time to thoroughly examine and test several of these tools, including Lovable, Replit, Vercel v0, base44, Cursor, Github Copilot, and Claude Code, using a structured approach with objective and subjective metrics to evaluate their performance, code quality, export capabilities, cost, tech stack, and developer experience.

This article explores the challenges and opportunities of leading remote engineering teams. It examines key challenges such as communication, performance management, and feedback, while also highlighting the benefits of a global talent pool, improved work-life balance, and increased innovation. The article provides actionable strategies for building high-performing remote teams.

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.