Food for thought.
Reflections on some of our cases, research on cutting-edge tech & experienced takes on design, development and business.
Reflections on some of our cases, research on cutting-edge tech & experienced takes on design, development and business.

Quality Assurance (QA) has always been at the heart of reliable software delivery. It ensures stability, usability, and confidence before every release. But as applications grow more complex and development cycles shorten, manual testing alone can no longer keep pace. Artificial Intelligence is now reshaping how QA operates. By integrating AI driven validation, pattern recognition, and predictive analytics, teams can detect issues earlier, automate more efficiently, and release software faster without compromising quality.

AI is transforming software maintenance by automating code migrations and dependency updates. Instead of spending weeks manually refactoring and fixing compatibility issues, teams can now use AI tools to analyze, update, and optimize large codebases automatically, reducing technical debt and keeping systems continuously up to date.

For years, Figma shaped how teams sketch, prototype, and ship interfaces. With Weave, the company pushes beyond static mockups into an intelligent canvas that blends design, motion, and media generation inside the browser. The result is a creative environment where prompts, nodes, and real-time collaboration help teams iterate faster while staying consistent with brand systems.

Most browsers still look and behave the same as they did twenty years ago. Tabs, bookmarks, and manual searches define how we move through the web. But that model is being reimagined by artificial intelligence. Dia, a new AI-powered browser from The Browser Company (creators of Arc), introduces a completely new way to browse and work online. Instead of just displaying web pages, Dia acts as an intelligent assistant that understands context, interprets commands, and automates actions across the web.

Code reviews are essential for maintaining software quality, consistency, and security. They catch errors early, enforce standards, and facilitate learning across teams. Yet, as development velocity increases, traditional review processes often become a bottleneck. Pull requests pile up, reviews delay merges, and developers lose momentum waiting for feedback. Artificial Intelligence is changing that. Modern AI code review tools bring speed, precision, and scalability to one of the most time-consuming stages of software delivery — without sacrificing quality or human oversight.

The modern AI stack is evolving beyond traditional data pipelines and web backends. As language models become central to application logic, a new layer of infrastructure has emerged — one built around LLM APIs, vector databases, and context windows. This emerging stack powers intelligent, context-aware systems capable of reasoning, retrieving, and generating information dynamically. In this article, we’ll explore how these technologies fit together, why they matter for developers, and how they are shaping the next generation of AI-driven products.