Artificial intelligence isn’t just changing how we write code—it’s transforming how we think about creativity in development. In this post, I revisit the playful spirit of early programming through a series of AI-assisted experiments using ChatGPT, GitHub Copilot, and JavaScript Canvas on CodePen. Along the way, I uncover practical lessons for developers on using AI to accelerate learning, inspire exploration, and rekindle the joy of creative coding…
It’s common to face challenges around long-running workflows, state management, and resiliency when you’re building cloud-native applications. Traditional approaches like background services or message queues might work sometimes, but they often require a lot of “glue code” and custom retry logic. This entails not only more work up-front for the developer, but also more maintenance in the long run.
That’s where Azure Durable Functions come in.
In this post, we’ll explore how to use GitHub Copilot to generate Java code and unit tests with minimal manual input. Using a real-world example—a mortgage calculator service—you’ll see how Copilot can help write both the core logic and the corresponding unit tests. Whether you’re new to AI-assisted development or curious about Copilot’s capabilities in a Java environment, this tutorial will give you practical insight into how it works—and where human oversight still matters.
Tired of forcing a legacy CMS into your sleek React stack?
Payload flips the script with a dev-first approach that feels native to modern JavaScript environments. While traditional platforms prioritize marketers, Payload is built for engineers—especially those working in full-stack TypeScript apps with frameworks like Next.js and React….
This post walks through a hands-on experiment in agentic development using an AI-powered digital twin embedded in the IDE. See how a single, well-structured prompt enabled the agent to implement a real user story, generate behavioral tests, and prepare Git commit documentation—with minimal developer input. Includes real-world code samples, implementation insights, and a candid look at what worked, what didn’t, and where human oversight is still essential.