Welcome to os890.ai — a new blog dedicated to the open-source side of agentic AI workflows. If you've followed os890.blogspot.com for Java and CDI content, this is its AI-focused companion: a space to document what happens when agentic AI meets open-source tools, libraries, and real-world development workflows.
The first project featured here sets the tone perfectly.
The Dynamic CDI Test Bean Addon is a CDI portable extension that automatically mocks unsatisfied injection points using Mockito — enabling clean CDI SE tests in multi-module projects where not all beans are on the classpath. A useful open-source tool in its own right. But what makes it the right starting point for this blog is how it was built:
The entire addon was created from scratch using an agentic AI workflow — extension logic, 64 tests against both Weld and OpenWebBeans, build configuration with Enforcer, Checkstyle, and Apache RAT, DeltaSpike integration, and all accompanying documentation including this post.
No hand-written code. No manual scaffolding. Just an agentic workflow driving open-source tooling from zero to a fully tested, properly licensed, publishable library.
This project was deliberately chosen for that reason: a CDI extension is a small but precise piece of software. There is no room for vague approximations — contracts must be correct, edge cases in dependency resolution matter, and the test suite runs against two different CDI implementations. It is the kind of project where implementation details are not cosmetic. That makes it a much more honest proving ground for agentic AI than building a typical app where the rough edges of generated code rarely surface.
That intersection — agentic AI and open-source software, tested against problems that actually require precision — is exactly what this blog is about. How far can these workflows go? What does it take to produce production-quality open-source artifacts with AI? Where do the rough edges still show? These are the questions os890.ai will keep exploring.
Try It or Build On It
The project site covers the full feature set, from zero-config auto-mocking to composable @TestBean meta-annotations. It also ships with a SKILL.md file — a structured description designed to make the addon easy to pick up and use inside your own agentic AI workflows.
What's Next
This project also served as a real-world validation run for jawelte — more on that soon.
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