GraphQL was good at a time, then it simmered off. Is GraphQL about to make a comeback because of AI? Will GraphQL be able to serve better for AI Agents?
In this article, I will be introducing a pipeline designed to identify sensitive data columns before masking steps and improve the efficiency of the data masking process.
We eliminated per-record Python-side Protobuf parsing and JVM-to-Python crossings by letting Flink's native Protobuf format decode records directly into typed columns.
By combining Quarkus Flow, LangChain4j, MCP tools, and AGENTS.md, developers can construct deterministic, tool-augmented, and enterprise-governed AI agent loops.
RAG cuts chatbot hallucinations by grounding answers in retrieved source data, not model memory. Retrieval quality and evaluation matter more than model size.
RFC 10008's new QUERY method is safe and cacheable like GET but carries content like POST. This article explains the spec and runs it on Quarkus today.
I built six AI visibility tools without a traditional backend, using one Cloudflare Worker to solve CORS while all scoring logic runs client-side in the browser.
A direct CNN benchmark on CIFAR-10 shows TensorFlow and PyTorch achieve identical accuracy (~68%). Choose TensorFlow for production and PyTorch for flexibility.
AI agents don't break your API rules; they expose the ones you never enforced. This article covers five gateway-level controls that bring autonomous agents under control.
There is no point in shipping another Java Version Manager unless it is best in class, so I mined the test suites and bug trackers of SDKMAN, jenv, mise, volta, and asdf.