Codetown ::: a software developer's community
sophie hannah has not received any gifts yet
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
Check out the Codetown Jobs group.
Google has introduced LLM-Evalkit, an open-source framework built on Vertex AI SDKs, designed to make prompt engineering for large language models less chaotic and more measurable. The lightweight tool aims to replace scattered documents and guess-based iteration with a unified, data-driven workflow.
By Robert KrzaczyńskiIntroducing JUnit 6.0.0: a transformative update that unifies versions, elevates minimum requirements to Java 17, and introduces streamlined support for Kotlin suspend tests. Enjoy enhanced testing performance with the new CancellationToken API, built-in JFR listeners, and upgraded CSV parsing using FastCSV. Embrace the future of testing—migrate today!
By A N M Bazlur RahmanSally O'Malley explains the unique observability challenges of LLMs and provides a reproducible, open-source stack for monitoring AI workloads. She demonstrates deploying Prometheus, Grafana, OpenTelemetry, and Tempo with vLLM and Llama Stack on Kubernetes. Learn to monitor critical cost, performance, and quality signals for business-critical AI applications.
By Sally O'MalleySoftware engineering governance helps teams make decisions, Sarah Wells said at Goto Copenhagen. She argued it should support value delivery, not hinder it. Poor governance slows progress and can increase costs. A technical strategy with a radar can help teams to make better decisions, and aligning with DORA capabilities can boost their performance.
By Ben LindersAI code generation tools promise faster development but often create quality issues, integration problems, and delivery delays. A structured Plan-Do-Check-Act cycle can maintain code quality while leveraging AI capabilities. Through working agreements, structured prompts, and continuous retrospection, it asserts accountability over code while guiding AI to produce tested, maintainable software.
By Ken Judy
© 2025 Created by Michael Levin.
Powered by
Comment Wall
You need to be a member of Codetown to add comments!
Join Codetown