Codetown
Codetown ::: a software developer's community
Michael Levin's Likes
January 2012
November 2011
http://blogs.oracle.com/java/entry/new_java_champion_michael_levin Blog Mike Levin ::: Java Champion 2 Likes
October 2011
September 2011
Here's a recap of what happened at the JCertif 2011 conference in Brazzaville…
August 2011
The month of July was a global gathering for all Java Communities around the…
Blog
Java 7 Launch events in Africa (photos)!!
1 Like
June 2011
March 2011
Hi folks,
It's been a while since last time I post here. I just want to share a project that I have started recently and hopefully it will benefit some of you.
In…
Blog My latest personal project 1 LikeHappy 10th year, JCertif!
Notes
Welcome to Codetown!
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.
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InfoQ Reading List
NgRx 22: Resource Extensions and Dynamic Deep Signals for Angular
NgRx 22 adds experimental resource extensions that change Angular's resource behavior, so value() is retained during reloads and no longer throws on errors. It also introduces dynamic deep signals for union types, a SignalStoreFeatureType utility, and ESLint v10 support. Upgrading requires Angular 22 and TypeScript 6.0, and most breaking changes have automated migrations.
By Daniel CurtisStudy Finds AI-generated Code Fails to Boost Productivity Due to Downstream Bottlenecks
A recent Harvard study of 718 firms, using the Jellyfish analytics platform, finds that although AI coding assistants and agents increase code volume, this does not translate into a corresponding increase in completed work, partly because AI-generated code increases the workload in later stages of development, particularly code review.
By Sergio De SimonePresentation: Actors for Agents: Patterns for Production AI
Manju Rajashekhar explains how the actor model solves the complex runtime challenges of production AI agents. By treating agents as distributed systems, he discusses state ownership, message passing, write-through state, and supervision boundaries to manage failures, continuations, and mutable execution graphs, moving agentic workflows beyond fragile demos to resilient architecture.
By Manju RajashekharVercel Labs Open-Sources fx: A Zig Coding Agent Designed to Be Embedded
Vercel Labs has released fx, an experimental open-source coding agent written in Zig. It runs as a CLI, a script component, or an embedded library, including a WebAssembly build. Early feedback questioned its model-agnostic claim and a name conflict with an existing tool. Vercel says the project is pre-1.0 and changing quickly.
By Daniel CurtisHarbor Adds Docker Sandboxes to Run Reproducible AI Agent Evals in Isolated MicroVMs
Docker announced that Harbor, the open-source agent evaluation framework, now works with Docker Sandboxes. This change allows each evaluation task to run in its own microVM. So, instead of sharing a container, tasks are isolated for better performance
By Claudio Masolo
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