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Happy 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
Study 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 MasoloArticle: AI Changes the Data Interface, Not the Query Engine
This article presents a disaster-recovery analytics workflow in which an AI agent generates constrained SQL or Python, DuckDB computes reproducible facts from Parquet, and the agent interprets the results. It explains the determinism split, replayable analysis, and four signals for deciding when an embedded engine is sufficient or a managed lakehouse is justified.
By Peihao Yuan
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Good day,
I picked interest on you after going through your short profile and demand it necessary to write you
immediately. I have something very vital to disclose to you, but I found it difficult to express myself
here, since it's a public site.Could you please get back to me on (Jonathanbewes9@gmail.com) for the full
details.
Have a nice day.
Jonathan
Hi Hendy! Welcome to Codetown!