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Happy 10th year, JCertif!
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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
Presentation: Panel: Modern Data Architectures
The panelists emphasize that data engineering is no longer just about "click-and-drag" UI tools; it is software engineering applied to data.
By Fabiane Nardon, Matthias Niehoff, Adi Polak, Sarah UsherHow Dropbox Built a Scalable Context Engine for Enterprise Knowledge Search
Dropbox engineers have detailed how the company built the context engine behind Dropbox Dash, revealing a shift toward index-based retrieval, knowledge graph-derived context, and continuous evaluation to support enterprise AI at scale
By Matt FosterUber and OpenAI Retool Rate Limiting Systems
Uber and OpenAI are replacing static rate limits with adaptive, infrastructure-level platforms. Uber’s Global Rate Limiter utilizes probabilistic shedding to manage 80M RPS, while OpenAI’s Access Engine implements a credit waterfall to prevent user interruptions. Both architectures utilize distributed enforcement and soft controls to maintain system stability and service continuity at scale.
By Patrick FarryMoonshot AI Releases Open-Weight Kimi K2.5 Model with Vision and Agent Swarm Capabilities
Moonshot AI released Kimi K2.5, their latest open-weight multimodal LLM. K2.5 excels at coding tasks, with benchmark scores comparable to frontier models such as GPT-5 and Gemini. It also features an agent swarm mode, which can direct up to 100 sub-agents for attacking problems with parallel workflow.
By Anthony AlfordLeapwork Research Shows Why AI in Testing Still Depends on Reliability, Not Just Innovation
Leapwork recently released new research showing that while confidence in AI-driven software testing is growing rapidly, accuracy, stability, and ongoing manual effort remain decisive factors in how far teams are willing to trust automation.
By Craig Risi
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