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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
Swiggy Improves Search Autocomplete Using Real Time Machine Learning Ranking
Swiggy detailed real-time machine-learning ranking system for autocomplete built on OpenSearch. The architecture separates candidate generation and ranking, uses feature stores for real time signals, and applies learning to rank models for improved relevance. It replaces heuristic ranking while maintaining strict latency constraints and enabling continuous model updates from user behavior signals.
By Leela KumiliAnthropic's Code With Claude Announces Managed Agents, Proactive Workflows, Capability Curve
Anthropic hosted "Code with Claude 2026" in San Francisco, featuring livestream sessions focused on Claude Code, the Claude API platform, and other projects. Key topics included developer experience, autonomy features, model step-changes, and the impact of AI on product architecture. Discussions included insights from GitHub, Vercel, and AI-native startups on engineering strategies and challenges.
By Andrew HoblitzellJava News Roundup: OpenJDK JEPs, Azul Payara, WildFly, LangChain4j, OpenXava, Google ADK
This week's Java roundup for May 11th, 2026, features news highlighting: three OpenJDK JEPs targeted for JDK 27; introducting Azul Payara Community and the WildFly wado CLI tool; point releases of LangChain4j and Google ADK; and maintenance releases of Micronaut and OpenXava.
By Michael RedlichPodcast: Context is the Key to the Agentic Architecture Revolution: A Conversation with Baruch Sadogursky
Michael Stiefel spoke to Baruch Sadogursky about software architecture in the age of agentic AI. LLM can function, albeit stochastically, as reasoning machines capable of interpreting human ambiguity. With the appropriate rigorous context artifacts to control the LLM’s reasoning, software specifications can become the source of truth, while the code becomes a disposable intermediate language.
By Baruch SadogurskyArticle: Building a Secure MCP Server on AWS for a Million-Company B2B Platform
We wanted to expose a B2B intelligence platform built on more than one million company profiles to an LLM client through an MCP server so a user can ask “find SaaS companies in Germany with 50-200 employees” and receive results through the LLM client. The engineering problem was: How do you make that workflow useful without creating an unsafe bridge between an LLM and production data?
By Shadi Elyafi
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