Codetown ::: a software developer's community
Chicago Kotlin User Group x Android Listeners
Hosted at GrubHub, July 17
Coroutines are the new hot stuff, and right now they’re being added to lots of libraries. But what if you don’t want to use an alpha01 in production code? What can coroutines do on their own, right now? In this talk, we’ll discuss the power behind structured concurrency and how we can use it to make our entire stack lifecycle-aware. We’ll look at examples of how to turn any callback or long-running code into a coroutine, and we’ll go over when and how to use Channels to handle hot streams of data without leaking. Finally, and most importantly, we’ll see how we can use these tools to inform our application architecture, so that we can quickly write maintainable and testable features. Thanks to GrubHub for hosting!
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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.

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.
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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 RedlichMichael 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 Sadogursky
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?
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