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Instant Runoff Voting - Contest #2
Instant Runoff Voting (IRV) is a fascinating way to run an election. The basic idea is that voters rank the candidates and the votes for the least popular candidate are automatically moved to the remaining candidates until one is selected winner.
Ready for the challenge? Read the details here, in Contest Town...
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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
Advance Your Socio-Technical Architecture Skills with InfoQ’s New Online Cohorts
Enhance your architectural leadership with InfoQ’s new online cohorts starting April 15, May 7, and June 10, 2026. Led by Luca Mezzalira, this 5-week program focuses on socio-technical skills like ADRs, platform engineering, and AI trade-offs. Senior practitioners can apply frameworks to live projects, earn ICSAET certification, and contribute to the InfoQ community.
By Ian RobinsMaking Retrospectives Effective with Small Concrete Actions and Rotating Facilitators
Teams can run regular retrospectives that focus on 1–2 concrete weekly actions to avoid complaint circles, Natan Žabkar Nordberg mentioned at QCon London. You can rotate facilitators to build ownership, with each one bringing their own unique perspective. He suggested framing bigger changes as 4–6 week experiments, then vote to keep, tweak, or revert, ensuring learning and continuous improvement.
By Ben LindersAWS Launches Strands Labs for Experimental AI Agent Projects
Amazon Web Services has introduced Strands Labs, a new GitHub organization created to host experimental projects related to agent-based AI development.
By Daniel DominguezClaude Opus 4.6 Introduces Adaptive Reasoning and Context Compaction for Long-Running Agents
Anthropic’s Claude Opus 4.6 introduces "Adaptive Thinking" and a "Compaction API" to solve context rot in long-running agents. The model supports a 1M token context window with 76% multi-needle retrieval accuracy. While leading benchmarks in agentic coding, independent tests show a 49% detection rate for binary backdoors, highlighting the gap between SOTA claims and production security.
By Steef-Jan WiggersRunning Ray at Scale on AKS
The Azure Kubernetes Service (AKS) team at Microsoft has shared guidance for running Anyscale's managed Ray service at scale. They focus on three key issues: GPU capacity limits, scattered ML storage, and problems with credential expiry.
By Claudio Masolo
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