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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
Cloudflare Makes Basin Serverless Analytics Generally Available
Cloudflare has announced the general availability of Basin, a serverless analytics platform built on Apache Iceberg and R2 Object Storage. The managed service supports open data formats and integrates with tools such as DuckDB, Snowflake, and Apache Spark, with no data egress fees.
By Renato LosioGoogle Finds that Technical Debt Can Derail Coding Agents Through "Agent Distraction"
In a recent article, Google senior staff software engineer Sam Saccone and senior staff data scientist Madhuri Garikapati highlighted the cost of agent distraction, where AI coding agents get derailed by stale technical debt, such as old TODO comments, obsolete bug references, and outdated specs, leading them to embark on unrequested "side-quests".
By Sergio De SimonePinterest and Intel Take Open-Source Profiling to Internet Scale
Pinterest has partnered with Intel to extend gProfiler, an open-source continuous profiler that provides production performance visibility across an internet-scale fleet of infrastructure.
By Craig RisiPresentation: Batch Intelligence at Scale: Cost-Efficient Multi-Agent LLM Workflows with Built-In Resilience
Aditya Mulik explains how Walmart Global Tech deployed multi-agent LLM workflows across 4,700 stores for nightly batch inventory forecasting. He discusses tackling production hurdles - schema violations, cross-department data mismatches, and network drops - via MCP grounding and loop agents, while slashing cloud inference costs from $100k+ to $10k per month shifting from PTUs to pay-as-you-go.
By Aditya MulikArticle: LLM Reliability Layers Under Test: Accuracy, Yield, and the Limits of Verification
Verification layers sort outputs by trust rather than fixing errors. In a benchmark of six reliability layers, voting and self-correction failed to recover accuracy - they only withheld doubtful records. Production systems gain more reliability by replacing generation with deterministic lookups, tracking yield over raw accuracy, and resolving extraction bottlenecks before stacking checks.
By Pushpdeep Mishra, Wejdan Bagais
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