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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: Slack's AI-Powered, Hybrid Approach for Large-Scale Migration from Enzyme to React Testing Library

Sergii Gorbachov shares how his team at Slack saved thousands of hours by using an innovative hybrid approach combining AST and LLM to tackle a complex migration from Enzyme to React Testing Library. He explains the challenges of this widespread problem, detailing how they built a pipeline that modeled human problem-solving to successfully automate the migration.

By Sergii Gorbachov

LinkedIn Re-Architects Edge-Building System to Support Diverse Inference Workflows

LinkedIn has detailed its re-architected edge-building system, an evolution designed to support diverse inference workflows for delivering fresher and more personalized recommendations to members worldwide. The new architecture addresses growing demands for real-time scalability, cost efficiency, and flexibility across its global platform.

By Leela Kumili

DeepSeek Releases v3.1 Model with Hybrid Reasoning Architecture

DeepSeek has released version V3.1 of its large language model, introducing a hybrid architecture that combines thinking and non-thinking modes in a single system.

By Daniel Dominguez

Presentation: Platform Engineering Patterns for Scalable Software Delivery

Building a successful Internal Developer Platform (IDP) requires balancing standardization with developer autonomy. The panelists discuss the core components of modern platforms, the role of platform teams, and strategies for driving adoption across diverse teams. They also share key patterns, anti-patterns, and lessons learned.

By Cat Morris, Martin Reynolds, Mike Fielder, Boyan Dimitrov, Renato Losio

Article: How Causal Reasoning Addresses the Limitations of LLMs in Observability

Large language models excel at converting observability telemetry into clear summaries but struggle with accurate root cause analysis in distributed systems. LLMs often hallucinate explanations and confuse symptoms with causes. This article suggests how causal reasoning models with Bayesian inference offer more reliable incident diagnosis.

By Dhairya Dalal

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