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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

Pulumi Adds Full Bun Runtime Support

Pulumi has announced that Bun is now a fully supported runtime for Pulumi, going beyond its previous role as merely a package manager option. With the new release of Pulumi 3.227.0, developers can set runtime: bun in their Pulumi.yaml and have Bun execute their entire infrastructure program, with no Node.js installation required.

By Claudio Masolo

Effect v4 Beta: Rewritten Runtime, Smaller Bundles and Unified Package System

Effect v4 beta, a TypeScript framework for building applications, features a complete rewrite of its core fiber runtime, offering reduced memory usage and smaller bundle sizes. The new release consolidates ecosystem packages under a single version number and introduces unstable modules for rapid feature development. Migration guides are available for users transitioning from v3 to v4.

By Daniel Curtis

C++26: Reflection, Memory Safety, Contracts, and a New Async Model

The C++26 standard draft is now complete, reports Herb Sutter, long-time C++ expert and former chair of the ISO C++ standards committee. The finalized draft introduces reflection, enhances memory safety without requiring code rewrites, adds contracts with preconditions and postconditions alongside a new assertion statement, and establishes a unified framework for concurrency and parallelism.

By Sergio De Simone

Meta Reports 4x Higher Bug Detection with Just-in-Time Testing

Meta introduces Just-in-Time (JiT) testing, a dynamic approach that generates tests during code review instead of relying on static test suites. The system improves bug detection by ~4x in AI-assisted development using LLMs, mutation testing, and intent-aware workflows like Dodgy Diff. It reflects a shift toward change-aware, AI-driven software testing in agentic development environments

By Leela Kumili

CNCF Warns Kubernetes Alone Is Not Enough to Secure LLM Workloads

A new blog from the Cloud Native Computing Foundation highlights a critical gap in how organizations are deploying large language models (LLMs) on Kubernetes: while Kubernetes excels at orchestrating and isolating workloads, it does not inherently understand or control the behavior of AI systems, creating a fundamentally different and more complex threat model.

By Craig Risi

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