- Medium’s CEO Details Path to Profitability After $2.6M Monthly Losses
- Meta Acquires Chinese-Founded AI Startup Manus
- Design System Annotations: Why Accessibility is Often Overlooked in Component Design (Part 1)
- The Red-Teaming Resistance Leaderboard: Evaluating LLM Safety
- Automating Your DevOps: Writing Scripts that Save Time and Headaches
- The Most Overlooked Way to Stop Spam Calls on Android and iPhone
- SteelSeries Arctis Nova 7P Gen 2 review: a highly versatile headset that’s become a daily driver
- KrebsOnSecurity.com Marks 16 Years of Cybersecurity Reporting
Browsing: Tools
The 2025 Python Typing Survey highlights the widespread adoption of type hints, with 86% of developers regularly using them. Key findings reveal that improved code quality, readability, and enhanced tooling are primary motivators. The survey also identifies challenges such as third-party library support and the complexity of advanced features, while noting a growing interest in TypeScript-inspired features and runtime type enforcement. Learning resources include official documentation, blog posts, and increasingly, large language models.
This article explores advanced methods for annotating design system components, moving beyond basic descriptions to address complex behaviors, states, and contextual usage. It covers interactive, contextual, and code-driven annotation techniques to improve clarity and collaboration between design and development teams.
GitHub Actions workflow pages can now successfully render workflows with over 300 jobs, thanks to the implementation of lazy loading. Users can also filter jobs by status, allowing for easier viewing of failed or in-progress tasks. These enhancements are designed to improve the experience for teams managing complex workflows and large monorepo setups.
Cloudflare Queues now offers new APIs for pausing message delivery and purging messages. These features help manage queues during consumer downtime, clear invalid messages, or clean up stale backlogs, available via Wrangler, REST API, or the dashboard.
Firefox’s security model relies on process separation and Inter-Process Communication (IPC). Exploiting IPC interfaces can lead to sandbox escapes. This post explores how snapshot fuzzing, a new technology, is now being used in production to find and fix vulnerabilities in Firefox’s critical IPC layer, significantly improving browser security.
Firefox is rolling out new features to enhance user experience. These include on-device web translations for iOS, customizable app icons for Android, and a new optional search engine powered by Perplexity. The translation feature prioritizes privacy by processing content locally on the device.
Dropbox has unveiled its seventh-generation hardware platform, featuring Crush, Dexter, and Sonic for traditional workloads, alongside new GPU tiers, Gumby and Godzilla. This latest architecture significantly boosts storage bandwidth, doubles available rack power, and introduces an advanced storage chassis to minimize vibration and heat, aiming for enhanced efficiency and scalability.
Workers AI has introduced a new JSON mode, allowing users to easily request and receive structured data directly from AI models. This enhancement simplifies data extraction and reduces the need for complex parsing of unstructured text responses, integrating seamlessly with the OpenAI SDK’s structured outputs API.
The core 2Africa infrastructure, the world’s longest open-access subsea cable system, has been completed. This monumental project aims to connect communities, foster economic growth, and enable digital experiences across Africa, Europe, and Asia, impacting billions of people through unprecedented scale and innovative engineering.
Developing robust conversational AI systems requires a structured approach to evaluation, treating it as an integral part of the development process. This article outlines a practical blueprint for evaluating large language models (LLMs) at scale, covering dataset curation, actionable metrics, platform setup, automated pipeline integration, and continuous improvement strategies. The methodology emphasizes rigorous testing and feedback loops to ensure accuracy, reliability, and quality control in AI deployments.
