Why DNS-Level Blocking Is Replacing Browser Ad Blockers for Full Privacy

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Traditional browser-based ad blockers like uBlock Origin cannot intercept telemetry from operating systems, mobile apps, or IoT devices, leaving significant privacy gaps. Google's Manifest V3 update further limits browser extensions by capping the number of dynamic blocking rules they can apply. DNS-level filtering using encrypted protocols — DNS-over-HTTPS (DoH) and DNS-over-TLS (DoT) — addresses these gaps by blocking malicious or tracking domains before any network connection is established. Response Policy Zones (RPZ) allow recursive resolvers to sinkhole harmful domains network-wide, covering every device including smart home hardware. Combining encrypted DNS with client-side tools is now considered a more comprehensive approach to privacy than browser extensions alone.

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OpenAI Reinstates 5-Hour Usage Cap for Plus Users, Frustrating Coders Mid-Sprint

OpenAI has reinstated a five-hour rolling usage cap for Plus subscribers on its Work and Codex surfaces, reversing a removal it had made earlier in the summer. The return of the limit drew sharp criticism from users, particularly developers who had structured their workflows around the assumption of consistent access. A recurring complaint was not simply that limits exist, but that they shift unpredictably, making it impossible to plan or budget usage across a workday or week. Anthropic users reported similar frustrations, with weekly quotas resetting at irregular intervals and uncertainty over which AI models would remain accessible. The episode highlights a broader tension in AI subscription services: paying customers increasingly find that the usage they are paying for is subject to conditions that can change without reliable notice.

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ProgrammingDEV Community ·

CoreShroud Platform Aims to Harden Android APKs Against Reverse Engineering

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ProgrammingDEV Community ·

Critical Magento RCE Flaw CVE-2026-75650 Exploited via Payment-Failure Emails

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AI Coding Tools Boost Junior Devs but Slow Down Experienced Ones, Studies Find

Recent research presents a mixed picture of AI coding assistants' impact on developer productivity. A multi-company field study involving 4,867 developers found that those using GitHub Copilot completed 26% more tasks, with less experienced developers seeing the greatest gains. However, a July 2025 randomised controlled trial by METR found that 16 experienced open-source developers took 19% longer to complete tasks when AI tools were available, despite expecting a 24% speed improvement. The gap between perceived and actual productivity was notable — developers believed AI had made them faster even when measurements showed the opposite. Researchers suggest the two studies are not contradictory, as outcomes appear to depend heavily on developer experience, task type, and the familiarity of the codebase.

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