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Google will extract landing-page images for new Performance Max campaigns by default — even when accounts opt out

Google is changing the default for Performance Max image extraction on December 4, 2026. Existing campaigns keep their settings, but new campaigns will opt in regardless of an account-level opt-out; agencies and SaaS ad tools need a campaign-level override and careful handling of repeated asset settings.

ChatGPT Atlas can still surface blocked URLs unless publishers use noindex

Blocking OAI-SearchBot is not a complete removal signal for ChatGPT Atlas. OpenAI says a disallowed page can still appear as a link and title when the URL is learned elsewhere and judged relevant; publishers that want to suppress that result need a crawlable noindex directive, while GPTBot remains the separate training control.

GitSpawn shows how a repository’s own Git config can escape AI coding-agent safety boundaries

The useful lesson is architectural rather than vendor-specific: coding agents inherit execution paths from ordinary developer tooling. If an agent shells out to Git without sanitising repository-local configuration, a hidden `.git/config` can become a host-level command channel that bypasses the controls users think govern the model.

Funes gives coding agents a local memory that can follow you across tools and machines

Funes treats agent memory as user-owned data rather than a hosted account feature: retrieval and reranking run locally, provenance stays attached to recalled passages, and cross-machine sharing is optional. The main risk is that publishing session-derived memory can still expose secrets if redaction misses them.

GLM-5.3-Flash turns the anonymous Ox Alpha trial into an open-weight multimodal coding model

GLM-5.3-Flash combines open weights, multimodal coding/agent capability and an 18B-active sparse architecture with a large anonymous pre-launch trial. Z.ai has already issued a chat-template correction for early downloads, showing that day-one self-hosted deployments need artifact-level validation as well as model benchmarking.

Microsoft Project Zenith turns 64GB-class Windows PCs into a standardized local-AI developer tier

Project Zenith is not a new model or another Copilot feature. It standardizes a developer-focused Windows experience and hardware floor for local AI work, with preconfigured tooling and OS settings intended to reduce setup friction and dependence on metered cloud inference.