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Cloudflare and OpenAI test edge signals that put hundreds of millions of pages into ChatGPT search

Cloudflare supplies page-discovery and change signals; OpenAI independently evaluates and ranks discovered pages. The experiment is limited, respects crawler permissions, and is not a new general opt-in indexing service or a guarantee of traffic.

Reddit opens Max campaign creation to third-party Ads API clients

The change makes Reddit's more automated campaign type usable by agencies, ad-tech platforms and internal campaign systems instead of only through first-party buying surfaces. It expands automation reach, but third-party builders inherit Max's creative and optimization assumptions rather than gaining a new manual campaign type.

Reddit Ads API is changing campaign objectives and retiring onsite lead forms in September

The technical migration is unchanged, but Reddit's documentation has proven unusually volatile. Integrations should now treat September 21 as the current objective/form readiness date and December 8 as the current published cutoff for HOUR reports longer than seven days—while continuing to recheck the live docs before each deadline.

Ahrefs is making a Google-derived AI demand estimate the default in Brand Radar

Ahrefs is standardising Brand Radar on an estimated AI-demand metric because major AI platforms do not publish prompt volume. The new number can improve relative weighting between prompts and platforms, but it remains a modelled proxy rather than a count of how many people actually asked an AI system a question.

Google Ads starts showing how many conversions your first-party data recovered

The shift is broader than another Ads dashboard metric. Google is connecting first-party data pipelines, conversion-recovery estimates, open-source marketing-mix modeling and causal geo experiments into one measurement stack — useful, but still heavily dependent on Google’s own modeling and internal benchmark claims.

Google DeepMind is piloting double-blind frontier-model evaluations with confidential computing

The pilot attacks a persistent evaluation trade-off: labs do not want to reveal frontier-model internals, while evaluators do not want benchmark prompts leaking back to the model provider. DeepMind says a Singapore AI Safety Institute pilot kept both sides’ sensitive assets hidden during execution.