OpenAI is discontinuing ChatGPT Atlas, its standalone desktop browser. The browser-based AI features are moving to the new ChatGPT desktop app, which includes ChatGPT Work, OpenAI’s work-focused agent, alongside ChatGPT Codex.

The end of Atlas. James Sun of OpenAI confirmed on X Atlas will be deprecated Aug. 9.

• “The current targeted date for deprecation is 8/9, and we’ll share more information in the upcoming days both in-app and via email,” Sun said.

One desktop app. The new ChatGPT desktop app becomes OpenAI’s primary desktop product with built-in browser capabilities. Instead of maintaining a separate AI browser, OpenAI is combining browsing, work-agent features, and Codex into a single app.

Chrome users can keep Chrome. OpenAI also offers a ChatGPT and Codex extension for Chrome. That lets Chrome users access ChatGPT in their existing browser without switching to an OpenAI browser.

Why we care. OpenAI is moving AI browsing from a standalone browser into the main ChatGPT app, where more users can ask questions, research brands, and complete tasks. That gives ChatGPT another way to shape discovery beyond traditional search results.

Catch up quick. Atlas will be retired as a standalone browser less than a year after its launch.

• ChatGPT Atlas launched on Mac in October.
• OpenAI later released a dedicated Codex app and added an in-app browser in April.
• Those features are now being folded into the new ChatGPT desktop app.

YouTube expanded Ask YouTube to signed-in U.S. desktop viewers 13 and older, moving its conversational search experience beyond a Premium-only test.

What is Ask YouTube? Ask YouTube lets users type natural-language questions into the YouTube search bar and receive responses that combine text, video clips, long-form videos, and Shorts. Users can also ask follow-up questions to refine results.

Access expands. When YouTube announced the test in April, Ask YouTube was limited to U.S. YouTube Premium members 18 and older who opted in through youtube.com/new. On July 6, YouTube expanded it to signed-in U.S. viewers 13 and older using English-language searches on desktop.

• Signed-out viewers and supervised accounts remain excluded.
• YouTube said it will roll out the feature to more devices, languages, and users worldwide in the coming months.

YouTube standard Search isn’t going away. Users can switch back to traditional video results by clicking All on an Ask YouTube results page or by returning to the Home page. Ask YouTube remains a separate search option rather than a replacement for standard YouTube Search.

Views count for creators. YouTube said videos featured in Ask YouTube responses give creators another way to be discovered.

• Views from Shorts, videos, and previews shown in Ask YouTube responses count toward total view metrics and YouTube Partner Program eligibility. Featured videos also display the video title and channel name.
• YouTube said creators can improve their chances of appearing by publishing unique, high-quality content with clear chapters and descriptive titles. Those signals help its systems match video segments to viewer questions.

Why we care. YouTube is putting conversational search in front of a much larger group of U.S. desktop users. Your videos may need clear titles, chapters, and segments that answer specific questions well enough to appear in Ask YouTube responses.

What it looks like. Here’s a GIF of Ask YouTube in action:

The announcement. Try a new conversational search experience with Ask YouTube

Google is adding AI disclosures to ads across Search, YouTube, and Discover. The new How this ad was made section will appear in My Ad Center, Google announced today.

The panel will indicate whether an ad was created or modified with AI, Google said. The feature will roll out globally across Google’s main ad surfaces, expanding its ad transparency tools as more advertisers use generative AI to create ad assets.

What it looks like. Users can access it from the three-dot menu or the info icon on ads. Here’s a screenshot Google shared with Search Engine Land:

Google will handle some disclosures. Google will automatically add the disclosure in My Ad Center when advertisers use its generative AI ad tools.

• Advertisers using third-party AI tools will have control over whether to disclose AI use. Depending on local requirements, an AI label may also appear directly on the ad, either automatically or after the advertiser uses that control.

Why we care. AI-generated ads are becoming easier to create, making disclosure more important. You need to know when creative was created or modified with AI because disclosure requirements can vary by market and ad format.

Existing ad rules still apply. Google said its ad policies continue to prohibit misleading or deceptive ads, whether AI was used or not. The update adds more transparency about how an ad was made, but doesn’t change Google’s requirement that advertisers clearly identify who they are and what they are promoting.

Earlier AI safeguards. Google already embeds imperceptible signals, including SynthID, into content created with its generative AI tools. Election advertisers must disclose synthetic or digitally altered content in political ads, a policy Google introduced in 2023.

The announcement. Expanding AI transparency in ads

Two new analyses found that ChatGPT’s cited sources changed as its search traffic shifted between hidden retrieval pipelines.

The findings. Research from Chris Green and Suganthan Mohanadasan adds a new complication to AI visibility tracking: the final answer doesn’t reveal how ChatGPT selected its sources.

• Both researchers found internal source-selection labels, including Labrador, Bright, Oxylabs, and SERP.
• Those labels sit behind the answer, not in the citation cards users see.

Hidden pipelines changed sources. Green tested 1,000 prompts up to 10 times each and captured 9,946 completed search runs. Most prompts stayed on one retrieval source. Labrador accounted for 88.1% of primary search sources in his dataset, followed by Bright at 9.9%, Oxylabs at 1.7%, and SERP at 0.3%.

• But 11.6% of prompts changed primary search source across repeated runs.
• URL overlap dropped from 0.273 to 0.149 when the search source changed. Domain overlap fell from 0.265 to 0.155. Green calculated that as roughly 45% lower URL overlap and 42% lower domain overlap.

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The labels behind results. Mohanadasan inspected two days of raw ChatGPT network traffic from one logged-in Pro account and logged about 1,240 source records across a few dozen searches.

• He found a result_source field attached to web results, with four observed values: SERP, Labrador, Bright, and Oxylabs.
• He described Labrador as including established publishers and reference sites, Bright as tied to Bright Data, Oxylabs as tied to Oxylabs, and SERP as an open-web baseline that appeared mostly in news-style results.
• Green’s repeated-prompt test found Labrador dominated his dataset. Mohanadasan saw Bright play a larger role in his sample, especially for commercial, shopping, finance, weather, and local queries.

Some prompts skipped search. Mohanadasan also found that ChatGPT classified some queries before searching, using a turn_use_case field. Some prompts were filed as text and skipped web search entirely, even when they sounded current. In those cases, no page could be fetched, cited, or used as evidence.

• More complex “thinking” queries behaved differently. Mohanadasan found that ChatGPT could fan out into many searches, including site: probes, pricing checks, and searches for unnamed competitors.
• That behavior changes which pages can enter the answer process because ChatGPT may search rewritten queries, direct site probes, or follow-up checks instead of the exact phrase a user typed.

Fetched was not cited. Mohanadasan separated three outcomes: fetched, cited and mentioned.

• A page can be fetched into ChatGPT’s context without being shown to users. It can be cited as the source behind a specific sentence. Or a brand can be mentioned without being the source of the claim.
• In his small commercial-query sample, Reddit and YouTube were both fetched often, but Reddit was cited and YouTube was not. He attributed the gap to text availability: Reddit threads expose text, while YouTube search results often provide metadata rather than full video transcripts.
• Vendor pages were cited for their own facts, such as prices and specs. Third-party pages were more likely to support broader recommendation claims.

Why we care. There’s no single ChatGPT visibility result to measure. Your page may never be considered if ChatGPT skips search, uses another retrieval source, or finds a clearer third-party page to support the claim.

Readable pages were easier to use. Both analyses showed that ChatGPT’s source selection depended partly on what it could retrieve and read.

• Mohanadasan found cases where ChatGPT appeared to prefer official pricing pages, then fell back to third-party sources when prices were hidden behind JavaScript or otherwise hard to parse.
• Green’s results showed that source routing changed which URLs and domains entered the answer set.
• Plain HTML, crawlable facts, clear pricing and specs, strong third-party coverage, and text-heavy pages became more important when source selection depended on retrieval and readability.

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Advanced architecture is no longer just technical structure. It determines whether your content can be found, understood, and surfaced by search engines and AI systems.

Our next SMX Now on July 15 features Shari Thurow, co-founder, information scientist, and search director at the Information Architecture Gateway. She’ll explain how advanced architecture works and where most AI, SEO, and site development workflows fall short.

The session introduces a five-phase framework Thurow has tested through decades of client work with organizations including Microsoft, Google Cloud, Abbott Laboratories, CVS Pharmacy, WebMD, Sony Music, the Library of Congress, Best Buy, and Merriam-Webster. You’ll learn how architecture decisions shape labeling systems, wayfinding networks, taxonomy, wireframes, and AI access to valuable content.

It also challenges long-standing misconceptions, including the three-click rule, the idea that taxonomy is only a hierarchy, and the belief that AI can generate effective wireframes without a deeper architectural model.

You’ll leave with a practical framework for building sites that communicate more clearly with users, search engines, and human-centered AI systems.

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