Cherry Prommawin presented crawling, indexing and serving in classic Search and Gary Illyes the AI parts (his hand-over and her self-introduction at the start). Transcript from a second attendee recording.
Shown on screen 20
Search runs as three stages, crawling, indexing and serving, and the event covered one stage per day.
Speaker Cherry Prommawin, Gary IllyesEvidence 2 slide photos, transcript
- Extended by D1-C214 Day 1: Crawling and indexing happen before anyone searches, while serving and ranking happen in real time when…
- Extended by D2-C026 Day 2: A Google pipeline slide placed processing between the crawler and the index and listed six processing steps…
- Repeated by D2-C719 Day 2: The speaker recapped Google's pipeline up to the index: Google crawls pages, processes the fetched documents…
For classic Search, crawling means Googlebot, scheduling and robots.txt, with AI used in parts such as scheduling. Indexing is one big but not limitless index that calculates signals and understands more than words, with AI such as BERT. Serving uses hundreds of signals tailored to the moment, with AI such as RankBrain.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Extended by D1-C205 Day 1: Signals calculated for a page during indexing are stored in the index and used both to decide whether the…
- Extended by D1-C211 Day 1: Index selection runs after signals are collected and duplicates are dropped, and decides what goes into…
- Extended by D2-C344 Day 2: Google deduplicates pages because many sites have very many pages and Google's index does not have room for…
- Extended by D2-C648 Day 2: Among the many signals Google calculates during indexing, the ones singled out as having large effects on…
- Repeated by D2-C680 Day 2: Google's index is immense but finite, so Google cannot index every URL it finds on a web with a practically…
- Extended by D2-C684 Day 2: Index selection is a predictive AI system that relies heavily on machine learning.
- Extended by D2-C722 Day 2: Each document in Google's index has pretty much all the signals calculated for it attached, for example…
AI Mode and AI Overviews use the same crawling and the same index as Search. At serving they add grounding on the Search index and query fan-out.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
Used byrequirement DEV-AIF-01story angle A-001glossary terms AI Mode, Grounding
- Extended by D1-C208 Day 1: AI Overviews and AI Mode may have extra processes of their own, like any other search feature, but the bulk…
- Extended by D1-C325 Day 1: Googlebot is the crawler Google uses for web search, including Search's AI features.
- Extended by D1-C388 Day 1: AI Mode is a feature that sits on top of Google's existing crawling infrastructure, so Google does not crawl…
- Extended by D2-C073 Day 2: John Mueller said Google uses the snippet as a way of building AI Overviews and AI Mode answers, so if a page…
- Extended by D2-C074 Day 2: Google's AI features guide says a page must be indexed and eligible to be shown in Google Search with a…
- Repeated by D2-C116 Day 2: AI Overviews and AI Mode are built on top of Search results: they are a different experience of the same…
- Extended by D2-C476 Day 2: The structured data Google processes is not fed very differently to AI Overviews and AI Mode: after cleaning…
- Extended by D2-C603 Day 2: Users often assume AI is all-knowing and borderless, but AI is still language-dependent: if an AI answer is…
- Extended by D2-C726 Day 2: AI Overviews and AI Mode use the same index structures and token-based snippets as classic web results, a…
- Extended by D3-C057 Day 3: Google's slide on how LLM features with grounding generally work showed a query going to both the search…
- Extended by D3-C701 Day 3: Google's closing slide said AI on Google is just SEO: AI features on Google Search use exactly the same…
- Repeated by D3-C702 Day 3: AI Overviews and AI Mode are built on the Search infrastructure Google has used for 25 to 30 years and have…
Gemini is not part of Search, but it uses crawlers for data, shares some technologies such as tokenization and deduping, and grounds on the Search index.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Extended by D1-C226 Day 1: Google said it does not own third-party AI chatbots such as ChatGPT and has no insight into how they work or…
- Extended by D1-C335 Day 1: Crawling for Gemini may be set to care less about quality and more about the amount of content, because for…
- Extended by D2-C118 Day 2: To train Gemini models, Google renders every page just as it does for Search, so a page that renders…
- Extended by D2-C120 Day 2: When a Gemini user asks about a specific web page (for example, whether it says anything about the ruby HTML…
- Contradicted by D2-C325 Day 2: Tokenization for AI models such as Gemini, in training and in inference, differs from tokenization for…
- Extended by D2-C669 Day 2: SpamBrain, Google's AI-based spam detection system, is nowadays built on Gemini and fine-tuned specifically…
URL discovery works through links: a homepage links to section pages, which link to further pages.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
Used byrequirement DEV-URL-04
- Extended by D1-C202 Day 1: Google may visit hub pages, such as a homepage or category pages, more often than other pages, because they…
- Extended by D1-C336 Day 1: Google finds what to crawl mainly by extracting URLs from previously crawled pages, and additionally from…
- Extended by D2-C820 Day 2: Google's Q&A slide advised large sites to rely on hub pages, such as category pages, that link out to their…
- Extended by D2-C038 Day 2: Google uses the links it extracts for three purposes: discovering new pages, determining a site's structure…
- Extended by D2-C168 Day 2: In Google's processing step, links are extracted from the HTML Google already has, before rendering, and the…
- Extended by D2-C169 Day 2: Google's JavaScript SEO basics guide says Googlebot extracts links twice, from the HTML response before…
- Extended by D2-C287 Day 2: A link that is an <a> element but does not point to a real URL gives Google something to look at, but Google…
Statistical models have been used at Google for over 20 years, for catching spam and originally for the 'Did you mean' feature.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Extended by D1-C209 Day 1: Google launched the 'Did you mean' feature around 2001-2002 using a statistical model, which Gary Illyes…
- Extended by D2-C668 Day 2: Google uses more and more AI to detect spam, and Google's testing shows that this AI-based detection is…
- Extended by D2-C669 Day 2: SpamBrain, Google's AI-based spam detection system, is nowadays built on Gemini and fine-tuned specifically…
- Extended by D3-C680 Day 3: Gary Illyes said machine learning is about 50 years old and that Google has been using it for 'probably 30…
BERT is used in indexing to understand each word in the context of the whole sentence rather than one word at a time.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
Used byglossary term BERT, RankBrain and MUM
- Extended by D2-C338 Day 2: Google detects soft 404s with a language model, described as something like BERT, that is trained to…
- Extended by D3-C684 Day 3: Predictive language models have been used a lot in Search, and BERT is one: technically, in the purest sense…
RankBrain is used in serving to interpret the intent behind queries, especially new or unusual ones, and match them to relevant results.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo
Used byglossary term BERT, RankBrain and MUM
- Extended by D1-C217 Day 1: Google began talking publicly about its use of AI in Search around 2015-2016, and RankBrain was the first…
MUM (Multitask Unified Model) understands information across text, images, audio and video, and processes information in more than 75 languages.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo
- Extended by D1-C218 Day 1: Google said MUM helps it understand the context of the words in a query: a search for hiking shoes that…
Ranking signals differ by result type: web pages (text, links, passages), images (resolution, colour, associated text), news (freshness, originality, diversity), local (location, type, rating, reviews, hours) and videos (language, text from speech).
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Repeated by D2-C537 Day 2: The text around an image is critical: Google uses it as context to understand the image and to rank it, so an…
- Extended by D2-C656 Day 2: Freshness is a signal for queries that deserve fresh results ('query deserves freshness'): when a breaking…
- Repeated by D3-C142 Day 3: Google's quality talk said ranking signals differ by result type: for web pages they include the text on the…
QQuestion and answers
A Google slide headed 'Your Question' raised whether Google can distinguish between AI-written and human-written content, presented on stage as the question this topic usually prompts rather than one asked live.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
Google's answer was that ML-based ranking systems are trained on content written by humans for humans, so they understand and promote natural content better.
“ML based ranking algorithms and signals are trained on content by humans for humans. They "understand" and promote natural content better.”
Wording checked against the slide or recording
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Extended by D1-C220 Day 1: Google said the more important documents in its index naturally tend to be documents created by humans.
- Extended by D1-C221 Day 1: Google said the natural content its ranking algorithms understand and promote better includes content created…
- Repeated by D3-C116 Day 3: Google's long-standing advice to write for people and give them what they want has become true in practice…
Google said it is not really trying to tell AI-written from human-written content, because it cares more about the quality of content than about how it was created.
“We care more about the quality of the content than how it was created.”
Speaker Gary IllyesEvidence transcript
- Repeats D1-C175 Day 1: Explaining the principle of incentivising high-quality content, Google said the content may be created by…
- Repeated by D3-C190 Day 3: Google's quality talk said quality problems should be treated as quality issues, not as AI versus human…
Google's answer to 'SEO is dead, long live GEO' is not to worry about the name: good SEO is good GEO and AEO.
“Don't worry about what to call it. Good SEO is good GEO, AEO.”
Wording checked against the slide or recording
Speaker Cherry Prommawin, Gary IllyesEvidence 2 slide photos, transcript
Used bymyth M-001quote Q-001story angle A-001glossary term GEO and AEO
- Extended by D1-C198 Day 1: Gary Illyes said SEO is not dead and that the new AI features only create more opportunities for site owners…
- Contradicted by D1-C296 Day 1: A community speaker argued for adopting the GEO label as the industry's chance to leave behind the bad…
- Repeated by D2-C601 Day 2: Sites need no extra work to appear in AI Overviews and AI Mode: both work on top of the existing web results…
- Repeated by D3-C701 Day 3: Google's closing slide said AI on Google is just SEO: AI features on Google Search use exactly the same…
Three reasons were given: generative AI features are built directly on the core ranking systems, query fan-out expands the original query to find related information, and generative AI features highlight content indexed by Google Search.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
Used byrequirement DEV-AIF-01myth M-001story angle A-001glossary term AI Overviews
- Extended by D1-C225 Day 1: Google said query fan-out is nothing new: it fires, for example, ten different searches in the background…
- Repeated by D2-C601 Day 2: Sites need no extra work to appear in AI Overviews and AI Mode: both work on top of the existing web results…
- Extended by D2-C727 Day 2: Google said that when AI Overviews or AI Mode run a query fan-out, the generated queries are sent to Google's…
- Repeated by D3-C056 Day 3: Google's generative AI features in Search build on the traditional ways of searching, so query understanding…
Myth: optimise for AI over readers. Google's answer: optimise for people, with no need to obsess over precise keywords or AI phrasing, no need to chop content, and no need for llms.txt.
“LLMS.txt isn't necessary.”
Wording checked against the slide or recording
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
Used byrequirements DEV-AIF-02, DEV-AIF-03myth M-002story angle A-001glossary term llms.txt
- Repeated by D1-C271 Day 1: A community speaker said llms.txt files are not necessary, citing a third-party study from summer 2026 (heard…
- Extended by D2-C330 Day 2: Gary Illyes said the common SEO advice to chunk content for AI systems is misunderstood: chunking is real…
- Extended by D2-C332 Day 2: Gemini does not need content cut into small chunks of 100 or 200 words, Gary Illyes said, since a smaller…
Myth: build content for every possible consumer need. Google's answer: prioritise unique perspectives, expertise and in-depth experience that go beyond common knowledge.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Extended by D3-C179 Day 3: Google's quality talk said non-commodity content offers a unique, experienced take, and advised writing…
- Repeated by D3-C588 Day 3: Google's slide advised producing unique, helpful, human-centric content.
Myth: your website is no longer relevant. Google's answer: keep content crawlable, well structured, fast and easy to read, for readers and for AI tools.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Extended by D2-C124 Day 2: Google's simple solution for the extra time of live page reads is to make JavaScript-generated content render…
- Extended by D2-C134 Day 2: Google urged sites to make sure their JavaScript content can be crawled, rendered and indexed, calling this…
- Extended by D2-C139 Day 2: A community speaker strongly advised putting everything you want cited into the raw, server-side rendered…
Myth: the old metrics don't work in the AI era. Google's answer: measure success through metrics that matter to your business.
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
- Extended by D3-C518 Day 3: A community speaker concluded that rankings and clicks no longer equal real business outcomes.
- Extended by D3-C536 Day 3: A May 2025 Search Central blog post advised site owners to look at the overall value of visits from Search…
- Extended by D3-C542 Day 3: Google's own line on Day 1 was to measure success by metrics that matter to the business, and its Generative…
Optimising for people is optimising for generative AI Search.
“Optimizing for people is optimizing for Generative AI Search”
Wording checked against the slide or recording
Speaker Cherry Prommawin, Gary IllyesEvidence slide photo, transcript
Used byquote Q-002
- Extended by D3-C497 Day 3: Pages that do better in AI answers than in classic results do not refute Google's line that optimising for…
- Repeated by D3-C586 Day 3: Google's marketing research talk reached the same advice as Search: optimise for people to win in generative…
Said on stage 24
Google said there are trillions of URLs on the internet, or even more, that even Google cannot tell how many exist, and that some may never be discovered.
Speaker Cherry PrommawinEvidence transcript
- Extended by D3-C602 Day 3: Google said it knows hundreds of trillions of URLs (as of October 2026).
Google may visit hub pages, such as a homepage or category pages, more often than other pages, because they usually link out to new or updated pages.
Speaker Cherry PrommawinEvidence transcript
Used byrequirement DEV-URL-04glossary term Hub pages
- Extends D1-C040 Day 1: URL discovery works through links: a homepage links to section pages, which link to further pages.
- Extended by D2-C820 Day 2: Google's Q&A slide advised large sites to rely on hub pages, such as category pages, that link out to their…
A crawler is software that downloads pages, extracts their links and repeats the process on the links it extracted; Googlebot is the main crawler of Google Search.
Speaker Cherry PrommawinEvidence transcript
Indexing starts with parsing the fetched HTML, so that elements of the page such as the title can be extracted and accessed easily.
Speaker Cherry PrommawinEvidence transcript
Signals calculated for a page during indexing are stored in the index and used both to decide whether the page gets indexed and, later, for ranking.
Speaker Cherry PrommawinEvidence transcript
- Extends D1-C037 Day 1: For classic Search, crawling means Googlebot, scheduling and robots.txt, with AI used in parts such as…
- Extended by D2-C687 Day 2: Index selection uses the signals calculated earlier in indexing for each document it has to select or discard.
Google renders JavaScript-heavy pages from their HTML, CSS and JavaScript as a browser would, using the latest version of Chromium.
Speaker Cherry PrommawinEvidence transcript
- Repeated by D2-C126 Day 2: Google renders pages with Chromium, the browser technology that also underlies Chrome, Edge and other…
- Extended by D2-C173 Day 2: Google's renderer is a headless Chromium that runs the page's JavaScript.
Google clusters duplicate pages and selects one page per cluster as its representative, the canonical URL, so that users are not shown duplicates.
Speaker Cherry PrommawinEvidence transcript
- Repeats D1-C128 Day 1: Google's canonicalization guide says some duplicate content on a site is normal and not a violation of its…
- Extended by D2-C345 Day 2: Google's deduplication has three steps: identify and cluster duplicate web pages, pick representative URLs…
- Extended by D2-C346 Day 2: For deduplication, a cluster is a set of pages Google considers essentially equivalent: Google stores one of…
AI Overviews and AI Mode may have extra processes of their own, like any other search feature, but the bulk of their processing is the same as for normal Search.
Speaker Gary IllyesEvidence transcript
- Extends D1-C038 Day 1: AI Mode and AI Overviews use the same crawling and the same index as Search. At serving they add grounding on…
Google launched the 'Did you mean' feature around 2001-2002 using a statistical model, which Gary Illyes counted as AI because it is a form of machine learning.
Speaker Gary IllyesEvidence transcript
- Extends D1-C041 Day 1: Statistical models have been used at Google for over 20 years, for catching spam and originally for the 'Did…
- Repeated by D3-C680 Day 3: Gary Illyes said machine learning is about 50 years old and that Google has been using it for 'probably 30…
Index selection runs after signals are collected and duplicates are dropped, and decides what goes into Google's index, which is big but not limitless.
Speaker Cherry PrommawinEvidence transcript
- Extends D1-C037 Day 1: For classic Search, crawling means Googlebot, scheduling and robots.txt, with AI used in parts such as…
- Extended by D2-C682 Day 2: Google's index selection system calculates thresholds and decides which documents are kept and which are…
- Extended by D2-C688 Day 2: Index selection is the last step before documents enter Google's index.
When a page is selected for Google's index, its whole duplicate cluster goes into the index with it.
Speaker Cherry PrommawinEvidence transcript
Google said its index, printed on paper, would reach the Moon and back twelve times.
Speaker Cherry PrommawinEvidence transcript
Crawling and indexing happen before anyone searches, while serving and ranking happen in real time when someone types a query.
Speaker Cherry PrommawinEvidence transcript
- Extends D1-C036 Day 1: Search runs as three stages, crawling, indexing and serving, and the event covered one stage per day.
Serving starts with interpreting the query, which includes cleaning it up, detecting its language and expanding it.
Speaker Cherry PrommawinEvidence transcript
- Extended by D3-C007 Day 3: Query language detection works poorly when someone searches only for a brand name, such as Facebook or…
Google said quality is one of the most important things in ranking.
Speaker Cherry PrommawinEvidence transcript
Google began talking publicly about its use of AI in Search around 2015-2016, and RankBrain was the first such system it publicised widely.
Speaker Gary IllyesEvidence transcript
- Extends D1-C043 Day 1: RankBrain is used in serving to interpret the intent behind queries, especially new or unusual ones, and…
Google said MUM helps it understand the context of the words in a query: a search for hiking shoes that mentions Mount Everest rather than Kilimanjaro gets results suited to that climb.
Speaker Gary IllyesEvidence transcript
- Extends D1-C044 Day 1: MUM (Multitask Unified Model) understands information across text, images, audio and video, and processes…
Google said the more important documents in its index naturally tend to be documents created by humans.
Speaker Gary IllyesEvidence transcript
- Extends D1-C047 Day 1: Google's answer was that ML-based ranking systems are trained on content written by humans for humans, so…
Google said the natural content its ranking algorithms understand and promote better includes content created by humans or at least edited and reviewed by them.
“content that was created by humans, or at least edited and reviewed”
Speaker Gary IllyesEvidence transcript
- Extends D1-C047 Day 1: Google's answer was that ML-based ranking systems are trained on content written by humans for humans, so…
After ordering the results, Google constructs the results page by deciding which search features fit the intent of the query.
Speaker Cherry PrommawinEvidence transcript
Google said a majority of its search features now use AI.
Speaker Cherry PrommawinEvidence transcript
For visual search, Google breaks an image down into vectors, sends the vectors to the index and returns results based on them.
Speaker Gary IllyesEvidence transcript
- Repeated by D3-C311 Day 3: Google handles an image used as a search query much like a text query interpreted as an embedding: the image…
Google said query fan-out is nothing new: it fires, for example, ten different searches in the background, each a normal search on the same systems.
“it is just ten different searches that fire in the background”
Speaker Gary IllyesEvidence transcript
- Extends D1-C051 Day 1: Three reasons were given: generative AI features are built directly on the core ranking systems, query…
- Extended by D3-C061 Day 3: Google tries to make fan-out queries distinct from each other for better coverage, avoiding asking the same…
Google said it does not own third-party AI chatbots such as ChatGPT and has no insight into how they work or are built.
Speaker Gary IllyesEvidence transcript
- Extends D1-C039 Day 1: Gemini is not part of Search, but it uses crawlers for data, shares some technologies such as tokenization…
What Google's documentation says 9
Google's ranking systems guide lists BERT among its ranking systems, as an AI system that helps Google understand how combinations of words express different meanings and intent.
“an AI system Google uses that allows us to understand how combinations of words express different meanings and intent”
Publisher Google Search Central
Google's May 2021 announcement of MUM says it is trained across 75 languages and understands information across text and images, and that it could expand to other modalities such as video and audio in the future.
“MUM is multimodal, so it understands information across text and images and, in the future, can expand to more modalities like video and audio.”
Publisher Google blog (18 May 2021)
Google's ranking systems guide says MUM is not currently used for general ranking in Search, only for specific applications such as COVID-19 vaccine searches and featured snippet callouts.
“It's not currently used for general ranking in Search”
Publisher Google Search Central
Used byglossary term BERT, RankBrain and MUM
- Extended by D3-C135 Day 3: The quality talk's slide listed MUM among Google's ranking systems, while Google's ranking systems guide says…
Google's guide for generative AI features says optimising for generative AI search is optimising for the search experience, and is therefore still SEO.
“optimizing for generative AI search is optimizing for the search experience, and thus still SEO”
Publisher Google Search Central
Used bymyth M-001story angle A-001glossary term GEO and AEO
Query fan-out means running several related searches at once to gather more results; a question about lawn weeds may also search herbicides and weed prevention.
Publisher Google Search Central
Used byglossary term Query fan-out
- Extended by D1-C412 Day 1: A community speaker described AI search as turning one query into many related searches, including searches…
- Extended by D2-C727 Day 2: Google said that when AI Overviews or AI Mode run a query fan-out, the generated queries are sent to Google's…
- Extended by D2-C729 Day 2: Google says query fan-out in AI Overviews and AI Mode issues related searches across subtopics and several…
- Repeated by D3-C058 Day 3: In Google's AI features, the query and the search results are additionally sent to an LLM, which returns new…
Google's guide says creating separate content for every variation of how people might search, including fan-out queries, primarily to manipulate rankings or AI responses violates its scaled content abuse policy. It adds that its AI systems can understand a page's relevance even without an exact match to the query.
Publisher Google Search Central
Used byrequirement DEV-AIF-03glossary term Scaled content abuse
- Extended by D2-C741 Day 2: In embedding-based retrieval, the distance between the embeddings of documents and the embedding of the…
- Extended by D3-C065 Day 3: Because every system runs fan-out differently, Google advised understanding that fan-out happens but not…
- Extended by D3-C212 Day 3: Google's quality talk said Google clarified that traditional spam techniques aimed at manipulating AI…
Google's guide says new machine-readable files, AI text files or special markup are not needed to appear in Search, and that such files neither harm nor help visibility because Google Search ignores them.
Publisher Google Search Central
Used byrequirement DEV-AIF-02story angle A-001glossary term llms.txt
- Extended by D2-C477 Day 2: As far as the speaker knows, in most of Google's main AI uses a page's schema.org markup is not turned into…
- Extended by D2-C480 Day 2: Google's guide to optimizing for generative AI features lists 'overfocusing on structured data' among the…
Google's guide for generative AI features recommends the Generative AI performance report in Search Console for measuring how content performs in generative AI features on Google Search and Discover.
Publisher Google Search Central
Used byrequirement DEV-MON-07glossary term Generative AI performance report
- Extended by D3-C535 Day 3: Beyond Search Console, Google's AI features guide suggests tracking conversions and time spent on the site in…
Google's launch post for the Generative AI performance reports in Search Console (3 June 2026; rolled out to all sites worldwide by 31 August 2026) lists impressions, pages, countries, devices (Search only) and dates, and no click or query metrics.
Publisher Search Central blog (3 June 2026)
Used byrequirement DEV-MON-07glossary term Generative AI performance report
- Repeated by D1-C196 Day 1: Google said Search Console's generative AI reporting launched alongside the generative AI control, starting…
- Extended by D2-C607 Day 2: Check AI Overviews and AI Mode with native-language queries in each target market, not with translated…
- Extended by D3-C063 Day 3: Google said fan-out queries are not added to Search Console, because Google considers them part of its…
- Repeated by D3-C437 Day 3: Search Console added reporting of the impressions a site's content gets in the AI surfaces of Google Search…
- Repeated by D3-C439 Day 3: Search Console's generative AI report shows impressions broken down by pages, countries and devices.
- Extended by D3-C495 Day 3: Nik Vujic said he hopes Search Console's generative AI report will get query data.
- Extended by D3-C542 Day 3: Google's own line on Day 1 was to measure success by metrics that matter to the business, and its Generative…