# Agentic Sites Puts Adobe's AI Speed to Test _Adobe's Carlos Sanchez demoed Agentic Sites that personalize AEM blocks in 1.1 seconds using Cerebras and Gemma 4, grounded on the site's own content._ **Published:** 2026-08-29 **Source:** https://www.startuphub.ai/ai-news/artificial-intelligence/2026/agentic-sites-puts-adobe-s-ai-speed-to-test --- [Agentic Sites](https://www.youtube.com/watch?v=jebp4V0vh30) generated a personalized page in 1.1 seconds live on stage at AI Engineer. Agentic Sites demoCoreCarlos Sanchez showcased live at AI Engineer conference on Adobe Experience ManagerFrom the article 3 mentionsAgentic Sites generated a personalized page in 1.1 seconds live on stage at AI Engineer.Cerebras fast inferenceCoreFrom the article 3 mentionsA backend service does reasoning over a vector database and calls LLM providers, with Cerebras used for fast inference and alternatives like Bedrock tested.Intent driven personalizationDriverAdapts page blocks to what visitor is trying to accomplish in real timeFrom the articleThe goal is intent driven personalization that adapts the page to what the visitor is trying to do right now.1.1 second generationOutcomeHero, products, navigation, and CTAs personalized within the threshold windowFrom the article 6 mentionsSanchez said Adobe targets 1 to 2 seconds for generation because proven data shows faster sites drive more conversions.grounded byRAG grounded on site contentContextVector corpus built from full site keeps brand guidelines and blocks hallucinationFrom the articleAll generated text is grounded on a RAG corpus built from the full site, so brand guidelines stay intact.Agentic Sites demoCoreCarlos Sanchez showcased live at AI Engineer conference on Adobe Experience ManagerFrom the article 3 mentionsAgentic Sites generated a personalized page in 1.1 seconds live on stage at AI Engineer.Browsing signals feed engineContextContinuously recorded pages visited and time on each shape personalization inputsFrom the article 2 mentionsInstead of hallucinating a whole site, the engine personalizes blocks like the hero card, products, blog feeds, navigation and calls to action.Intent driven personalizationDriverAdapts page blocks to what visitor is trying to accomplish in real timeFrom the articleThe goal is intent driven personalization that adapts the page to what the visitor is trying to do right now.grounded byRAG grounded on site contentContextVector corpus built from full site keeps brand guidelines and blocks hallucinationFrom the articleAll generated text is grounded on a RAG corpus built from the full site, so brand guidelines stay intact.served viaAEM Edge DeliveryCoreFramework pushes rendering to edge for hyper personalized web experiencesFrom the articleContent lives on AEM Edge Delivery Services, a framework that pushes rendering to the edge for speed.reasons onCerebras fast inferenceCoreFrom the article 3 mentionsA backend service does reasoning over a vector database and calls LLM providers, with Cerebras used for fast inference and alternatives like Bedrock tested.enables1.1 second generationOutcomeHero, products, navigation, and CTAs personalized within the threshold windowFrom the article 6 mentionsSanchez said Adobe targets 1 to 2 seconds for generation because proven data shows faster sites drive more conversions.preservesMarketers retain controlEffectEditors approve layouts, blocks, and brand guardrails before any generation runs Principal scientist Carlos Sanchez built the demo inside [Adobe (NASDAQ:ADBE)](https://www.google.com/finance/quote/ADBE:NASDAQ) Experience Manager to show hyper-personalized websites working at edge speed. ## What Agentic Sites actually do The goal is intent driven personalization that adapts the page to what the visitor is trying to do right now. Instead of hallucinating a whole site, the engine personalizes blocks like the hero card, products, blog feeds, navigation and calls to action. All generated text is grounded on a RAG corpus built from the full site, so brand guidelines stay intact. ## How the stack is wired Content lives on AEM Edge Delivery Services, a framework that pushes rendering to the edge for speed. A backend service does reasoning over a vector database and calls LLM providers, with [Cerebras](https://www.startuphub.ai/ai-news/startup-news/2026/cerebras-systems-eyes-4-8-billion-ipo-amid-ai-chip-demand) used for fast inference and alternatives like Bedrock tested. Browsing signals are recorded continuously, including pages visited and time on each page, then fed to the LLM to pick personas like exploring. ## Why 1.1 seconds is the threshold Sanchez said Adobe targets 1 to 2 seconds for generation because proven data shows faster sites drive more conversions. Evaluation runs continuously with Promptfoo, which systematically tests prompts and models side by side. On a 15 prompt test set for the demo coffee gear site, Cerebras with Gemma 4 averaged 1.1 seconds while the next best provider averaged 4.6 seconds. The demo showed 2,300 tokens per second and an LLM time of 1 second for a query about a coffee machine for camping, which returned tailored copy and recommendations for Agile and Nano brewers. Cerebras has previously reported wafer scale inference above 1,800 tokens per second on Llama 3.1 8B and record 3,000 tokens per second on OpenAI models. ## Where marketers keep control Marketers define personalization strategy in natural language and choose how many persona groups to use, such as buyers versus information seekers. Query pages and For You recommendation pages are grouped by intent and can be pre generated and pre fetched as the user browses. Sanchez also showed OfOneLabs, an internal tool that crawls any URL and spins up an agentic site in less than an hour. In the live example it turned an AI engineering events site into a search box that built Europe AI conferences lists and side by side comparisons on the fly. He extended the same query to a voice assistant on Google TV to argue agentic pages work beyond the browser. ## Why this matters [Alphabet Inc. (NASDAQ:GOOGL)](https://www.google.com/finance/quote/GOOGL:NASDAQ) and Adobe are both pushing agentic personalization as the product layer, not the research layer, with Adobe's Agent Orchestrator already in beta for Experience Platform. The demo reframes the bottleneck from model quality to inference economics, since each personalized page needs an LLM call and fresh RAG retrieval. That favors wafer scale inference vendors like Cerebras and Groq over general GPU clouds, and it pressures CMS rivals to match edge plus AI latency. StartupHub.ai data shows You raised $80M in its 2023 Series A and tracks Promptfoo among peers including Perplexity AI, [Alphabet Inc. (NASDAQ:GOOGL)](https://www.google.com/finance/quote/GOOGL:NASDAQ), Lucidworks, matey and Dante. Adobe's comparison makes the point explicit: Promptfoo lets teams prove whether speed is good enough when accuracy is similar across providers. The gap not covered is cost at scale, governance of auto generated blocks, and how Adobe will price per generation when every visitor becomes an audience of one. --- Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory. © StartupHub.ai. All rights reserved. You may not republish this article in full without a license. Search engines and AI research tools may crawl and summarize for reference. Bulk reproduction or model training on this content requires a license. See https://www.startuphub.ai/terms.