{"id":341468,"date":"2025-12-13T05:06:44","date_gmt":"2025-12-13T05:06:44","guid":{"rendered":"https:\/\/peraltafinancing.com\/business\/marketing\/ai-meets-content-orchestration-story-needle\/"},"modified":"2025-12-13T05:06:44","modified_gmt":"2025-12-13T05:06:44","slug":"ai-meets-content-orchestration-story-needle","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=341468","title":{"rendered":"AI meets content orchestration &#8211; Story Needle"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div>\n<p>When Generative AI emerged, interest in structured content went into hibernation.  It seemed like LLMs could generate text on demand, tailored to any specific scenario.  All you needed was a bank of prompts to cover the scenarios you had in mind.<\/p>\n<p>Alas, the real world turns out to be more complicated. LLMs don\u2019t have enough context to provide highly tailored content, and the information sources are too diverse for them to understand what to draw on.<\/p>\n<p>As organizations drop magical thinking about LLMs and embrace greater realism, they are returning to the concept of orchestration.  <\/p>\n<p>I wrote about orchestration a couple of years ago.  I noted that \u201cstructured content enables online publishers to <a href=\"https:\/\/storyneedle.com\/orchestrating-the-assembly-of-content\/\">assemble pieces of content in multiple ways<\/a>.\u201d  But the challenge is knowing how to assemble those pieces, the job of orchestration.  It involves matching the user\u2019s intent, the content\u2019s intent, and the organization\u2019s readiness to address the user\u2019s needs. <\/p>\n<p>Orchestration is challenging for many reasons.  It involves many types of inputs to consider and a mix of hard and soft rules for deciding how to assemble the right content.<\/p>\n<p>AI \u2014 not just LLMs, but also predictive and semantic AI \u2014 offers a range of tools to support decision-making in orchestration.  What previously seemed too complex is now more possible.<\/p>\n<p>The growth in the implementation of the model context protocol (MCP) is helping connect LLMs with the information sources they need to draw on and with the applications required for decision-making and action.  Whereas previously, a handful of firms were positioning themselves to be a proprietary connection layer, now connections are becoming open.<\/p>\n<p>The most promising new orchestration tool is <a href=\"https:\/\/www.activepieces.com\/\">Activepieces<\/a>, an open-source tool that enables organizations to integrate data, content, LLMs, and workflow tools.  It already integrates with Drupal, for example, allowing organizations to pull content from that CMS, combine it with database data, and leverage LLMs to generate content. These tasks can be orchestrated through workflow rules.  The tool is open-ended, allowing for a range of orchestration possibilities.<\/p>\n<p>Tools like Activepieces will support the development of <a href=\"https:\/\/storyneedle.com\/the-death-of-the-webpage-and-rise-of-ai-native-content\/\">AI-native content<\/a>.  We\u2019ll find that providing the right content to the right person at the right time requires a diverse array of content, data, rules, policies, and design decisions. Orchestrators will need to consider context from many perspectives.<\/p>\n<p>\u2014 Michael Andrews<\/p>\n<\/p><\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>When Generative AI emerged, interest in structured content went into hibernation. It seemed like LLMs could generate text on demand, tailored to any specific scenario. All you needed was a bank of prompts to cover the scenarios you had in mind. Alas, the real world turns out to be more complicated. LLMs don\u2019t have enough [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[98],"tags":[11165,7222,4909,6141,30131,3972],"dealstore":[],"offerexpiration":[],"class_list":["post-341468","post","type-post","status-publish","format-standard","hentry","category-marketing","tag-ai","tag-content","tag-meets","tag-needle","tag-orchestration","tag-story"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI meets content orchestration - Story Needle - Som2ny Network<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fivemor.com\/?p=341468\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI meets content orchestration - Story Needle - Som2ny Network\" \/>\n<meta property=\"og:description\" content=\"When Generative AI emerged, interest in structured content went into hibernation. It seemed like LLMs could generate text on demand, tailored to any specific scenario. All you needed was a bank of prompts to cover the scenarios you had in mind. Alas, the real world turns out to be more complicated. 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