每天早上，Michelle Seo都会收到来自Chattiana的晨间简报，她的Muse人工智能agent.
Chattiana的通报列举了徐的议程和待办事宜清单
“我在挑战自己作为一个内向者，通讯"她称"让她有每日新闻感和填补Zoom呼叫中尴尬的沉默的选择。
徐远在人工智能协助下消费她的消息的第一人。 事实上，这一趋势已变得如此普遍，一些新闻机构开始制作内容，将AI agents——而不是人类读者——视为预定受众。 这可以看起来像任何东西从为AI优化的种子到结构化的片段，允许agents创建个性化的文章。
称 Axios首席收入官Jacquelyn Cameron。 “我们看到，我们看到搜索正在缩小。 LLMs在人们消费新闻的方式上变得越来越重要。
主要出版商以各种方式应对了这一变化。 包括WIRED的母公司Condé Nast在内的许多人签署了协议，允许AI平台露出内容。 外出者正努力“基因引擎优化”或GEO，去年，AIOSEO, WordPress网站的SEO插件，发布，这个功能为网站提供LLM.
也有人采取更防守的姿态："纽约时报"在2023年以侵犯版权罪起诉了OpenAI和Microsoft，指控这些公司非法训练了报道模式。 该案仍在进行中。
Axios和少数其他人在尝试什么
“我们总是称，”卡梅伦·称，“我们想成为观众所在地。”
在9月的Digiday出版峰会上，Axios 宣布即将到来的Axios Direct：为AI agents所设计的Feed.
Cameron 称认为，她形容这些素材是agents更高效地访问Axios内容，削减叙事来优先排列结构化数据
最初的两个"直接"(Direct feed)针对的是公司客户。 第一个是今年秋天的发布，它让Axios Pro Deals的AI agents用户访问合并和收购的内容。 第二回取料会起源头作用，在内部培养大型语言模型，并将于明年出道发布。
从以企业为对象的饲料开始就有道理。 公司预算往往比个人订户更能容忍实验，特别是如果这些未经证实的概念能够提供轻微的商业优势。 但公司计划明年开发的第三道Axios Direct feed将会成为消费者的取景方式，所有这三种饲料看起来都类似于RSS饲料
Axios正在修改其(已经简短的)内容，以满足大赦国际的要求，但Everyone正在采取不同的做法。 包括LinkedIn创始人Reid Hoffman在内的投资者去年提供的200万美元资金
每个创始人Dan Shipper 称最常见的方式是，Every's 内容与典型文章的不同之处在于，其作者尽可能将提示分解，让读者自己测试概念。 例如，一篇关于新模型的文章包括一系列的提示，读者可以复制-复制到AI，演示模型如何回答问题和评价输入。
某些类型的文章——例如指南——还包括读者可以按下“用Claude读取”或“用ChatGPT读取”的按钮。 点击会拉起一个提示，指示AI“从一个紧凑的总结开始：一个段落被击中。 然后提议更深入一些。” agents将会挑出最相关的位子。
发布的首篇“可扩展”文章在两年前推出，读者可以查询一个聊天机，从数据库中获取更多细节。
最近，每个用户都发表了一篇关于Codex的8000个字的文章，用户可以消费更多的形式。 用户的agents可以根据数据库来裁剪新作品，一个读者可能想要一个被弹出的摘要，而另一个读者可能要求一个采访比特的短片。
“作为一个作家，你必须选择你所讲的故事的内容，”Shipper 称。 “总有一个问题，这些选择是正确的吗？或者说，这些是某一读者正确的选择吗？” 有了AI，记者不再选择。
“人们会用这个做疯狂的事情
另一个问题出现：出版商真的能靠这个赚钱吗？
Rasmus Kleis Nielsen，哥本哈根大学通讯教授，称认为，虽然agents的出版市场“正在出现”，但它仍然不成熟，“极不平衡”。 主要的问题依然存在，他称，关于价格点和AI agents未来如何与内容互动。
Axios的首席操作官Cameron和Allison Murphy对AI作为观众代理持乐观态度。 Axios的短形、结构化强的风格已经让出版商成为AI最喜爱的，“时间是爬行者的钱”,Murphy 称。 “他们不想为了找到要点而下行四分之三。 因此，这已经使我们受益。”
但AI爬行其内容是否真正有利于Axios的底线？即使读者实际上没有访问Axios主页，品牌知名度本身也可以是积极的，Nielsen 称。 与为TikTok和Instagram等社交平台提供内容的出版商不同
当一个聊天员能在银盘上给出答案时，人们只想为其他出版物所没有的信息付出代价。 在Axios Pro Deals，快速获取可以推动市场的信息。 Axios Pro Deals全程订阅每年2 499美元，而每年每台订阅每年288美元。
船夫视这288美元为人类读者的订阅费，连同他们的agents. “我也许不想每个月都读你的东西，” 但是，如果他的订阅可以包括他的agent,“我也许希望我的agent知道这一点，以便它能告诉我，‘嘿，这件事很重要。 ` ` '
Murphy 称认为Axios的起点是接受：人们已经在使用AI来吸收信息，并且在不久的将来会有更多的人这样做。
“我还试图通过思考，让它在存在上更加恐怖，人们通过社交媒体、短视频、播客获得新闻。 Murphy 新增：“这不是真正的AI作为观众，“这是帮助我们接触观众的AI工具。”
本文由 AI宝库自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
Every morning, Michelle Seo receives a morning briefing from Chattiana, her Muse artificial intelligence agent.
Chattiana’s briefing lists Seo’s agenda and to-do list, and plucks water-cooler topics from the headlines in her various newsletters along with links to the sources.
“I'm kind of challenging myself as an introvert to start more conversations,” Seo, a San Diego-based public relations consultant, tells WIRED. The newsletter, she says, gives her a sense of the daily news and options for filling an awkward silence on a Zoom call.
Seo is far from the first person to consume her news with an AI assist. In fact, the trend has become so common that some news outlets are starting to produce content that treats AI agents—not human readers—as the intended audience. This can look like anything from feeds optimized for AI to pieces structured to allow agents to create personalized articles.
“We believe that the media ecosystem is changing,” says Axios chief revenue officer Jacquelyn Cameron. ”We see this with open web deteriorating. We see that search is shrinking. We see that hyperpersonalization is surging, that LLMs are becoming more important in the way that people are consuming” their news.
Major publishers have responded to that change in a variety of ways. Many, including WIRED’s parent company Condé Nast, have signed deals to allow AI platforms to surface their content. Outlets are grappling with “generative engine optimization,” or GEO, strategies to ensure articles appear in responses to AI prompts. Last year, AIOSEO, a SEO plug-in for WordPress sites, launched a feature that provides websites with LLM.txt files, which help AI discover and interpret sites’ content.
Others have taken a more defensive posture: The New York Times sued OpenAI and Microsoft in 2023 for copyright infringement, alleging that the companies illegally trained models on reporting. That case is still ongoing.
What Axios and a handful of others are trying, though, represents a more foundational shift in how the media operates—and who its stories are for.
“We have always said,” Cameron says, “that we want to be where the audience is.”
At the Digiday Publishing Summit in September, Axios announced the upcoming launch of Axios Direct: feeds designed for AI agents.
“We do believe that a significant portion of news consumption will move into AI systems, LLMs, and devices,” Cameron says. She describes the feeds as a more efficient way for agents to access Axios content, cutting back on narrative to prioritize structured data—more similar to a Bloomberg terminal than a series of articles.
The two initial Direct feeds are aimed at corporate clients. The first, which launched this fall, gives the AI agents of Axios Pro Deals subscribers access to merger-and-acquisition content. The second feed will act as a source to train in-house large language models, and will launch next year.
Starting with feeds aimed at businesses makes sense. Corporate budgets tend to have more tolerance than individual subscribers for experiments, especially if these unproven concepts could offer even a slight business advantage. But the third Axios Direct feed, which the company plans to develop next year, will be consumer-facing—a way for individual subscribers to have Axios’s reporting sent directly to their agent. All three feeds will look similar to RSS feeds—not aesthetically pleasing, as they aren’t intended for the human eye, but instead taking the form of standardized lines of text.
While Axios is trimming its (already brief) content to satisfy AI, Every is taking a different approach. The six-year-old tech media and software company, which announced a $2 million funding round from investors including LinkedIn founder Reid Hoffman last year, expects its subscribers to treat AI as almost an extension of themselves.
Every’s founder Dan Shipper says the most common way Every’s content differs from a typical article is that its writers include prompts in pieces whenever possible, allowing readers to test concepts themselves. An article about a new model, for example, includes a series of prompts the reader can copy-paste into AI, demonstrating how the model answers questions and evaluates input.
Certain types of articles—such as guides—also include buttons that readers can press to “Read With Claude” or “Read With ChatGPT.” Clicking pulls up a prompt, instructing AI to “Start with a tight summary: one paragraph, bulleted. Then offer to go deeper.” Writers pack stories with details without worrying about losing readers’ attention, knowing agents will pick out the most relevant bits.
Two years ago, the outlet launched its first “extendable” article: a long-form feature accompanied by a database of reporting, from interview recordings to news articles to YouTube videos. Readers could query a chatbot, which would fetch additional details from the database.
Recently, Every published a 8,000-word article about Codex that subscribers can consume in even more forms. Drawing from the database, subscribers’ agents can tailor a new piece—be it an article, podcast, or video—to suit their interests. One reader might want a bulleted summary, while another could request a short film of interview bits.
“As a writer, you have to make choices about what goes into the story you're telling,” Shipper says. “And there's always a question about, are those the right choices? Or, are those the right choices for a particular reader?” With AI, journalists no longer choose.
“People are gonna do crazy, crazy stuff with this,” Shipper adds.
As outlets eye AI agents as a new audience, another question looms: Can publishers actually make money off of this?
Rasmus Kleis Nielsen, a professor of communication at the University of Copenhagen, says that while the market of publishing for agents is “emerging,” it remains immature and “extremely uneven.” Major questions remain, he says, about price points and how AI agents will interact with content in the future.
Cameron and Allison Murphy, Axios’s chief operating officer, are optimistic about AI as an audience proxy. According to the executives, Axios’s short-form, highly structured style has already made the publisher a favorite for AI to pull from, when responding to prompts. “Time is money for crawlers,” Murphy says. “They don't want to have to go three quarters down the page to find the main point. So, that's something that's already benefiting us.”
But does AI crawling its content actually benefit Axios’ bottom line? Even if readers don’t actually visit the Axios homepage, the brand visibility in and of itself can be positive, Nielsen says. It’s not unlike publishers making content for social platforms like TikTok and Instagram that rarely bring viewers back to their websites.
Publications in general are grappling with how difficult it has become to monetize certain types of content when a chatbot can offer up answers on a silver platter. People only want to pay for information that other publications—and LLMs—don’t have. At Every, that means in-the-weeds guidance on AI and how to use it; at Axios Pro Deals, it’s speedy access to information that could move the market. An all-access Axios Pro Deals subscription costs $2,499 a year, while an annual Every subscription costs $288.
Shipper sees that $288 as a subscription for a human reader, along with their agents. “I may not want to read all of your stuff every month,” Shipper says. But if his subscription can include his agent, “I may want my agent to know it so that it can tell me, ‘Hey, this thing is important.’”
Murphy says that Axios’s starting point is one of acceptance: People are already using AI to absorb information, and that more people will be doing so in the near future.
“I also try to make it a little less existentially terrifying by thinking, this isn't the first time this has happened in media,” Murphy says. People get their news via social media, via short-form video, via podcasts. “It isn't really AI as the audience,” Murphy adds. “It's AI as a tool that helps us reach our audience.”
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