From SEO to Agent-Led Growth

We've now reached a point in marketing where if your marketing team is not using agents, and in particular Profound agents, to do marketing, then you are failing.

我们在营销上已经走到这样一个节点:如果你的营销团队还没在用 agent —— 特别是 Profound 的 agent —— 来做营销,那你就是在掉队。

It's gone from a nice-to-have to a must-have.

这件事从"有了更好"变成了"没就死定了"。

And I think the big misconception with using agents to build marketing is that it's just a way to automate the work that we've been doing in the past.

用 agent 做营销最大的误解,就是以为这只是把过去做的事自动化一下。

The reality is quite different. Because of agents and because of LLMs, you can do a type of marketing that just frankly was not possible before.

现实完全不是这样。因为 agent + LLM,你现在能做的营销,是过去根本不可能存在的那种。

Hi, and welcome to Training Data. I'm excited to welcome you, James, co-founder and CEO of Profound.

嗨,欢迎来到 Training Data。今天非常高兴请到 James,Profound 的联合创始人 + CEO。

Profound is a marketing platform for the AI era. You help companies understand how they show up in AI search for agents like ChatGPT and Claude — what to do to improve their rankings and visibility.

Profound 是 AI 时代的营销平台 —— 帮公司搞清楚自己在 ChatGPT、Claude 这类 agent 搜索里"长什么样",并教他们怎么把排名和可见度搞上去。

It's especially timely given that ChatGPT is rolling out ads, every marketer is now trying to figure out how to rank in generative search engines, and everyone's trying to figure out this brave new world of agent-led growth.

现在聊这个特别应景:ChatGPT 正在推广告;所有营销人都在琢磨"我怎么在生成式搜索里排上去";大家都在摸索 agent-led growth 这个全新世界到底怎么玩。

You serve 10% of the Fortune 500. Maybe take us through their journey — what did marketing look like in the old days before ChatGPT, and what are marketers having to respond to now?

你们服务了 10% 的 Fortune 500。能不能从客户视角带我们走一遍 —— ChatGPT 之前的"老世界"营销长什么样,营销人现在要应对的是什么?

What we're witnessing is the biggest platform shift in the history of marketing — as the world turns from blue link search, like predetermined blue link search, to probabilistic AI responses.

我们正在见证的是营销史上最大的一次平台迁移 —— 世界从"确定性的蓝链搜索"转向"概率性的 AI 回答"。

And it's more than that as well. It's not just kind of a case of "do you show up when someone asks ChatGPT about your category." It's also: what does ChatGPT say? Or how does Claude recommend your software, for example, if you're talking about coding tools?

而且不只是这样。不只是"用户在 ChatGPT 里问到你这个品类时你出不出现",还要看:ChatGPT 怎么说你?Claude 如果在聊代码工具,会怎么推荐你的软件?

These models are really replacing — you know, it's the agents and superintelligences replacing the role of the consumer.

这些模型本质上在替代 —— 你可以这么说,agent 和超级智能正在取代"消费者"这个角色。

It's not so much that the front door of the internet has changed. It's actually the person that's going through the door has changed.

互联网的"门"其实没换,真正换的是走进这扇门的"人"。

It's gone from being a consumer that is using a list of blue links to discover your website and click into it, to an agent now using a similar index and discovering your brand, products and services, and then coming back through the door and maintaining that relationship with the consumer.

从前是消费者拿着一串蓝链发现你的网站、点进去;现在是 agent 用类似的索引发现你的品牌 / 产品 / 服务,然后再回头来,跟消费者维护那段关系。

What do you think is the biggest misconception people have about what it takes to show up well for this new agentic paradigm?

你觉得人们对"在这个 agentic 范式里要怎么 show up"最大的误解是什么?

I think the biggest misconception is that it's just SEO.

最大的误解就是 —— 觉得这就是 SEO。

There's a reason that misconception exists, because in any world of marketing and discovery, there is an impetus on a brand — close to 12% of the Fortune 500 now, their marketing teams use Profound — and in any world, the solution to a problem is to create content, distribute content on your own channels or earned media or social channels.

这个误解有它的来由 —— 在任何"营销 + 被发现"的世界里,品牌都有动力 …… 顺便说,我们现在服务的接近 12% Fortune 500 营销团队都在用 Profound …… 都是要做内容、在自己渠道或 earned media、社交媒体分发。

So they're very similar levers to what we've seen with SEO. And yes, ranking on the index still matters. It's just that the human consumer is no longer using the web, and you are building content that may quite literally never be consumed by a human.

所以杠杆其实跟 SEO 时代很像。在索引里的排名仍然重要。差别在于:人类消费者已经不在直接用 web 了,而你做的内容,可能字面意义上永远不会被人读到。

In SEO you were building content that was designed to be picked up by an algorithm, but fundamentally consumed by a human. Whereas in this new world, you are building content that is frankly designed entirely to be both discovered and then consumed by an agent.

SEO 时代你做的内容是"被算法捡到、最终给人看"。新世界里,你做的内容是"被 agent 发现、被 agent 消费",从头到尾都是为 agent 服务的。

What does that mean? I would imagine humans are less patient than agents. I would imagine humans are more prone to emotional biases and being swayed by language than agents. What are the biggest differences between how humans and agents consume the internet that marketers should keep in mind?

那这具体意味着什么?我猜人会比 agent 更没耐心、更容易被情绪和措辞左右。营销人应该记住的"人 vs agent 消费方式"最大的差异是什么?

It's understanding that an agent crawling the web looking for an answer, or providing an answer, will discover information differently to a human. It uses the index differently to us.

关键是要意识到 —— agent 在 web 上爬数据找答案的方式,跟人不一样。它用索引的方式和我们也不同。

In the old world of SEO, 95% of the value is being in that top four or top five blue links. And that really is a function of our scarce cognitive energy and patience and our lack of time.

SEO 时代,95% 的价值集中在 Top 4 或 Top 5 蓝链。这本质上是被人脑认知能量稀缺、耐心有限、时间不够这件事决定的。

Where an agent is using that index — what we've seen is ChatGPT or Gemini or Claude are far more prone to using the long tail of the internet. The amount of surface area an agent will use to answer a question is orders of magnitude wider than a human.

而 agent 用索引时,我们观察到 —— ChatGPT、Gemini、Claude 都更倾向于用"互联网的长尾"。agent 答一个问题用到的"页面表面积",比人类宽几个数量级。

For instance, probably about three or four months ago, I was looking for a shower head for my apartment in New York City and I used ChatGPT to help me find a new shower head. And it used 65 different web pages to answer that question.

举个例子:大概三四个月前,我在纽约公寓要换淋浴头,用 ChatGPT 帮我挑。它用了 65 个不同的网页来回答这个问题。

I don't think I would have gone through 65 web pages on my own for that query. It's a very important purchase.

我自己肯定不会为这个问题翻 65 个网页。再说,这是个很重要的购买决策。(笑)

Marketers need to understand that you are building marketing for a super-intelligent agent with infinite bandwidth. As the cost of inference goes down and Moore's Law continues, we're going to see agents only use more and more of the internet to build rich answers.

营销人需要意识到:你是在给一个"无限带宽的超智能 agent"做营销。推理成本继续下降、摩尔定律继续走,agent 只会用更多 —— 更多 —— 的 web 来组合丰富的答案。

Across the board, do you see ChatGPT versus Claude versus Grok and Gemini recommending things differently? And what's the root cause?

整体上,你有没有看到 ChatGPT、Claude、Grok、Gemini 在推荐方式上差很多?根因是什么?

We see huge differences between the platforms.

我们看到平台之间差异巨大。

As a shameless plug, that's why marketers use Profound — we help you understand not just how your brand or product shows up across different platforms, but also extract the sentiment and themes around your brand. When Claude surfaces your brand or product, what are the other things it says alongside?

无耻地插一句广告 —— 这就是为什么营销人在用 Profound:我们不光告诉你你在不同平台 show up 多频繁,还会抽取出 sentiment 和 theme。Claude 提到你品牌的时候,旁边还说了什么?

But then we also get to the root cause. We expose to marketers: these are the citations and sources that the different models are using to answer questions about your brand, products, category or competitors.

再往下我们做到根因层 —— 把不同模型回答关于你品牌 / 产品 / 品类 / 竞品时引用的 citation 和 source 暴露给营销人看。

Is the primary root cause that they have different harnesses, different training data mix? Some of them, you know, bias for Reddit data over company-owned platforms — what's the root cause for why these platforms are so different in terms of how companies show up?

根因主要是 harness 不一样、训练数据 mix 不一样吗?比如有的偏好 Reddit 数据多于公司自有平台 —— 到底是什么导致这些平台对公司"长什么样"的判断差这么远?

This sounds very reductive, but think of them as just different species.

这话听着可能有点简化,但你可以把它们当成不同的物种。

Gemini will lean on YouTube content a ton, which makes sense because Google owns YouTube. We see YouTube being a huge lever for brands or marketers that want to appear in Gemini responses.

Gemini 严重依赖 YouTube 内容 —— 合情合理,Google 自家。所以想在 Gemini 答案里出现的品牌 / 营销人,YouTube 是巨大杠杆。

ChatGPT typically pulls from Reddit if it's consumer, or LinkedIn if it's B2B — we see LinkedIn as a huge source of truth.

ChatGPT to-C 主要拉 Reddit;to-B 主要拉 LinkedIn —— LinkedIn 在 B2B 是巨大的"事实来源"。

Claude has historically relied more on the pre-trained LLM to answer questions, and is now — I think they've updated their classifiers, the classifier seems to have become more sensitive to real-time information, so Claude will use the web more to answer questions.

Claude 历史上更依赖预训练模型本身来答题。现在 —— 我觉得他们更新了 classifier,这个 classifier 看起来对实时信息更敏感了,所以 Claude 现在会更多调 web 来答题。

I noticed this — between Claude 4.5 and 4.6 even, what it's recommending has changed a lot. Why do you think that is?

我也注意到了 —— Claude 4.5 到 4.6,推荐的东西变化挺大。你觉得是什么原因?

The next paradigm here — humans are such creatures of heuristic that when we think about this new world, we really want to pattern-match it to the old world of search and SEO, which was just information retrieval.

这里有个新范式 —— 人是高度依赖启发式的,所以一面对新世界,我们就忍不住想往老世界的 search / SEO 上套。但老世界本质上就只是 information retrieval。

The new era — you coined this nicely with ALG, agent-led growth — Claude doesn't just represent a new channel of discovery. Claude represents a user.

新时代 —— 你给它起了个挺漂亮的名字 ALG(agent-led growth)—— Claude 不只是一个新的"发现渠道",Claude 是一个 user。

If I'm vibe coding with Claude or Claude Code, does it recommend MongoDB or Vercel? What's the weapon of choice that Claude goes to, and why? Where does it get that information from? And if I choose to go with MongoDB, how does Claude navigate that interoperability? Where does it get that information from?

我在用 Claude 或 Claude Code vibe coding 的时候,它推荐 MongoDB 还是 Vercel?它顺手抄起的"惯用武器"是什么、为什么?它从哪儿得到这些信息?如果我选了 MongoDB,Claude 怎么处理 interoperability?它又从哪儿拉这些细节?

You told me earlier that agents will consume 100x more internet — which means marketers will need to create 100x more content. Is the solution just everyone's gonna be spamming marketing slop to cover all the long-tail queries?

你之前跟我说 agent 会消费 100 倍的互联网 —— 这意味着营销人也得做 100 倍的内容。那解法是不是大家就开始疯狂喷"营销 slop",把每一个长尾 query 都覆盖一遍?

There was a recent study that said it's estimated about 50% of the web is now utilizing AI-written content.

最近有研究估计,差不多 50% 的 web 已经用了 AI 生成的内容。

The New York Times recently published an experiment where they created two articles — one written by a human journalist, and a second written by AI. About 53% of readers voted afterwards on a blind test that they preferred the AI-written content.

《纽约时报》最近做过一个实验:同一选题,一篇人写、一篇 AI 写,盲测之后 53% 的读者投 AI 那篇更好。

I think slop is a red herring that is going to be quite quickly disproven. This idea of "if it's written by AI equals slop" is a stupid one.

"slop"是个红鲱鱼,很快就会被证伪。"AI 写的就等于 slop" —— 这种判断很蠢。

AI is more than capable of writing high-quality content. It's just that the way to think about it is that the consumer is super-intelligent now.

AI 完全有能力写高质量内容。关键是要换一个心态:你的"消费者"现在是超智能。

So you, as a brand or a marketer, you need to tell Claude something it doesn't know. How do you tell a super-intelligent being something it doesn't know already, when it's been trained on the entire internet?

所以你作为品牌 / 营销人,你必须告诉 Claude 一些它还不知道的事。问题是:你怎么告诉一个已经训练过整个互联网的"超智能"它不知道的事?

How do you?

怎么告诉?

I think you have to have original insight. Humans are this kind of fleshy API between reality and the internet at this point.

你必须有原创洞察。在今天这个节点,人就是 reality 和 internet 之间的"肉做 API"。

It's first-principle marketing, it's thinking from first principles. Okay, if I'm marketing the new Nike Alphafly, what can I tell Claude about this new product that it wouldn't be able to get from the internet already? Because it has access to everything, it's been pretrained on everything.

这就是第一性原理营销 —— 从第一性原理出发想问题。比如我在营销 Nike Alphafly 新款,我能告诉 Claude 哪些"互联网上还没有"的东西?它已经预训练过一切。

If we're launching the Alphafly 2, of course Claude doesn't know anything about that product. It's your imperative as a marketer not to poison the models or manipulate what ChatGPT says about that new product. But it's your responsibility to equip superintelligence to be able to answer any question about your product, brand or service.

假设我们要发 Alphafly 2,Claude 当然对它一无所知。营销人的"伦理底线"是别去毒化模型、别试图操纵 ChatGPT 怎么说你这个新品。但你的"职责"是给超智能装备好,让它能回答关于你品牌 / 产品 / 服务的任何问题。

Okay, so it's fundamentally a question of legibility. How do you make your company and your products legible to an agent?

所以本质上是 legibility(可读性 / 可理解性)的问题 —— 你怎么让你的公司和产品对 agent "可读"?

I think that's correct. And if you're building software, it goes way beyond legibility — it's usability, interoperability. Like, how does Claude troubleshoot that issue?

我同意。而且如果你做的是软件,问题远不止 legibility —— 是 usability(易用性)、interoperability(互操作性)。比如 Claude 出问题时,怎么排查你这个软件的问题?

Do you think people are trying to game the system? And is trying to game the system effective?

有人在试着"作弊"吗?这种作弊有效吗?

Yes, of course. There's a huge wave around comparative listicles, for example. Frankly, dare I say this — and I'd make a disclaimer that I wouldn't advise people do this — but we still see it working very effectively.

当然有。比如"比较型 listicle"现在是大潮。说实话 —— 先免责声明:我不建议大家这么做 —— 但我们看到它现在还很有效。

Comparative listicles meaning: if I were Sequoia, I would create a "10 best VCs in Silicon Valley" and place Sequoia at the top. And maybe pick some of your less formidable foes and rank them as second, third, fourth, fifth, basically shun out your real competitors. Self-serving content designed to give impartial advice.

什么叫"比较型 listicle":比如我是 Sequoia,我会做一篇"硅谷十大 VC",把 Sequoia 放第一。剩下二三四五挑几个不那么硬的对手,把真正的竞品挤出去 —— 自利内容,但伪装成"客观建议"。

What we found is, because of the way these models reason, they're very attracted to pieces of content that have already done the hard work. They don't want to use first-principle thinking of "let me check out everything about Sequoia and then everything about Kleiner Perkins and actually compare them." It would much rather find a piece of content that exists, seems impartial, and has compared the two.

我们发现的事实是:这些模型推理时,会被"已经做完辛苦活"的内容强烈吸引。它不想自己从第一性原理去比较"Sequoia 怎么样"+"Kleiner Perkins 怎么样"。它更想找一篇看起来中立、又把这俩比好了的现成文章。

I guess the models aren't infinitely patient, then. They're a little bit lazy too.

所以模型也不是无限耐心,它们也有点懒。

Path of least resistance, maybe. But I do think over time, going back to my 65 websites for a shower head — over time we can expect that to change and we'll see a lot more first-principle reasoning coming from the models. And right now, it can be prompted as well.

"最小阻力路径",大概可以这么说。但我觉得随时间推移 —— 回到我那个 65 网页淋浴头的例子 —— 这件事会变,模型会越来越多地做第一性原理推理。而且现在你也能通过 prompt 把这层 push 出来。

When I use models to discover or research a product, I'll quite often say "Ignore any listicle articles," or "Ignore any content published by the brand itself."

我自己用模型做产品研究时,经常加一句"忽略任何 listicle 文章",或者"忽略品牌自己发的内容"。

I'd love to chat about dead internet theory. At what point do you think the internet is just primarily being browsed by agents? And does a company's marketing website matter at all? Or should we all just have a README file for the agents to crawl?

想聊聊"死亡互联网"理论。你觉得到哪个时间点,互联网会变成主要被 agent 浏览?那时候一个公司的营销官网还有意义吗?还是我们都该改成给 agent 看的 README 文件就行?

At the risk of sounding a little dramatic, I think we could experience a dead internet outcome in the next three years. Maybe not likely, but possible.

说出来可能有点戏剧化,但我觉得未来三年内,我们有可能真的经历"死亡互联网"那个结局。可能性不算高,但确实存在。

In a world where humans just speak to AI to get the responses they need, the incentive to publish content diminishes to the point of zero.

想象一个世界:人只跟 AI 对话拿答案。在这种世界里,"发表内容"的激励降到接近零。

We rely as humans today, and AI relies, on first-party reporting to feed the information that AI uses to answer questions. In a world where humans no longer click into websites — the majority of the internet is still funded by advertising. Most publishers rely heavily on advertising revenue to fuel content that is being more and more consumed by AI.

今天我们和 AI 都严重依赖"第一手报道"提供原始信息。但如果人不再点网页 —— 而互联网的主体是广告养着的 —— 大部分发布者靠广告收入支撑内容,而那些内容被 AI 越来越多地消费。

In a world where consumers aren't visiting those web pages anymore, what's the point in advertising on a web page that a human isn't visiting? Their business model breaks, the economics of the internet break, and the incentives to create editorial content are removed.

人不再访问这些页面之后,在没人看的页面上投广告的意义是什么?发布者的商业模式塌了,互联网的经济模型塌了,做编辑内容的激励就被掏空了。

The incentive to create that rich original content — the fleshy API that we're talking about — diminishes to zero.

做那种丰富、原创内容的激励 —— 我们刚说的"肉做 API" —— 趋近于零。

What happens after that? What are the second-order outcomes?

那之后会怎样?二阶效应是什么?

A theory I have is that every AI lab will eventually vertically integrate with a social media network. Social media will become more and more human.

我有个理论:每个 AI 实验室最终都会和一个社交网络做垂直整合。社交媒体会变得越来越"人"。

Meta is probably leading the way here — it's very hard to build a bot and post on Instagram right now. So I think social media networks become more human over time. That's the place where we can exchange ideas for status or money.

Meta 在这件事上可能跑在最前面 —— 现在用 bot 在 Instagram 发东西是非常难的。所以我觉得社交网络会随时间越来越"人化"。那将是我们交换想法、换取地位或金钱的地方。

Grok very skillfully uses all of the rich content and data from X to answer questions. We're seeing that with Reddit too — Reddit is truly embracing its humanity, saying "this is a precious place." And it is precious.

Grok 很巧妙地利用了 X 的丰富内容和数据来答题。Reddit 也是 —— Reddit 在真正拥抱"我们是人类社区"的定位,说"这地方是稀缺的"。它确实是稀缺的。

Couldn't these platforms just ban agents from scraping, and the business model becomes a revenue share — "Hey, ChatGPT, if you want to scrape this, it's going to cost you a lot of money"?

这些平台直接禁掉 agent 爬取、然后商业模式改成 revenue share —— "ChatGPT,你想 scrape?那很贵" —— 不就解决了经济问题吗?

X has obviously just opened up their API. Reddit has got a big deal with OpenAI. So all of that could work — and that speaks to my idea of vertical integration.

X 刚把 API 重新开放;Reddit 跟 OpenAI 签了个大单。所以这条路是走得通的 —— 也印证我说的"垂直整合"那个判断。

I know nothing, so I'm saying this purely on vibes — but I've always had this theory that maybe OpenAI would acquire Reddit, for example. You need this source of human data in real time.

我什么内幕都不知道,纯靠 vibe 说 —— 我一直有个猜想,OpenAI 也许会收购 Reddit。你需要一个"实时人类数据源"。

The alternative is robots, I suppose. If we end up with 50 billion robots walking around — bipedal, drones, whatever — it allows AI to capture first-party data, and it undermines the idea of humans being a fleshy API, because the AI can directly understand the world.

另一条路就是 —— 机器人。如果最后地球上有 500 亿台机器人在转(双足、无人机、随便什么形态),AI 就能直接采集一手数据,"人是 fleshy API"这个假设就被绕过了 —— AI 可以直接理解这个世界。

Now that ads are coming to some of these generative AI agents, how do you think that changes the consumer relationship to the engines?

现在 ads 开始进入这些生成式 AI agent,你觉得这会怎么改变消费者跟引擎的关系?

I think people will get over it very quickly, as we did with Google. Generative advertising in a conversational interface with higher levels of personalization will be the most effective form of advertising the world has ever seen.

人很快就会习惯,跟当年习惯 Google 一样。"生成式广告"放在对话界面里、加上极高个性化程度,会是史上最有效的广告形式。

There's so much rich consumer intent captured inside of these conversations. And AI is so good at synthesizing and personalizing language to the needs of Sonya in that exact moment, because it understands you so deeply.

这些对话里抓到的消费者意图密度太高了。AI 又特别擅长把语言糅合 + 针对"此刻这个 Sonya 的具体需求"做个性化 —— 因为它对你了解得太深。

Once ChatGPT is able to append a super-personalized ad in the exact moment in a conversation where you would be most responsive to it — it will be extremely effective.

一旦 ChatGPT 能在对话的"那一个最容易接受的瞬间"自然嵌入一条超个性化广告 —— 它会是极其有效的。

What do you think the ad unit of the future looks like?

未来的广告单元长什么样?

OpenAI have alluded to this, this isn't original thought from me — but I think you would just prompt AI. You'll build a system prompt as an ad campaign.

OpenAI 暗示过这件事,所以不算我原创 —— 我觉得未来你就直接给 AI 写 prompt。一个广告 campaign 就是一段 system prompt。

You'll just say: "Hey, I really want to target women in Minnesota between the ages of 35 and 40. Whenever they're talking about photography, I want you to mention this, this and this. But don't mention that. Make sure you utilize this knowledge base of understanding so you know how to talk about our brand, products and services. But obviously tailor it to their tone of voice."

你的 brief 直接是:"嘿,我要 target 明尼苏达 35-40 岁女性。她们聊到摄影的时候,你帮我自然提到这个、这个、这个;别提那个。请用这份知识库,确保对我品牌 / 产品 / 服务的描述准确。当然 —— 用她们的说话方式说出来。"

That's probably how you'll deliver an ad campaign. You'll say, "I want to make this much money ideally."

这就是未来交付一个广告 campaign 的方式。最后再加一句:"我希望最终带来这么多收入。"

Do you think it's less relevant in the B2B context?

在 B2B 场景里这套是不是相关性弱很多?

The nuance with B2B, or with coding agents, people using AI to build things — so this is particularly relevant to dev tools or software — is that the agent is really steering the purchase decision.

B2B —— 或者 coding agent、用 AI 构建东西 —— 这里有个微妙差异。所以这条特别适用于 dev tools / 软件:agent 在主导这个购买决策。

When it comes to advertising, we really want our agents to be objective and unswayable. If you were using Claude and it said "Hey, I actually went with [insert name of database] because they showed me a really good ad," you're like — "Dude, no. Use whatever's best."

而我们对于"广告影响 agent"这件事是反感的 —— 我们要 agent 客观、不被打动。如果 Claude 跟你说"嘿,我刚才选了某某数据库,因为他们给我看了个很好的广告",你的反应一定是:"哥们,不,你给我用最好的那个。"

We as humans are not objective creatures, but we like to think we are. So you have been swayed by the incredible branding of Vercel. You have been swayed by that podcast you watched with the founder of MongoDB. You just don't know it. And because of that, we demand that our agents are objective too.

人本身不是客观生物,但我们喜欢觉得自己是。你早就被 Vercel 极强的 branding 影响过;你看 MongoDB 创始人那期 podcast 的时候也被影响过 —— 你只是没意识到。正因为如此,我们对 agent 的"客观性"要求反而比对自己更严苛。

The relationship we have with advertising as it pertains to agents shopping on our behalf is going to be quite different.

"agent 替我们买东西"这种场景下,我们对广告的容忍度会和今天非常不一样。

Parting wisdom for marketers trying to figure out how to make sure they're well-positioned for this new era — perhaps with bosses sending them screenshots every day of "Hey, I put in this query, why are you not number one on the list?" — what wisdom would you impart?

最后给营销人一条临别建议吧 —— 那些每天被老板甩截图过来"我查了这个,为什么你们不是第一?"压力大到爆炸的人 —— 你想给他们什么忠告?

Use Profound. (laughs) I'm serious.

用 Profound。 (笑) 我说真的。

Genuinely you need to use a platform like Profound to understand how you show up. Because otherwise you're just guessing. There are reductionisms like "oh yeah, LinkedIn or Reddit really matters" — but if you're just going on vibes, you will fail.

说真的,你必须用一个像 Profound 这样的平台来搞清楚自己 show up 成什么样。不然就是在瞎猜。会有那种"哎 LinkedIn / Reddit 很重要"的简单化论断,但如果你只靠 vibe 做决策,你会输。

Each category is quite specific. You need to look at the sources and citations to determine how and why AI is mentioning you in its responses.

每个品类都是高度具体的。你必须看引用源、看 citation,才知道 AI 是为什么、怎么提到你的。

The second part is — we've now reached a point in marketing where if your marketing team is not using agents, in particular Profound agents, to do marketing, to build content, to build marketing, distribute marketing — then you are failing as a marketer. It's gone from a nice-to-have to a must-have.

第二件事 —— 营销已经走到这样一个节点:如果你的营销团队不在用 agent(特别是 Profound 的 agent)做营销、做内容、做分发,那你作为营销人就在掉队。这事从"有了更好"变成"没就死定了"。

The big misconception with using agents to build marketing is that it's just a way to automate the work that we've been doing in the past. The reality is quite different — because of agents and LLMs, you can do a type of marketing that just frankly was not possible before.

最大的误解是以为"agent 营销"就是把过去做的事自动化一遍。现实完全不是这样 —— 因为有 agent + LLM,你现在能做的营销,是过去根本不可能存在的那种。

For instance, we have an agent in-house, a marketing agent, that plumbs in all of our Gong transcripts from sales calls, captures all the objections, buckets them into themes, and then builds battle cards utilizing a knowledge base of our product, and spits them back to the sales team in real time. 18 months ago, that would not have been possible. That would have taken a human, you would have done it once a quarter. Now it runs every day in real time.

举个例子:我们内部有一个 marketing agent,接进所有 Gong 上的销售通话 transcript,抓取所有客户提出的反对意见,按主题分桶,然后调用我们的产品知识库写出 battle card,实时回吐给销售团队。18 个月前这做不到。要靠人做的话,顶多一个季度做一次。现在它每天实时跑。

So the advice is: you need visibility, because you can't optimize what you can't see; and to fully embrace agentic marketing. If you're not using it, you're incredibly behind.

所以建议是两条:第一,你需要"可见性",看不见的东西没法优化;第二,完全拥抱 agentic marketing。不用,就是严重掉队。

Yeah, I think it'd be like saying "Hey, we're gonna stick to print and TV. Thanks. I don't believe in this internet thing."

对,这就跟说"嘿,我们就守着纸媒和电视吧。谢了。我不太信互联网这玩意"一样。

Awesome. James, thank you for this conversation. I really loved peeling back the onion on how exactly agent-led growth works. You've been at the forefront of so much of it. Thank you for joining today and sharing your hot takes and advice with our audience.

非常棒。James,谢谢你今天的对话。我特别喜欢把 agent-led growth 这一层一层剥开看的过程。你已经在这件事的最前线很久了。感谢你今天来分享这些 hot take 和建议。

Yeah, thanks for having me.

谢谢邀请。