Episode 443AIContent StrategyMarketing Operations

Why more AI content is not the same as more pipeline with Amanda Landsaw

Amanda Landsaw, CMO at Endeavor B2B (a marketing, media, and intelligence organization spanning 90+ brands across 16 verticals), argues that increased supply and volume of AI content does not increase relevance, differentiation, or trust, because speed is not strategy. She frames the work as 'crap input equals crap output' and explains that getting useful AI work back requires an almost intimate relationship with the model, layered prompts that peel back the onion, and a willingness to feed the system your own talks, papers, blogs, and podcasts so it can ghostwrite in your voice without losing the human review layer. Amanda also walks through how buyer behavior is shifting as people use ChatGPT and Claude as their new search, why personalization is really just relevancy in disguise (anchored in privacy-first behavioral and intent data), and how to give sales reps smarter openings so discovery starts a step or two ahead of ground zero. She makes the case that the one thing AI cannot replicate is point of view, which is why the human element, tone, and bias have to stay in the loop. The takeaway: produce less noise, sharpen the input, keep the human review, and design content so AI surfaces it on the consumer side too.

Amanda Landsaw

Amanda Landsaw

CMO, Endeavor B2B

19 min

Key Takeaways

  • 1Increased supply and volume of AI content does not increase relevance, differentiation, or trust — speed is not strategy, so before you produce more, ask whether the next piece will reduce risk, sharpen a decision, or actually move pipeline.
  • 2Treat AI as a conversation, not a one-and-done prompt: build an almost intimate working relationship with the model, layer prompts to peel back the onion, and accept that crap input equals crap output every single time.
  • 3Buyers are using ChatGPT and Claude as their new search and asking AI to summarize email threads, PDFs, and decks for them, so design every asset (including podcasts and video) so it is easy to digest and easy for AI to pick up and surface.
  • 4Personalization is really relevancy in disguise — use behavioral and intent data with a privacy-first mindset to start sales conversations a step or two ahead of ground zero, instead of opening with 'we offer 1,200 products, where do you want to start?'
  • 5Point of view is the one thing AI cannot replicate, so train the model on your own talks, papers, blogs, and podcasts to ghostwrite in your voice, then keep a human review layer to catch hallucinations and protect the bias that makes the content yours.

About this episode

Speed is not strategy. In this episode of Content Amplified, Amanda Landsaw, CMO at Endeavor B2B (a marketing, media, and intelligence organization with 90+ brands across 16 verticals), explains why pumping out more AI-generated content does not translate into relevance, differentiation, or trust. Amanda argues that 'crap input equals crap output' and walks through what it actually takes to use AI well: developing an almost intimate relationship with the model, layering prompts to peel back the onion, and treating point of view as the one thing AI cannot replicate. She also covers how buyer behavior is shifting as people use ChatGPT and Claude as their new search, why personalization is really just relevancy in disguise, and how to train AI on your own talks, papers, and podcasts so it can ghostwrite in your voice without losing the human review layer. If you are wrestling with how to scale content without drowning in noise, this conversation gives you a sharper way to think about the work.

Topics covered

  • Speed is not strategy in AI content production
  • Crap input equals crap output and intimate AI prompting
  • ChatGPT and Claude as the new search layer
  • Personalization as relevancy and privacy-first sales openings
  • Training AI on your own voice with human review

Notable quotes

I think that increased supply and volume does not increase relevance or differentiation or trust. Speed is not strategy.

Amanda Landsaw(0:02)

If you're putting in, pardon my French, crap input into it, it's gonna give you crap output.

Amanda Landsaw(4:19)

You have to have almost like an intimate relationship with that AI to be able to have a conversation and have an ongoing conversation because the prompt isn't one and done.

Amanda Landsaw(4:19)

AI can help you produce thought leadership all day long. What it can't do is really provide you with like, all right, Benjamin's point of view and expertise.

Amanda Landsaw(13:19)

Resources mentioned

  • Framework

    Crap In, Crap Out: The Intimate Prompting Loop

    Treat every AI session as a layered conversation, not a single request. Start by giving the model the same depth of context you would give a senior collaborator: your audience, the emotion you want them to feel, the objection you are trying to overcome, and your point of view on the topic. Then keep peeling back the onion with follow-up prompts that go to the next level instead of accepting the first draft. The quality of the output is bounded by the quality and honesty of the input, so the work is in the prompting, not in the asking.

  • Playbook

    Train AI on Your Own Voice (with a Human Review Gate)

    Feed the model your own corpus: every talk you have given over the last three years, every paper you have written, every blog you have published, and every podcast you have participated in. Instruct it to ghostwrite in your tone using that source material, then route every output through a human review step before publication. The review catches hallucinations and preserves the nuance and bias the model cannot fully learn, while the corpus does the heavy lifting on voice. This is how individual operators and small teams get leverage without sounding generic.

  • Strategy

    Privacy-First Personalization as Relevancy

    Stop equating personalization with merge tags. Real personalization is relevancy: do you know enough about what the buyer cares about to start the conversation a step or two ahead of ground zero, without sounding creepy. Use the behavioral and intent data your stack already captures (with a privacy-first lens) to surface the specific section of your offering that maps to the prospect's role and recent activity, and hand that context to the rep. The opening shifts from 'we offer 1,200 products, where do you want to start?' to 'we saw you are in the safety space and looked at our content syndication section, want to dig into that?'

Amanda Landsaw (00:02) I think that increased supply and volume does not increase relevance or differentiation or trust. Speed is not strategy. And so at the end of the day, yes, you can produce more content. You can produce it very fast, but it doesn't really increase the demand for it, right? It kind of creates noise. Benjamin Ard (00:48) Welcome back to another episode of Content Amplified. Today I'm joined by Amanda. Amanda, welcome to the show. Amanda Landsaw (00:54) Thank you for having me, excited to be here. Benjamin Ard (00:55) Yeah, Amanda, this is going to be a ton of fun, very timely subject. People are just hungry for learning how AI should be used in the right way. But before we dive into that, Amanda, let's get to know you, your work history, background, all that fun stuff so the audience knows a little bit about who you are. Amanda Landsaw (01:12) Yeah, of course. So I am Amanda Landsaw, the CMO at Endeavor B2B. We are a marketing media and intelligence organization. We have 90 plus brands across 16 different verticals. We produce a ton of content, both at the brand level, but also from a marketing perspective. A little bit history with me, you know, I have a wide diverse background of marketing from agency worlds to a little bit in WNBA and the publishing and media space. And so, you know, it's been a fun ride over the years, but we were also seeing a lot changing very rapidly. And so that's kind of where part of this conversation comes in, you know, as an organization that produces a lot of content, both for, you know, for our organization itself, our brands itself, but also for our clients, there's an interesting takeaway too I think a lot of this that's coming down the pike really rapidly, whether that's the impacts that AI is having on search or just content production on a regular basis and how we're interacting with AI every day. Benjamin Ard (02:14) Yeah, I love that. That's awesome. Okay, well, let's dive in. Amanda, we're talking about AI and how it has kind of shifted how we manage to create content. It has made it so much more rapid. It's easier than ever. You can produce incredible quantities of content like never before. It is absolutely insane. I've seen websites like kick out dozens of posts every single day. Of interesting content. I don't know if I'd ever read that kind of content, but the whole question is, even though we can produce more content and it's changed the whole content workflow and life cycle, it's not always adding up to pipeline or revenue. It feels like there's a little bit of a disconnect. Why do you think that's happening? What do think that disconnect actually looks like? Amanda Landsaw (02:59) I think that increased supply and volume does not increase relevance or differentiation or trust. Speed is not strategy. And so at the end of the day, yes, you can produce more content. You can produce it very fast, but it doesn't really increase the demand for it, right? It kind of creates noise. So what it really, what it comes down to is like what are you actually producing and is it going to help, you know, reduce risk somewhere? Is it going to help sharpen decisions? Like how is it actually going to to move the needle or increase pipe, move pipeline, increase pipeline or whatever it may be. If you're utilizing AI and again, I think that there is a way to do that very responsibly, but I just at the end the day, I don't think it actually increases relevance of differentiation unless you make it. Benjamin Ard (03:51) I love that. So just because you can produce an excessive amount of content doesn't mean that it's always the right content. How do you focus on creating the right content and how does AI play a role for you personally and how have you seen it done right? So when you're identifying building, not just having it be this machine that kicks out whatever, how does that work and what does that look like for you? Amanda Landsaw (04:19) So I think a big piece is at the end of the day, you still have to provide the direction, right? You still have to provide your input. You still have to provide your expertise to help guide it. Yes, it can do a lot of the research for you. It can create beautiful drafts. But if you're putting in, pardon my French, crap input into it, it's gonna give you crap output. And so I really think that there's a big piece to that. And that's really how I, you know, I personally try to use it in that way. I work with like our teams to try and utilize it more efficiently and effectively in that way. But you have to be an expert with prompting. You have to have, this is going to sound weird and I totally, I totally understand that and realize that, but you have to have almost like an intimate relationship with that AI to be able to have a conversation and have an ongoing conversation because the prompt isn't one and done right. It is taking things to those next levels to keep peeling back the onion. What are those different layers? And so I do think that's a critical piece to all of it is if you want to be able to produce more content at a higher speed, higher velocity, I think it's all possible, but you have to be putting in the right information to be able to get the right information out. Benjamin Ard (05:32) I love that. And I love how you talked about almost the intimacy of getting used to the AI system. I know as I've trained and talked to people that aren't familiar with AI, it's a completely different interaction with a computer than they've ever had before. Where you're like, you almost have to bear your soul to this thing to say, this is what I'm feeling. This is what I'm thinking. This is the emotions I want the audience to feel. Here's what I'm trying to overcome. That's really uncomfortable for a lot of people at very first to be like, this is like a journal, but I'm telling a computer and then it's kicking something out. But I love that you kind of call that out. If you're really honest and really in depth, you're going to get a much higher quality, not the crap in crap out kind of a concept. Now, Amanda, you mentioned at the very beginning, it's not just on the content creation side that we're changing everything. It's also on the consumer side about the kinds of content I want to consume, how I'm going to consume them, where I'm going to consume them. How does that change the whole game of content and what is shifting and how are you adapting to that? Amanda Landsaw (06:32) Yeah, I mean, I think it changes the game in a big way because I people have their phones constantly now, right? You have, I mean, heck, now you have AI that's kind of being embedded into your messages or whatever it may be. I'll say this as a funny little story. I was talking to one of my employees today and we were talking about AI and how he's utilizing it. And he said, he followed up with me after the meeting. He was like, here's one way that I, you know, I thought this was interesting. He's like, one of my biggest pet peeves is being put on an email thread and there's a CC below and you have to go through 15 different chains to see what's going on. He's like, I just threw it into AI and said, what is relevant for me? And it popped it up. Right. And so I think that whether it is at the employee level and how they are consuming content, whether that's their day to day on, you know, you can have AI summarize a PDF for you now, you can have it helping you create presentations, whatever it may be from a consumer perspective and how they're actually consuming content. It's people are now using it, whether it's ChatGPT, Claude, doesn't matter, right? They're using that almost as their new search. And so how are you staying relevant in that sense and updating your content to stay relevant in that sense? I think is an important piece that all of us as marketers have to really come to terms with and have that, you know, that uncomfortable conversation with ourselves about it's also looking at like, are podcasts, right? How are you utilizing podcasts now? How are you regurgitating some of the content that you will have already produced to actually start a conversation and have a deeper level with it, with the podcast or with a video session or whatever that may be. And people now, are they're on the go. They're busy. So basically making sure that however you're producing the content is as easy to digest as possible. And that's also going to be easy for AI and other other avenues to pick up. Benjamin Ard (08:24) I love that. That's so cool. So the whole content creation, content consumption, it's all changed, you know, and it's constantly changing every single day, every single model update, anything that comes out, there's something cool and new as a CMO who has responsibility over a lot of different areas in your business, who also really cares about revenue generation. How do you look at content's role in revenue generation? And how are you measuring some of those KPIs, whether it's for your team, company performance, things like that? How does the content fit into the overall structure, especially now that things have kind of shifted? Amanda Landsaw (09:03) I'll admit, I'll be the first admit, this is an ever evolving thing, right? We are still in the infancy stages of trying to figure this out as well. We, I mean, it's definitely on our radar. It's definitely, you know, we're moving past the entity metrics, right? We are taking it to that next step. Really look like, looking at like outputs and what that, you know, what actually that's producing, inputs and outputs and how, what all that's actually producing. But it's a big part of the direction that we're trying to push and that I'm trying to push my teams from a revenue perspective because there, whenever you have marketing and sales alignment, you have a lot more harmony than whenever those two things are siloed out, right? If you can't see what the left hand and the right hand are doing, then they could be working on the same thing, but providing different messages and just making it very, very convoluted. So the more content, relevant content, that we can provide to really help our sales team take those conversations to that next level. We really try and push them to say, like this gives you a great opportunity for an opening, right? Like we have underlying data. We all know that technology is getting smarter scripts are on all these different websites to give companies these different levels of insights and intent data at the end of the day, the behavioral data. We all know that's happening, right? So how are we doing that in a smart way to help guide the conversation from the content perspective? How are we helping that, then taking that content and helping the sales reps guide those conversations so that they're getting the right information in front of the right people at the right time and having that next layer to those discovery conversations instead of going in, hey, we offer 1,200 products or whatever that may be, where do you wanna start? Instead we can say like, in a not, let's say in a non creepy way, like, hey, we saw that, you know, we know you are in the safety space and hey, maybe you might be interested in this content syndication program that we have, because I know you looked at our content syndication section out of our website, right? Like it's just basically having some of those smarter insights that is, you know, all doing all of that with a privacy first mindset. But giving people the opportunity to really have those next level conversations and starting it kind of a step or two ahead instead of just having to start from ground zero. Benjamin Ard (11:25) I love that. And what you just described, in my opinion, is what personalization actually looks like. Personalization is not just all these variable tags throwing their name and industry in a piece of content. It's really about relevancy. Do I know what they care about? At least can I assume, like you said, in a very privacy minded way, I'm looking at helpful data points and I'm just trying to be as helpful as I can with my content. That is relevancy. That is actually what we mean by personalization. I love that. That's super cool. Amanda Landsaw (11:56) Agreed, and it's not easy. At the end of the day, that is not easy. That takes a lot of time, right? You have to have the technology stack and the technology layers on top of that. And then you also have to have the right people in the right positions to be able to have that conversation. That is not a conversation that everybody can have eloquently without it sounding creepy at the end of the day. Benjamin Ard (12:16) Yeah, 100%. And I also love like with your privacy background, you probably have to draw a line to say, okay, this is where things stop. This is where it crosses the line. This is where it's no longer productive, helpful, or at all ethical. And it's nice to have that baseline to say, okay, I know where we have to draw the line. Now, one other question I have for you with content changing on all sides of things, what kind of content being produced has seemed to shift. A lot of businesses are focused on like bringing out individuals in their business and showing them off and letting them be subject matter experts. The formats, the kinds of content, you mentioned podcasting and videos and things of that nature. Have you found a shift in the kinds of content you're creating and how people are kind of accepting or creating that content? Now that AI is playing a bigger part of the discovery and the consumption, even in like the email reading, summarize this thread for me kind of an idea. Has that shifted the kinds of content you're creating in any way, or form? Amanda Landsaw (13:19) A little bit. I mean, I look at, so we look at content at a couple different levels, as I mentioned earlier, right with the organization, we have things at the brand level that are very B2B, right, we're gonna have an engineer coming into one of our brand sites and consuming content that's going to be most relevant for them. And their job, how can they do better? Like, what's what's the latest that's happening in their job that they need to be aware of? Or how can they do better? What's like this product review or whatever? Maybe we have a wide variety of content that's around that. And yes, it has kind of shifted some of how our editorial teams are producing that content, right? And how they're doing some of the fact checking. It does speed some of that along, but it gives that journalism piece, I think, again, when done right with the right prompts and ethical manner, which we train our teams very much to do, it can be a very, very helpful and useful tool. On the marketing side of things, and this kind of plays a role on both sides of it on the marketing sides of things, right? Like really diving into the thought leadership, which AI can help you produce thought leadership all day long. What it can't do is really provide you with like, all right, Benjamin's point of view and expertise and whether that's like really your name behind it, right? Like, do I personally believe you have to bring people to the forefront? I do think it helps. I do think people want to feel like they have that connection with the human at the end of the day. Is it absolutely a requirement? Probably not. But I do think having the point of view and the expertise, those are the types of things that AI can't replace. Again, can help, AI can help you pull that out with the right prompts, but you still, like I'm firm believer, you're gonna have to have that human element, that human review, that human tone that's gonna help at least set it and take it to that next level. And that's really what we've done in that sense. Benjamin Ard (15:02) I love that. And it does differentiate your content in such a big way, because if you say, write me a piece of content about something, AI is taking the middle of the road, unbiased, whatever kind of a perspective on the content. And I love how you talked about like, this is my point of view. It's almost like, you know, again, with that conversation about prompting, I almost have to say I am biased because I believe this. Put those lenses on and everything we're going to write her out has to come from that bias standpoint because that's why we have a business. We do things differently than others because we believe this where other people believe this. So we have to prove that our way is the right way or at least a way that you should be thinking about it. So I love the call out really embedding that point of view, the human nature into it because that's a part of being a human. That's a part of being a natural person to say, I believe this and not this. And AI doesn't inherently do that. And I love that you're putting that in your content. Amanda Landsaw (16:03) Well, and I think an interesting piece to that too is AI has changed so much in the last six months even, right? Last 12, 18 months, but like last six months, where it's gonna be in the next six months, we have no idea. All we can do is kind of prepare for change and get up to speed with where it's at today and continue to evolve. But to that point, I also think, you know, you can train the AI for your point of view. Right? Here's all of my talks that I've given over the last three years. Here's all the papers I've written. Here's all the blogs that I've posted. Here's all the podcasts that I've participated in. Now use that to write for me. Be my ghostwriter, right? And write for me with my tone and all that. And then I'll go back and I'll review it occasionally. I do think that that is where we're at. Many people have done that. People are gonna listen to this and go, well, I did that a year ago. Okay. Yes, that absolutely can be done and probably should depending on the I guess the demand for your voice in the industry. But I do think you still need that human review to make sure because at some points it's gonna hallucinate right and are you being able to that hallucination? Benjamin Ard (17:14) Well, and there's always nuance, right? Like no matter how well I train AI, it may not fully understand like the nuance of my bias or point of view. It may take a different interpretation of that. The human in the loop is absolutely vital. I love that call out. Amanda, these episodes go by quick. When we have run out of time, this is an amazing conversation. It has got the wheels turning for me personally, and I'm sure for anyone listening, this will be incredible. Amanda, if anyone wants to reach out and connect with you online, how and where can they find you? Amanda Landsaw (17:41) Find me on LinkedIn and always reach out and then reach out on LinkedIn then happy to exchange email information and you know have coffee chats. Benjamin Ard (17:51) I love it. For anyone listening, regardless of what platform you're on, scroll down to the show notes, click on the LinkedIn link, it'll go directly to Amanda's profile. Connect with Amanda there. Say you came from the podcast and all that fun stuff. That'll be great. Amanda, again, thank you for the time and insights today. Really do appreciate it. Amanda Landsaw (18:07) Thank you so much for having me. It has been a blast.

About the guest

Amanda Landsaw

Amanda Landsaw

CMO, Endeavor B2B

Amanda Landsaw is the CMO at Endeavor B2B, a marketing, media, and intelligence organization that produces content across 90+ brands in 16 verticals, both for its own properties and for clients. Her background spans agency work, the WNBA, and the publishing and media space, giving her a wide-angle view of how content gets made and consumed. Amanda is focused on helping marketing and sales teams use AI responsibly, with a privacy-first mindset and the human point of view kept firmly in the loop. She believes the marketers who win the next cycle will be the ones who treat AI as a conversation partner, not a content vending machine.

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Frequently Asked Questions

Amanda's frame is that increased supply and volume does not increase relevance, differentiation, or trust. You can produce more content faster with AI, but if it does not reduce risk, sharpen a decision, or move a deal forward, all you have done is add noise. The output is bounded by the input, so unless marketers sharpen the prompt and layer the conversation with the model, the extra volume creates fatigue rather than demand. Speed is not strategy, and the teams that win are the ones producing the right content, not just more of it.

Amanda means treating AI like a long-running conversation partner, not a search bar. You give the model real context (audience, emotion, objection, point of view), then keep prompting deeper to peel back the onion until the output reflects what you actually think. People who are new to AI find this uncomfortable because it feels like journaling to a computer, but that vulnerability is exactly what produces non-generic work. The prompt is never one-and-done; it is an ongoing dialogue you refine over time.

Buyers are using ChatGPT and Claude as their new search, asking AI to summarize long email threads, PDFs, presentations, and podcasts on their behalf. That means content is increasingly being read by a model first and a human second, so format matters as much as substance. Marketers should make every asset (including video and podcasts) easy to digest and easy for AI to pick up and surface, so it shows up where buyers are now actually looking. If your content is not AI-friendly, it is invisible to a growing slice of the audience.

Amanda's answer is no. AI can help you produce thought leadership all day long, including pulling out angles and drafting in your tone if you train it on your own talks, papers, blogs, and podcasts. What it cannot replicate is genuine point of view, expertise, and the bias that comes from believing one thing rather than another, which is what differentiates a brand in the first place. The fix is to keep a human review layer in place to catch hallucinations and preserve nuance, and to deliberately prompt with your bias on the table so the output reflects how you actually see the world.

EP 42216 min

Using AI for Mega Trend Research and Smarter Content Strategy with Tuesday Hagiwara

with Tuesday Hagiwara

In this episode of Content Amplified, host Ben Ard chats with Tuesday Hagiwara about a side of AI that most marketers are overlooking — using it for high-level strategic research and trend analysis rather than just content creation. Tuesday walks through her process of identifying mega trends using the PESTLE framework (Political, Economic, Social, Technological, Legal, Environmental) and how she leverages tools like ChatGPT, Claude, and Miro to consume and synthesize massive amounts of research — including 160+ pieces of thought leadership and 60+ reports. She explains how grounding your LLM conversations in deep research produces dramatically better campaign ideas and content strategies. Tuesday also shares how she validates insights through real-world conversations and emphasizes using AI for what it does best — summarizing and pattern recognition — rather than writing content directly.

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EP 43820 min

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Awareness, opens, and clicks are vanity metrics, and most marketing teams are still measuring content as if they aren't. In this episode of Content Amplified, Justin Chappell, Head of Digital Strategy, CX and Operations, breaks down how to connect content to the numbers that actually matter: gross revenue retention, net revenue retention, renewal rates, and time to value. Justin walks through the three places content programs typically break down, why a 'peanut butter' health-score approach fails customers, and how predictive engagement models beat old-school drip campaigns. He shares his long form / short form / micro-learning framework for building a content roadmap every team can contribute to, explains why you have to stop measuring success at the open and start measuring it at 30, 60, and 90 days, and makes the case that self-service content is really about removing friction, not removing humans. If your content program is stuck proving awareness instead of proving value, this conversation gives you a clear path forward.

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