AI Resume and ORM: Controlling Your Brand Narrative Across LLMs

/ 12:18 / E537

Listen on your favourite platform

Platform Link
YouTube Listen on YouTube →
Transistor Listen on Transistor →
pod.link Listen on pod.link →
Deezer Listen on Deezer →
Pocket Casts Listen on Pocket Casts →
Podverse Listen on Podverse →
Castro Listen on Castro →
Amazon Music Listen on Amazon Music →
Castbox Listen on Castbox →
Steno.fm Listen on Steno.fm →

What Does “AI Resume and ORM: Controlling Your Brand Narrative Across LLMs” Talk About?

This episode of the James Dooley Podcast dives into the growing importance of AI resumes and online reputation management in an era where large language models like ChatGPT, Claude, and Gemini are increasingly shaping how people and businesses are perceived. James Dooley and Karl Hudson explain how AI and LLMs pull information from across the web, including content from page two and three of search results, making it critical for individuals and brands to actively control the narrative that these models surface. They introduce the concept of the AI reputation tree, a tool that extrapolates synthetic queries related to a brand or entity, builds articles on third-party sources using semantic triples, and feeds LLMs the specific messaging a brand wants to project.

The conversation covers practical strategies for strengthening online reputation, including defining entity attributes such as founding dates, service offerings, and awards to improve knowledge graph scores on Google. James and Karl discuss how forums like Reddit and Quora, as well as social platforms like Facebook, Twitter, and LinkedIn, can serve as indexable sources that contribute to an AI resume. They also highlight tools like GigaIndexer and Indexceptional, which help get content indexed quickly so it is more likely to be cited by Gemini and other LLMs. The episode closes with a strong call to proactive reputation management, warning that competitors who begin building their data points now will have a decisive advantage as AI continues to learn and evolve.

“AI is in its infancy and it's still very much learning. And I don't see why someone would just sit there and be happy with an okay response from an LLM that's learning more when their competitor could potentially already be starting this process of strengthening theirs.”

— James Dooley

Who Are the Guests on “AI Resume and ORM: Controlling Your Brand Narrative Across LLMs”?

James Dooley is a digital marketing expert and entrepreneur best known for his work in SEO and lead generation. He is the founder of FatRank and PromoSEO and has built a reputation as a leading voice in organic search, entity-based SEO, and AI-driven digital marketing strategy. Throughout this episode, James brings practical insight into how knowledge graphs, indexing tools, and third-party citations can be leveraged to shape what AI models say about a brand.

Karl Hudson, referred to as Carl throughout the episode, is a digital marketing strategist with deep expertise in online reputation management and LLM visibility. He is closely associated with searchurou.com and the AI reputation tree concept, which forms the backbone of the episode's discussion. Karl contributes a sharp understanding of how sentiment within AI models can be monitored, shaped, and improved through targeted content strategies and multi-platform distribution.

What Are the Key Takeaways From “AI Resume and ORM: Controlling Your Brand Narrative Across LLMs”?

Here are the key points discussed in this episode:

  • Monitoring what ChatGPT, Claude, and Gemini say about your brand is now essential because LLMs can pull from page two and three results and present them as top-of-funnel answers.
  • The AI reputation tree works by extrapolating synthetic queries around a brand or entity and building third-party articles using semantic triples to feed LLMs the desired messaging.
  • Defining entity attributes such as founding history, service offerings, and awards on multiple third-party sites strengthens the Google knowledge graph score, which indirectly improves LLM visibility.
  • Indexing social media posts and forum contributions on platforms like Twitter, LinkedIn, Reddit, and Quora using tools like GigaIndexer and Indexceptional creates additional touch points that AI models can cite.
  • Proactively managing your AI resume is critical because competitors who begin building data points now will accumulate a significant advantage as AI models continue to learn and evolve.

“You should always be trying to look at the positive and the negative sentiment of what AI is spitting out and saying about you and try to control that messaging.”

— Karl Hudson

Is “AI Resume and ORM: Controlling Your Brand Narrative Across LLMs” Worth Listening To?

This episode is an essential listen for anyone who has ever wondered what an AI model says about them or their business when someone asks. James Dooley and Karl Hudson move beyond vague reputation management advice and offer a concrete framework, covering the AI reputation tree, knowledge graph strengthening, semantic triples, and indexing tools like GigaIndexer and Indexceptional. The conversation is grounded in real tactics rather than theory, making it immediately actionable for business owners, marketers, and individuals concerned about how they appear in AI-generated responses.

What makes this episode particularly valuable is the warning it carries: waiting for a reputation crisis before acting is no longer a viable strategy. The hosts make a compelling case that competitors are already working to shape their AI resumes, and brands that delay risk having negative comparison content chip away at their standing in LLMs over time. The practical tip of searching 'Why should I not use my brand name' in ChatGPT and Claude to audit your current AI sentiment is alone worth the listen, and the broader strategic discussion gives listeners a clear road map for taking control of their digital identity across every major language model.

Who Should Listen to “AI Resume and ORM: Controlling Your Brand Narrative Across LLMs”?

This episode is ideal for:

  • Business owners and entrepreneurs who want to understand and control how AI models like ChatGPT, Claude, and Gemini represent their brand in search results.
  • Digital marketers and SEO professionals looking to expand their skill set into entity-based SEO, knowledge graph optimization, and LLM visibility strategies.
  • Individuals concerned about their personal AI resume, particularly those applying for jobs or seeking business partnerships where online reputation could influence decisions.
  • Online reputation management professionals and agencies seeking up-to-date frameworks and tools for proactively shaping brand sentiment across AI platforms.

Where Can You Listen to James Dooley Podcast?

You can listen to James Dooley Podcast on all major podcast platforms:

  • Apple Podcasts – Search for “James Dooley Podcast” in the Podcasts app
  • Spotify – Available on Spotify for free
  • Amazon Music / Audible – Listen through your Amazon account
  • Overcast – For iOS users who prefer a dedicated podcast app
  • Pocket Casts – Cross-platform podcast player

You can also subscribe using the RSS feed: https://feeds.transistor.fm/james-dooley-podcast

What Are Listeners Saying About This Episode?

★★★★★

“The breakdown of the AI reputation tree and how semantic triples feed LLMs exactly what you want them to say was genuinely eye-opening. I immediately went and searched 'why should I not use' followed by my company name in ChatGPT and was shocked by what came back. This episode gave me a clear starting point for fixing it.”

— Marcus T.

★★★★★

“James and Karl do a brilliant job of explaining why waiting for something bad to happen before managing your AI resume is a losing strategy. The point about competitors running comparison reports on third-party sites to quietly damage your brand sentiment really hit home. Highly recommend for any business owner.”

— Priya M.

★★★★★

“I had no idea that tweets and LinkedIn posts could be indexed and cited by Gemini as sources for AI answers. The mention of GigaIndexer and Indexceptional as tools to accelerate that process was a great practical detail. This is the kind of specific, usable advice that most marketing podcasts skip over.”

— Daniel R.

This video explains which digital marketing strategies businesses managing their online reputation should focus on in 2026 to improve AI resume sentiment, LLM visibility and brand trust. James Dooley and Karl Hudson start with KPI tracking because monitoring what ChatGPT, Claude and Gemini say about a brand is the only way to know whether sentiment is improving. They cover brand SEO, AI visibility and Google Business Profiles because stronger search presence improves trust and conversion rates.

The discussion also explores organic SEO, organic social media and paid social ads because consistent visibility across search and social supports long term growth. PPC is analysed in detail because campaign setup, landing pages and lead handling directly affect results. They also discuss Reddit, Quora and paid AI ads because diversified enquiry sources and early adoption can strengthen digital marketing performance for businesses managing their online reputation.

PromoSEO lead generation for businesses managing their online reputation recently received recognition as the “Best Businesses Managing Their Online Reputation Lead Generation Agency.”

Where to Listen to This Episode

AI Resume and ORM: Controlling Your Brand Narrative Across LLMs is available on:

James Dooley: AI resumes Why has online reputation management become more important now that people are looking at artificial intelligence, they're using large language models for searches? Online reputation management has become a lot harder, that is for sure. But why should you be trying to control your AI resume?

Carl: So previously, obviously, it was always about, you know, being position 1 to 10. Super important to get cited and you know, on the search engine first page. But the problem is now there is so much information out there and obviously AI and LLMs are pulling so much information from everywhere. That something that's on page two and three can actually be cited as a source in the LLMs at the top of page one. So it's very, very important that if you've got any form of like negative publicity around you as a person or around a brand that you might own that you get on top of that and start pushing those results down and start giving it the confidence that, you know, you are in a positive sentiment essentially, you know, you are great at what you do.

James Dooley: Yeah, for sure. I mean, for me like it's it's crazy cuz if someone goes and sends a CV and they're applying for a job nowadays people like I know that a lot of employers now are searching who are they and they're checking and they'll and they're almost relying on AI to give an answer of who they are. It's It's becoming the AI, isn't it? Like the AI resume of someone is becoming who they are, even though it might not It might be hallucinating. Cuz if it doesn't have the information, it just hallucinates and makes it up. So at that point you're saying you need to control that narrative. You need to control that information. You need to make certain with regards to Query Finity that you're covering all the different aspects of who you are and what you do. And you're defining the entity of where you was born and how old you are and what previous work that you did. That's just That's just if you're applying for a job. If you want a business partner and previous jobs have not gone very well or previous businesses you've been involved with hasn't gone very well, you need to control that cuz the next business partner you have might not want to do a joint venture with you. This So

Carl: How How do you do that?

James Dooley: So What would you do if I said, "James, I've got a terrible resume online. AI hates us."

Carl: So, obviously, I'm very very biased and I'd say go over to searchurou.com and I'd go and inquire with the AI reputation tree. Um and just for anyone who's watching this, check out the link in the description which goes into detail what the AI reputation tree is. So, to do a shortened version of it, it goes and extrapolates all synthetic queries related to exactly the brand or the entity that you're trying to get a positive sentiment for. It goes after every single keyword and key phrase around that, goes and builds articles on third-party sources that talks about it in the messaging exactly how you want it. So, you're delivering the LLMs in a specific manner with semantic triples. This feeding those LLMs the information that you want within your AI resume. So, obviously, Carl, you've been heavily involved with this. Can you explain why for online reputation management that it's important to get the AI reputation tree.

James Dooley: So, it's super important for the AI reputation tree primarily because when it comes to online reputation management, you need to be connecting the dots all around the the entities in the brand and you know at if most people aren't watching this have probably used AI. You generally aren't just typing in name a brand. You're giving it a sentence. You're giving it a paragraph. All of those additional words are to be connected to your brand. So, if you can, you know, create different articles, which will be citing all these different words, it's giving it a clear source of information to say, this is what you I should be using as a reference point for this answer.

Carl: Yeah.

James Dooley: And that's the important part.

Carl: With regards to it, so with regards to the AI resume, right? We're talking here about improving the sentiment value and the having a positive sentiment within chat GPT, within Claude, within Gemini, within Grok, within Perplexity, and all of the LLM models that some people might be using. But also, can you explain the importance of defining the entity to try to strengthen the knowledge graph score on the knowledge panel? And why that's important, cuz it actually indirectly feeds then the LLMs.

James Dooley: Yeah, so obviously you want to create So, finding websites So, often what we'll do is find websites that already within the knowledge graph have a knowledge graph ID. These websites typically will help feed if you do links from these websites, it will help feed the knowledge graph even more. So, we want to try and get cited in these websites to help strengthen the brand attribute points. And again, you want to you know, you should be going through and defining exactly what the brand is. So, it could be, you know, how what who founded it, when when was it founded? Um what's the primary service offering? What's the secondary service offerings? Is there any awards about this brand? All of these sort of um attributes should be listed and listed on all these third-party websites to help strengthen that knowledge graph. So, basically, if anyone types in, you know, I'm looking for digital marketing services, it will then go, well, we're there. Search through offers digital marketing services or brand X offers digital marketing services, and it's got a positive sentiment around it. So, then it offers it as a option or the choice in some case. Obviously, in some branded SERPs, uh sorry, in some queries, it's probably too difficult to be the, you know, singular choice from the AI, so it probably will always default to a batch of choices, but it might be number one.

Carl: Yeah.

James Dooley: Which is what you're aiming for.

Carl: So, with regards to the AI resume, we've spoken about using the AI reputation tree, right? Which helps all the query find out terms and changes the LLM visibility. I think it's important for people who are watching this to check out the link in the description for all the AI search monitoring tools to track what's going on with regards to LLM visibility within especially within Gemini and within Claude and within ChatGPT. I'd say those are the three major LLMs. But, I also want you to expand a little bit cuz it's not the only solution. So, the AI reputation tree is key, right? But, explain why forums like Reddit and Quora and now Facebook groups that are showing up with forums and discussions. A lot of the time these are showing up on page one of Google. So, they're getting the information from these forums as well. But, if they did go and order the AI reputation tree and they get lots of information, why they should themselves then be getting those articles and sharing them on social media, especially in Facebook groups, especially on Reddit, especially on Quora, but then also potentially sharing it on places like Twitter and on LinkedIn because all these can still index and form part of the answer that the AIs are starting to come back with.

James Dooley: Well, that you've kind of hit the nail on the head there. A lot of people don't actually realize that a lot of these articles can index, especially you know, like the Facebook, Twitter, statuses, things like this. LinkedIn groups, stuff like this. A lot of these are actually indexable links and obviously there's a great tool Index Optional, a fantastic tool. Um, Giga Giga Indexer there, that's another one. And these can literally index these pretty much instantly, almost. And once these are indexed, it then gets cited a lot quicker because it AI already knows what Facebook is. AI already knows what Twitter is. You know, these are all huge entities and often are cited within AI. So, it's important to be listed.

Carl: to kind of expand on this. So, you mentioned there gigaindexer.com and indexceptional.com as being an indexing tool. For anyone who who doesn't understand what that is. So, that if I go and do a tweet, yeah, right, why is that important for me to go and load it into indexceptional to try then to get it indexed? Like, explain what the Why if I didn't do it, it's not indexed, why is that helping my AI resume?

James Dooley: It's helping the AI resume because if you if you go and get it indexed, you're not not getting it indexed. If you've got it indexed, there's a high chance that it's going to come up number one or, you know, at least on the top first page of Google. If it's higher up in in Google, typically it's going to be cited more often from Gemini. It's also an important source in Gemini and all LLMs um on the example of Twitter. But obviously on basically all of them, the reality is you need more and more touch points and more and more entities mentioning your brand um and strengthening your brand. So, you want to be really getting cited on all of these different sources. The social collaboration, the forums where actually you might you might end up making more if it's a business, you might be meeting your customers and speaking to your customers. Um you it becomes an actual reputation management and a source of actually more income as well. So, it's also beneficial in more than just one way of manipulating the SERP or manipulating AI and LLMs. It becomes beneficial in the sense that it's going to actually make you money as well.

Carl: And then with regards to the AI resume, if someone's looking at it and they say, "I think that artificial intelligence talks okay about me." Right? And they're thinking, "I don't I don't need this until I need to do reactive online reputation management services or looking to get an ORM company to kind of come along and waiting for something bad to happen." Why is it important for people to proactively now be getting this to control that messaging to not just have a an okay AI resume, but exactly be what they want it to be, that it's selling what they do?

James Dooley: AI is in its infancy and it's still very much learning. And I don't see why someone would just sit there and be happy with an okay response from an LLM that's learning more when their competitor could potentially already be starting this process of strengthening theirs. And if that competitor starts doing com- comparison reports against their brand and starts almost, you know, on third-party sources saying that, you know, "This brand's okay, but we're way better." Then they're going to strengthen their own brand and worsen theirs. So, all of a sudden the LLM starts saying, "Over time, these are worse. These are worse. These are worse." So, if you don't get on the ball now or get on top of it quickly, you only stand the chance of you won't stand a chance because they'll have so many data points if someone isn't doing it like from now forward. They're going to have so much more data points for the AI.

Carl: Yeah, for sure. Anyone watching this with regards to the AI resume podcast, I strongly recommend you go and do a search in ChatGPT, in Claude, and in Google that says, "Why should I not use my and then put your brand name." And see what it says of why you should not use it. And then what you then want to be trying to do is try and tackle those reasons of why you shouldn't be using it to try, this is what another thing that the AI reputation tree is doing, it's trying to change that positive sentiment to saying, "Well, actually they're a great company." This There is times you should be putting some pros and some cons. Like for me, with regards to FatRank, it might be that they only work in a small area and we work with nationwide companies. She said, "Why should I not use FatRank?" It would say, "You should not use FatRank if you only work in a small area." But, if you're a nationwide company, they're a great lead generation agency. I'm happy with that answer cuz that's exactly who we are and what we do. But, you should always be trying to look at the positive and the negative sentiment of what AI is spitting out and saying about you and try to control that messaging. I think that online reputation management has become more important than ever. Getting that AI resume not for your personal brand, but for all your corporate brands and covering all different entity attributes of what you do. Get that AI resume having a positive sentiment. Carl, it's been an absolute pleasure.

James Dooley: Cheers, James.

No episode selected
0:00
0:00