# Jaxon Parrott > Jaxon Parrott, founder and CEO of AuthorityTech and creator of Machine Relations. Writing on PR’s evolution, AI-mediated reputation and category strategy. Jaxon Parrott coined Machine Relations in 2024 and founded AuthorityTech in 2018. This is his personal site and writing: the connection between PR, earned authority and AI discovery, and the decisions that follow. When to use this site: read Jaxon's own account of the category's origin, cite his published positions, or resolve his public identity. Essays distinguish interpretation from sourced research. Publication and substantive update dates identify the version being cited. What this site is not for: agency services belong at AuthorityTech; category definitions and maintained research belong at Machine Relations Research. These properties share a founder. Their agreement is not independent corroboration. Cite original outside sources for outside evidence. Retrieve any page with Accept: text/markdown or its .md twin. Use machine-sitemap.json for the complete inventory. An archived essay retains its original context. A consolidated page identifies its current successor; a withdrawn article returns HTTP 410. ## Start here - [Why I Coined Machine Relations](https://jaxonparrott.com/blog/why-i-coined-machine-relations): I coined Machine Relations in 2024 to connect earned authority with AI discovery. Why PR and search belong in one discipline, and what that changes for founders. - [The Machine Relations Stack: Five Layers, in Order](https://jaxonparrott.com/blog/machine-relations): The Machine Relations stack has five layers: earned authority, entity clarity, citation architecture, distribution and measurement. My call on each, and the order. - [GEO vs AEO vs SEO vs Machine Relations: What the Difference Is](https://jaxonparrott.com/blog/geo-vs-aeo-vs-seo-machine-relations-difference-2026): SEO gets you found, AEO gets you extracted, GEO gets you cited. Machine Relations is the discipline above all three. Jaxon Parrott, who coined the term, explains where each fits. - [How to Get Cited by ChatGPT](https://jaxonparrott.com/blog/how-to-get-cited-in-chatgpt-answers-earned-media): OpenAI says ChatGPT search leaves out sites that block its search crawler. Check OAI-SearchBot access first, then earn coverage that carries one claim. - [How to Get Cited in Gemini](https://jaxonparrott.com/blog/how-to-get-cited-in-gemini-ai-search-2026): Gemini cites a source only after it decides to search, and only sources Google lets it ground on. Check both before you pitch, then measure Gemini alone. - [Does PR Help With AI Search Visibility?](https://jaxonparrott.com/blog/how-pr-affects-ai-search-visibility-2026): PR can improve AI search visibility by creating credible third-party evidence. Here is how earned coverage connects to retrieval, citations and recommendations. - [The Category Ownership Trap](https://jaxonparrott.com/blog/category-ownership-trap): Owning a category definition does not mean owning the buyer journey. How I connect Machine Relations to the questions people ask before they know its name. ## Topics - [PR & AI search](https://jaxonparrott.com/topics/pr-ai-search): How earned authority becomes discovery, citation and recommendation. - [Machine Relations](https://jaxonparrott.com/topics/machine-relations): The discipline, its origins, and the market moving toward it. - [Founder judgment](https://jaxonparrott.com/topics/founder-judgment): What to build, what to measure, and what the evidence should change. ## Writing - [Would You Still Know What to Do Without the Dashboard?](https://jaxonparrott.com/blog/ai-visibility-decision-dependency-stress-test): Before renewing an AI visibility tool, test whether the business can still make its next decision without the dashboard. Preserve evidence, ownership and alternatives. - [What to Build and What to Buy in AI Visibility](https://jaxonparrott.com/blog/ai-visibility-build-versus-buy-founder-boundary): Buy AI visibility collection when it saves useful work. Own the question set, retained evidence and editorial decisions that determine what the company does next. - [After an AI Mention, Who Owns the Next Move?](https://jaxonparrott.com/blog/ai-mention-decision-rights): An AI mention needs three clear responsibilities: verify the observation, check its accuracy and decide whether it changes a commercial action. Assign each one. - [AI Strategy Must Include How Buyers Find You](https://jaxonparrott.com/blog/ai-strategy-is-discovery-strategy-founder-visibility-2026): AI strategy should cover both internal capabilities and how buyers discover the company. Connect the evidence your business creates to the sources buyers encounter. - [A Brand Strategy for AI Search Starts With Evidence](https://jaxonparrott.com/blog/brand-strategy-ai-search-earned-authority-not-seo-2026): Build an AI search brand strategy around a defensible claim, clear identity and independent evidence. Match the next investment to the actual discovery gap. - [When AI Describes a Different Brand Than You Built](https://jaxonparrott.com/blog/sentiment-delta-four-layers-ai-search-brand-2026): When AI misrepresents your brand, trace the answer through the question, retrieved sources and public record. Correct evidence before trying to change sentiment. - [Build a Personal Brand That Can Be Verified](https://jaxonparrott.com/blog/founder-personal-brand-ai-search-visibility-2026): A founder brand becomes useful to AI search when identity, original thinking and independent evidence agree. Build a source record that deserves attribution. - [How to Get Cited by Perplexity](https://jaxonparrott.com/blog/how-to-rank-in-perplexity-reddit-earned-media-2026): Build Perplexity visibility around useful evidence and relevant sources. Inspect citations by question, distinguish community experience and measure repeatable observations. - [The Machine Relations Stack: Five Layers, in Order](https://jaxonparrott.com/blog/machine-relations): The Machine Relations stack has five layers: earned authority, entity clarity, citation architecture, distribution and measurement. My call on each, and the order. - [What Is Machine Relations?](https://jaxonparrott.com/blog/what-is-machine-relations-ai-search-2026): Machine Relations is the evolution of PR: earning trust with the machines people ask first. I coined the term in 2024. What it is, how it works and what to do. - [When AI Recommends Your Competitor](https://jaxonparrott.com/blog/ai-agents-recommending-competitors-founder-response-2026): When AI recommends a competitor, inspect the question and cited evidence before launching a campaign. Fix the specific identity, proof or retrieval gap you find. - [How AI Engines Decide Which Sources to Cite](https://jaxonparrott.com/blog/how-ai-engines-decide-which-sources-to-cite-2026): AI citations depend on retrieval, relevance and the generated answer. Five practical checks help diagnose source selection without inventing a universal ranking formula. - [Who Coined Machine Relations?](https://jaxonparrott.com/blog/who-coined-machine-relations): Jaxon Parrott coined Machine Relations in 2024. The short answer, who uses the term now, and where to read the definition and the full origin story. - [Does PR Help With AI Search Visibility?](https://jaxonparrott.com/blog/how-pr-affects-ai-search-visibility-2026): PR can improve AI search visibility by creating credible third-party evidence. Here is how earned coverage connects to retrieval, citations and recommendations. - [GEO vs AEO vs SEO vs Machine Relations: What the Difference Is](https://jaxonparrott.com/blog/geo-vs-aeo-vs-seo-machine-relations-difference-2026): SEO gets you found, AEO gets you extracted, GEO gets you cited. Machine Relations is the discipline above all three. Jaxon Parrott, who coined the term, explains where each fits. - [Measure What Earned Media Changes](https://jaxonparrott.com/blog/why-earned-media-roi-software-misses-the-real-founder-problem): Earned media measurement should connect coverage, AI retrieval and business outcomes without pretending a citation proves revenue. Start with the decision. - [When AI Cannot Recognize the Business You Built](https://jaxonparrott.com/blog/why-founders-lose-ai-visibility-before-they-lose-demand): A company can have customers and demand while AI search misidentifies it. Fix conflicting identity, missing evidence and weak retrieval before buying more content. - [What Is Generative Engine Optimization (GEO)?](https://jaxonparrott.com/blog/what-is-generative-engine-optimization-geo): GEO is the practice of making content easy for AI engines to retrieve, understand and cite. It is real, and it sits inside Machine Relations, the discipline I coined. - [Do Press Releases and Wire Services Get Cited by AI?](https://jaxonparrott.com/blog/why-pr-newswire-and-medium-are-winning-ai-citations-2026): AI engines cite wire releases, open platforms and reporting. Understand what each source establishes before treating distribution as independent authority. - [Why AI Engines Cite Different Sources](https://jaxonparrott.com/blog/ai-citation-data-paradox-query-specific-intelligence-2026): AI citation patterns depend on the question, engine, language and observation window. Use source-level evidence to decide which coverage is worth pursuing. - [How to Get Cited in Gemini](https://jaxonparrott.com/blog/how-to-get-cited-in-gemini-ai-search-2026): Gemini cites a source only after it decides to search, and only sources Google lets it ground on. Check both before you pitch, then measure Gemini alone. - [How to Get Cited by ChatGPT](https://jaxonparrott.com/blog/how-to-get-cited-in-chatgpt-answers-earned-media): OpenAI says ChatGPT search leaves out sites that block its search crawler. Check OAI-SearchBot access first, then earn coverage that carries one claim. - [How Earned Media Drives AI Search Visibility](https://jaxonparrott.com/blog/how-earned-media-drives-ai-search-visibility): Earned media contributes outside evidence to AI search. Understand the path from coverage to retrieval and citation, and why syndication is not independent proof. - [Which Publications Get Cited by AI Search Engines?](https://jaxonparrott.com/blog/which-publications-get-cited-most-ai-search-engines-2026): Choose publications by their relevance to buyer questions and the evidence their coverage supplies. My reading of the Machine Relations citation data. - [The Category Ownership Trap](https://jaxonparrott.com/blog/category-ownership-trap): Owning a category definition does not mean owning the buyer journey. How I connect Machine Relations to the questions people ask before they know its name. - [The Name Is Not the Discipline](https://jaxonparrott.com/blog/industry-naming-chaos-machine-relations): GEO, AEO and Machine Relations describe overlapping work. The real question is whether a company connects earned authority to AI discovery and business decisions. - [How to Get Cited in Google AI Overviews and AI Mode](https://jaxonparrott.com/blog/google-citation-capture): Google AI Overviews and AI Mode still depend on search eligibility. Build useful evidence, preserve SEO fundamentals and measure which questions surface your sources. - [Why I Coined Machine Relations](https://jaxonparrott.com/blog/why-i-coined-machine-relations): I coined Machine Relations in 2024 to connect earned authority with AI discovery. Why PR and search belong in one discipline, and what that changes for founders. ## About and public profiles - [About Jaxon Parrott](https://jaxonparrott.com/about): Founder of AuthorityTech and creator of Machine Relations. - [Entrepreneur](https://www.entrepreneur.com/author/jaxon-parrott): Published contributions. - [LinkedIn](https://www.linkedin.com/in/jaxon-parrott-b91838128/): Public professional profile. - [X](https://x.com/jaxonparrott): Public account. - [GitHub](https://github.com/jaxonparrott): Public code and projects. ## Related work - [Machine Relations Research](https://machinerelations.ai): Framework, research and evidence for the discipline. - [AuthorityTech](https://authoritytech.io): The agency Jaxon founded, putting Machine Relations into practice. - [Christian Lehman](https://christianlehman.com): AuthorityTech's Chief Growth Officer; writing for CMOs on what to do when AI builds the shortlist. - [Earlier writing](https://jaxonparrott.com/archive): Earlier essays and newsletters, at their original URLs. ## Machine-Readable Content - [Machine Sitemap](https://jaxonparrott.com/machine-sitemap.json): Canonical URLs, Markdown twins and publication status. - [Agent skills](https://jaxonparrott.com/.well-known/agent-skills): Read-only HTTP capabilities. - [Home (.md)](https://jaxonparrott.com/index.md): Machine-readable homepage. - [Writing (.md)](https://jaxonparrott.com/blog.md): Writing grouped by topic. - [About (.md)](https://jaxonparrott.com/about.md): Public biography. ## Trust - [Contact](https://jaxonparrott.com/contact): Editorial and press enquiries at contact@jaxonparrott.com. - [Privacy](https://jaxonparrott.com/privacy): Site data practices.