--- source_url: "https://a16z.com/newsletter/may-2025-enterprise/" title: "How Generative Engine Optimization (GEO) Rewrites the Rules of Search (May 2025 Enterprise Newsletter) | Andreessen Horowitz" mirrored_at: 2026-08-10T13:04:34.197Z host: a16z.com cited_in_42a: true mirror_canonical: "https://index.42a.ai/a16z.com/newsletter/may-2025-enterprise/index" --- > **Original source:** https://a16z.com/newsletter/may-2025-enterprise/ ## How Generative Engine Optimization (GEO) Rewrites the Rules of Search **Zach Cohen, Seema Amble** It’s the end of search as we know it, and marketers feel fine. Sort of. For over two decades, SEO was the default playbook for visibility online. It spawned an entire industry of keyword stuffers, backlink brokers, content optimizers, and auditing tools, along with the professionals and agencies to operate them. But in 2025, search has been shifting away from traditional browsers toward LLM platforms. With Apple’s announcement that AI-native search engines like Perplexity and Claude will be built into Safari, Google’s distribution chokehold is in question. The foundation of the $80 billion+ SEO market just cracked. A new paradigm is emerging, one driven not by page rank, but by language models. We’re entering Act II of search: Generative Engine Optimization (GEO). **From rankings to model relevance** In the SEO era, visibility meant ranking high on a results page. Page ranks were determined by indexing sites based on keyword matching, content depth and breadth, backlinks, user experience engagement, and more. Today, with LLMs like GPT-4o, Gemini, and Claude acting as the interface for how people find information, visibility means showing up directly in the answer itself, rather than ranking high on the results page. One emerging signal of the value in LLM interfaces is the volume of outbound clicks. ChatGPT, for instance, is already driving referral traffic to tens of thousands of distinct It’s no longer just about click-through rates, it’s about reference rates: how often your brand or content is cited or used as a source in model-generated answers. In a world of AI-generated outputs, GEO means optimizing for what the model chooses to reference, not just whether or where you appear in traditional search. That shift is revamping how we define and measure brand visibility and performance. Already, new platforms like [Profound](https://www.tryprofound.com/), [Goodie](https://www.higoodie.com/), and [Daydream](https://www.withdaydream.com/) enable brands to analyze how they appear in AI-generated responses, track sentiment across model outputs, and understand which publishers are shaping model behavior. This isn’t just a tooling shift, it’s a platform opportunity. The most compelling GEO companies won’t stop at measurement. They’ll fine-tune their own models, learning from billions of implicit prompts across verticals. They’ll own the loop — insight, creative input, feedback, iteration — with differentiated technology that doesn’t just observe LLM behavior, but shapes it.  Put another way, GEO is the competition to get into the model’s mind. [How to make the mentions: A market map of GEO tools >>](https://a16z.com/geo-over-seo/) About the Contributors is a partner on the consumer tech team at Andreessen Horowitz, where he focuses on companies building at the application layer in generative AI. is a partner at Andreessen Horowitz, where she focuses on investments in B2B software and fintech. ## More from a16z: Recent Articles [A Framework for Defining and Refining Your ICP](https://a16z.com/framework-define-refine-icp/) _By Michael King_ The risks of not identifying your Ideal Customer Profile (ICP) well can be massive, from high CAC and low conversion rates to sky-high marketing spend. Here’s how to hone your company’s profile.   [Emerging Developer Patterns for the AI Era](https://a16z.com/nine-emerging-developer-patterns-for-the-ai-era/) _By Yoko Li_ Agents are spurring a shift in foundational developer tools. Many of the core concepts we’ve taken for granted — version control, templates, documentation, even the idea of a user — are being rethought in light of agent-driven workflows.  ## More from a16z: Top Podcasts [What Is an AI Agent?](https://a16z.com/podcast/what-is-an-ai-agent/) _By Guido Appenzeller, Matt Bornstein, and Yoko Li_ a16z Infra partners discuss and debate one of the tech industry’s buzziest topics: AI agents. Will they _really_ replace humans? [MCP Co-Creator on the Next Wave of LLM Innovation](https://a16z.com/podcast/mcp-co-creator-on-the-next-wave-of-llm-innovation/) _By David Soria Parra and Yoko Li_ Anthropic’s David Soria Parra — who created MCP (Model Context Protocol) with Justin Spahr-Summers —  discusses exciting use cases for connecting LLMs to external sources. [What Comes After Mobile? Meta’s Andrew Bosworth on AI and Consumer Tech](https://www.youtube.com/watch?v=qEjTz2ZmxHI) _By Andrew Bosworth and David George_ Meta’s CTO explores how breakthroughs in AI and hardware could turn the existing app model on its head, introduce new competitive dynamics for startups, and usher in a post-mobile era. If we get it right, he says, the next wave of consumer tech won’t run on taps and swipes — it’ll run on intent. [Who’s Coding Now? AI and the Future of Software Development](https://a16z.com/podcast/whos-coding-now-ai-and-the-future-of-software-development/) _By Guido Appenzeller, Matt Bornstein, and Yoko Li_ From their potential for new, high-level programming abstraction to their immediate practical impacts, AI coding tools are redefining what it means to be a developer. This conversation covers the dynamics of “vibe coding” and the enduring role of formal programming languages.