From SEO And CRO To Agentic AI Optimization (AAIO): Why Your Website Needs To Speak To Machines via @sejournal, @slobodanmanic

For 25 years, we’ve built websites for humans who click, scroll, and browse. That era is ending. I’ve been in website optimization for 15+ years, and this is the biggest shift I’ve seen since mobile. And honestly, I think it’s way bigger than that.

The internet is undergoing its most significant transformation since it began. Your website now has two audiences: humans and AI agents. The agents are already here, shopping, researching, booking, and making decisions. The question is whether your website can serve them.

This is the first article in a five-part series on optimizing websites for the agentic web. We’ll cover discovery, citation, technical implementation, and the new commerce protocols that let AI complete purchases on your behalf. Throughout this series, we’ll draw exclusively from official documentation, research papers, and announcements from the companies building this infrastructure.

But first, we need to understand how we got here and why December 2025 changed everything.

The Evolution: SEO To AEO To GEO To AAIO

The alphabet soup of optimization acronyms tells a story about how the web has changed.

SEO (Search Engine Optimization) dominated from the mid-1990s through the 2010s. The goal was simple: rank higher on Google. You optimized keywords, built backlinks, and structured your site so crawlers could index it. Success meant appearing on page one when someone searched for your topic.

AEO (Answer Engine Optimization) emerged as AI systems started answering questions directly. When Google introduced featured snippets, then AI Overviews, the game changed. Ranking wasn’t enough anymore. You needed to be the source that AI systems cited when generating answers. AEO focuses on structuring content so it gets selected and quoted, becoming the definitive answer rather than just a search result.

GEO (Generative Engine Optimization) expanded this further. Systems like ChatGPT, Claude, and Perplexity don’t just cite sources. They synthesize information from multiple places into comprehensive responses. GEO ensures your content appears in these synthesized answers, ensuring your expertise gets woven into the AI’s response even when you’re not the primary citation.

AAIO (Agentic AI Optimization) is the latest evolution, and it represents a fundamental shift. AAIO isn’t about being found or cited. It’s about being usable by AI agents that act autonomously on behalf of humans.

A research paper published in April 2025 by Luciano Floridi and colleagues formalized this distinction. As they put it, AAIO “explicitly optimises content for autonomous artificial agents, simultaneously addressing both human and machine interpretability.” Unlike SEO, which enhanced discoverability for humans through search engines, AAIO prepares websites for AI systems that initiate digital interactions independently.

Agent Experience Optimization (AXO) is the umbrella term that encompasses all of these practices. Just as UX focuses on human users and SEO focuses on search crawlers, AXO focuses on AI systems that interact with websites. It includes discovery (being found), citation (being referenced), and action (being usable). I cover AXO in depth in What is Agent Experience Optimization.

The progression is straightforward: SEO asks “How do I rank?” AEO asks “How do I get cited?” GEO asks “How do I get included?” AAIO asks “How do I enable agents to complete tasks on my site?”

The relationship between website optimization and AI effectiveness creates a virtuous cycle, similar to what happened with SEO and search engines in the early 2000s. When websites implement AAIO practices, AI agents perform better, which encourages more websites to adopt these practices, which makes agents more useful, which drives adoption further.

December 2025: The HTML Moment For AI

On Dec. 9, 2025, something significant happened. The Linux Foundation announced the Agentic AI Foundation (AAIF), a vendor-neutral governance body for agentic AI standards.

Eight platinum members anchored the foundation: Amazon Web Services, Anthropic, Block, Bloomberg, Cloudflare, Google, Microsoft, and OpenAI. What’s remarkable here isn’t the technology. It’s that OpenAI, Anthropic, Google, and Microsoft are building shared infrastructure instead of competing standards. This is a strong signal that the industry sees agentic AI as foundational, not a feature war.

Three key projects were contributed:

• Model Context Protocol (MCP) from Anthropic: a universal standard for connecting AI systems to tools and data sources, now with over 10,000 published servers and adoption by Claude, ChatGPT, Gemini, VS Code, and Microsoft Copilot
• AGENTS.md from OpenAI: a standardized specification for providing AI coding agents consistent project guidance across repositories
• goose from Block: an open-source, local-first agent framework combining language models with extensible tools

This matters because it mirrors what happened with the early web. In the 1990s, competing browser vendors and incompatible standards fragmented the internet. The W3C brought order by establishing shared protocols like HTML and CSS. The Agentic AI Foundation aims to do the same for AI agents, creating the shared infrastructure that lets agents from different companies work together and interact with websites consistently.

As Linux Foundation Executive Director Jim Zemlin put it, the foundation enables development “with the transparency and stability that only open governance provides.”

We’re watching the TCP/IP moment for agents. The protocols being established now will define how AI interacts with the web for the next decade: MCP for tool integration, A2A for agent-to-agent communication, NLWeb for making websites queryable.

I realize that sounds hyperbolic. It isn’t. We’re in the early months of a decade-long transformation.

Discovery, Citation, And Action

These three concepts form the framework for this entire series:

• Discovery is about being found by AI systems. AI crawlers like GPTBot, ClaudeBot, and PerplexityBot index the web for their respective platforms. If you’re blocking these crawlers, or if your content isn’t accessible to them, you’re invisible to AI systems. Discovery is the foundation. Nothing else matters if agents can’t find you.
• Citation is about being selected as a source. When an AI system generates a response, it chooses which sources to reference. Getting cited requires content that AI systems recognize as authoritative, accurate, and relevant. This involves structured data, clear information hierarchy, and demonstrable expertise. Microsoft has published detailed guidance on what makes content citable.
• Action is about enabling agents to use your site. This is where AAIO diverges from earlier optimization approaches. An agent visiting your site might need to click buttons, fill forms, navigate menus, compare options, and complete transactions. If your site breaks when an agent tries to interact with it, you lose the business to competitors whose websites work.

The stakes escalate at each level. Failing at discovery means invisibility. Failing at citation means your competitors get referenced instead. Failing at action means losing transactions that would have happened on your site.

Why This Matters Now

Two converging trends make 2026 the year to act.

Agentic browsers are reaching consumers.

The first wave of AI browsers launched in 2025, and 2026 is bringing them to mainstream users. For a complete breakdown, see The Agentic Browser Landscape in 2026.

Perplexity’s Comet combines search-focused AI with full browser capabilities. ChatGPT Atlas from OpenAI includes Agent Mode for autonomous multi-step tasks. Chrome’s auto browse feature, powered by Gemini, is shipping to Google AI subscribers.

Chrome alone represents 3 billion potential users. If you’re wondering whether to take this seriously: Google doesn’t ship features to 3 billion users on a whim.

When the world’s most popular browser can autonomously scroll, click, type, and navigate on your behalf, the implications for website owners are profound. Websites that work well with these agents get included in agentic workflows. Websites that don’t get skipped.

As DigitalOcean’s analysis notes, “This shift forces websites to redesign for both human and AI users,” requiring cleaner navigation, API-first strategies, and optimization for agent functionality beyond visual presentation.

Commerce is shifting.

Stripe, Shopify, and OpenAI are building infrastructure for AI agents to complete purchases. The Agentic Commerce Protocol enables secure, agent-initiated transactions. Brands like URBN, Etsy, Glossier, and SKIMS are already implementing these systems.

Checkout is no longer a page. It’s an API endpoint. The agent researches, selects, and purchases on behalf of the user, who never visits your website at all.

What’s Coming In This Series

This article established the “why.” The rest of the series covers the “how”:

Part 2: Answer Engine Optimization dives into getting your content cited in AI responses. How AI systems parse content differently than search engines, the structure that gets cited, which schema markup matters, and how to measure your AI visibility.

Part 3: The Agentic Web Protocols explores MCP, A2A, NLWeb, and AGENTS.md, the standards powering the agentic web. These protocols are complementary, not competing, and together they form the infrastructure layer that enables everything else.

Part 4: How AI Agents See Your Website provides the implementation guide. How agents “see” websites, why semantic HTML matters more than ever, the role of accessibility standards, and what to tell your developers.

Part 5: Selling to AI covers agentic commerce. Stripe’s Agentic Commerce Suite, Shopify’s Universal Commerce Protocol, secure payment tokens, fraud detection for agent traffic, and how to get started.

Key Takeaways

• The web is shifting from pages for humans to content for AI agents. Your website now serves two audiences, and optimizing for both is becoming necessary.
• The evolution runs from SEO to AEO to GEO to AAIO. Each builds on the last: ranking, then citation, then inclusion, then enabling autonomous action.
• December 2025 was the turning point. The Agentic AI Foundation launch established shared standards, moving agentic AI from experimentation to infrastructure.
• Three levels matter: discovery, citation, and action. Being found, being referenced, and being usable by AI agents.
• The business case is concrete. Agentic browsers are reaching billions of users. Commerce protocols are enabling agent-initiated purchases. Websites that work with agents capture this opportunity; those that don’t lose business to competitors.

Traditional SEO asked: “How do I rank on Google?” The new question is: “How do I become the answer, and how do I let AI complete transactions on my site without a human ever visiting?”

I’m writing this series because I believe most websites do and will get this wrong. They’ll treat it as an SEO tweak or a CRO experiment when it’s an architectural shift.

The infrastructure is being built now. The standards are being established. The agents are already browsing.

The question is whether your website is ready for them.

More Resources:

This post was originally published on No Hacks.

Featured Image: Collagery/Shutterstock

How To Use AI To Streamline Time-Consuming SEO Tasks via @sejournal, @coreydmorris

SEO, like most organic and non-advertising or paid channels in digital marketing, is labor-intensive. Yes, there are software suites, analytics platforms, research tools, and a number of other things that help in the tech stack.

We all have our favorites, and no one is (or should) be doing SEO like I was in 2008 (despite my desire sometimes to just do something manually where I can see the inputs and outputs and have more control, but I digress).

In the midst of constant noise about new platforms, new ranking factors, ways to become visible in AI, and everything else, it can be hard at times to keep going with the tasks that still require a human at some level. Whether it is gaining efficiency, scaling efforts, doing more with less, or a combination of these, I’m sharing human-involved ways to streamline time-consuming tasks so you can gain time (and maybe money).

1. Generating Meta Descriptions, Page Titles, Alt Text

I could have started with something more high-level or strategic, but I’m getting this one out of the way right now.

The basic blocking and tackling of ensuring you have unique, helpful, and topically relevant meta descriptions, page titles, and image alt text can be a huge investment of time on a large website or across sites if you own tactical SEO for multiple sites or clients.

While there are ways to semantically have these tags auto-generated by a database or CMS, we know that, in a lot of cases, there’s still a manual process or intervention to audit and ensure that the tags are written to best practices and strategic positioning.

Also, I know that there’s plenty of discussion or debate on whether there’s even value in creating titles and meta descriptions. I’m not going there. But I will say that, if you have any areas where you need to create them and they are on your tasks list, you can spend a lot of hours and the cost of those hours (or outsourced resources) for a minimal return.

Leverage tools based on what you’re already paying for or what tech ecosystem you’re in, like Screaming Frog + OpenAI API + a WordPress plugin, which can save thousands of dollars and many dozens of hours.

Putting It Into Action

Steps for generating alt text at scale:

1. Get your OpenAI API key:
   • In your OpenAI dashboard at platform.openai.com, go to API keys.
   • Create a new secret key and name it something you’ll remember, like Screaming Frog.
   • Make sure you have credits in your account (a few dollars can go a long way).
2. Set up your Screaming Frog crawl:
   • Set up your OpenAI configuration by going to Configuration > API Access > AI. Enter your API Key into the field. Press Connect.
   • Set up a prompt to generate alt text by going to the Prompt Configuration tab. Click Add from Library > System > Generate alt text for images.
   • Set up your crawl configuration and don’t forget to go to Spider > Rendering and change the rendering mode from Text Only to JavaScript. Then, go to Extraction and, under HTML, check Store HTML and Store Rendered HTML.
   • Run a test crawl on one URL to ensure the output works for you. Tweak the prompt if you’d like.
3. Run the crawl.
4. Export to a CSV.
5. Format the file with two columns: image URL, alt text.
6. Add this plugin to the site: https://wordpress.org/plugins/alt-text-updater/.
7. Upload the file.
8. Crawl your site and do manual checks to test that images have alt text.
9. Deactivate and uninstall the plugin.

2. Structuring Content Outlines

This might be one of the most common things we do when starting SEO or in periodic content organization, expansion projects, or ongoing content creation. With content being what I call the “fuel” of SEO (and also visibility in AI search), it is still as important as ever to organize it well and present it in a way that makes sense to site visitors and the machines that are also learning it.

While you might not be able to automate this out of the box or in a single prompt in your favorite LLM, you can definitely speed up the process and gain some insights into connections you might not make on content themes on your own (my favorite bonus).

Whether you’re working on a single article, a longer-term content calendar, reorganizing evergreen content, or other content-specific tasks, mastering the art of prompt creation, coaching the AI agent, ensuring the output is good, and using project folders (with brand style guides) in ChatGPT can ensure the quality and speed the more you produce.

Putting It Into Action

Example Prompt

You are an expert SEO who specializes in content writing for [industry]. Your task is to create an outline for an article for [topic]. The article outline should cover the following subtopics: 

[subtopic 1], 

[subtopic 2], 

[subtopic 3]. 

The article should target the following keywords: 

[keyword]

[keyword]

[keyword]

Attached are the HTML files of pages currently ranking well in Google search results to use as guidance. Review the HTML files and generate a content outline. 

3. Creating Project Briefs

Going a little higher level into organizing the work we do, connecting desired outcomes to strategies and ultimately to tactics, project briefs are something you might not do every day.

I like to think about SEO in projects or sprints as a way to break up the big nature of ongoing and long-term work that requires short-term progress and tactics. Regardless of how you organize the work, you likely have a lot of varying documentation and information. Whether in sheets, documents, decks, or other sources, you have information that you can feed together into your LLM of choice to have AI organize and sort out.

Whether you’re doing this formally to produce a report deliverable or informally to help your team or yourself organize the minutiae of SEO information, I can point to examples of my team using Gemini to read through a bunch of documents, including meeting notes, personal notes, transcripts, AI transcripts, agendas, competitor lists, research, emails, and more.

This can be helpful for a number of uses, including putting together a document that can be helpful for personal reference, team reference, onboarding, and articulation of the overall knowledge base for stakeholders.

Putting It Into Action

Example Prompt

You are an experienced Senior Marketing Strategist and you’re onboarding your team for [describe project]. Your task is to create a comprehensive project brief for [name of campaign or project].

Ensure the project brief takes into account the following project details:

Objective: [what is the overarching goal of the project]

Target audience: [overview of the demographics]

Key messaging: [provide details about campaign messaging]

Channels: [what channels will be incorporated into the campaign/project]

For the deliverable, the output should include the following:

Project Overview: Include a 1-2 sentence summary of the project

Success Metrics: [provide KPIs]

Budget: [provide financials]

Timeline: [provide deadlines and milestones]

Generate the project brief as a professional, internal-facing document.

Classifying Keywords

Prompt for using the AI function in Google Sheets to classify keywords by search intent, segment, branded/non-branded, etc.

=ai("Act as an SEO Specialist. Classify the following Keyword into exactly one of these Categories: [Informational, Navigational, Commercial, Transactional].

Rules:

Informational: User is looking for an answer or guide.

Commercial: User is researching products/services before buying.

Transactional: User has high intent to buy/convert now.

Navigational: User is looking for a specific website/brand.

Keyword: [Cell Reference, e.g., A2]

Result: Return only the category name with no extra text or punctuation

4. Segmenting Keywords

In SEO today, we’re not focused necessarily on granular keywords. However, they are still important in our research and strategy planning, along with more tactical work in guiding content topic building and creation.

When you do your research and have your list of keywords from any source, you can utilize the Google Sheets AI function to categorize them by topic, pillar, branded/non-branded, localized or not, search intent, etc.

You can also run keywords through an LLM and have it categorize them, export the output, import that back into your spreadsheet, and align it to the data using a VLOOKUP function (a recommendation, as my team thinks the Google Sheet AI function isn’t where we want it to be yet).

While the method I noted also might feel manual and not where we want it to be eventually, with better AI and tooling, it is still much better than doing things manually. I encourage you to use your own spreadsheet logic or “regular expression” (regex) to categorize as much as you can efficiently before going to AI, especially if your dataset is extensive.

5. Documenting Competitor Outlines

While I have to admit that I like to visually check out competitor websites for my first impression and a quick, informal sophistication check, automating this is a huge time-saver.

For example, Gemini is really good at outlining the content structure of a webpage, so my team likes to feed three or four competitor URLs that are ranking well or have high visibility for a topic that we’re building a strategy for, and it can give us an outline of each page. That includes messaging, targeting, and providing baseline content blocks that each page has that we can use when we do content development on our side.

Disclaimer: Just like in the olden days, don’t copy directly and don’t steal. Verify that what you’re getting back out of the tool you’re using isn’t ripping someone off. That’s on us to validate.

Putting It Into Action

Example Prompt

You’re an expert SEO strategist and you’re conducting a competitive content analysis of your client’s page against pages currently outranking it in Google for the search term [keyword]. The client is a [describe client and industry]. The page is [describe purpose of the page and topic].

I’ve attached the HTML files of the client’s page, as well as the HTML files for the competitor pages. Your tasks are to provide me:

An outline for each page of the content blocks present in the HTML

An overview of the messaging, tone, voice

A list of outgoing internal links in the content

Content gaps between the client's page and the competitors 

6. Conducting SERP Analysis

We can’t waste impressions and any visibility we get by showing up on the wrong topics. SEO now is about quality, and we can’t miss the mark on search intent.

An example that is a big time-saver is to build your seed keyword list using Ahrefs and then export the keyword list with SERP data. Then, feed that spreadsheet into Gemini and have it provide a breakdown of organic competitors per keyword, intent of ranking organic pages per keyword, etc. This example is a good way to save time from having to review hundreds and hundreds of rows. My team usually filters out AI Overviews and ad placement data to condense it a bit.

This type of work has been helpful in figuring out informational versus commercial intent SERPs at scale so that we’re targeting the right keywords with the right content. It has also been helpful in understanding the level of competition within a topic, so we know what to avoid and what long-tail keywords may represent realistic opportunities.

I will emphasize, though, that it is important to note that the SERPs aren’t 100% accurate, and localization and personalization will change the SERPs that users see. But it’s helpful in comparing keywords against each other. We also do SERP reviews manually to confirm findings. Again, validate as a human what you’re getting from tools.

In Closing

There’s a lot of power in what you can reclaim in time and dollars, leveraging automation, deeper tools use, and the power of AI for SEO. And, you probably detected a theme where, in pretty much everything you do, there have to be solid inputs in order to get useful outputs, which also require human validation and experience to trust.

Regardless of where you are with automation, the goal of being able to do more with less, scale tasks, and not do manual tasks that might have low return on investment is a great way to determine where you should consider doing more with tech and less manual work.

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Featured Image: ArtEternal/Shutterstock