For the past few years, the pitch has been that AI will write your content. But when you open most of the tools that purport to run your AEO and SEO end-to-end, you’ll likely be met with a chatbot that turns out competent, forgettable pages from whatever it soaked up in training.

That isn't the job. What an SEO and AEO team owns is a run of decisions: what's worth writing, what's already working, what slipped and why, and which pages need to earn a place on the Google results page and show up inside an AI answer. A team now has to clear both, and the decisions are only as good as what you know about the people you're writing for—what they type into Google, what they ask answer engines, and which sources come back for each.

That data is what Profound is built on. It's an agentic platform: a set of agents that run on the live SERP and AI citation data, each one taking a job an SEO and AEO team already owns and handing the work back for you to approve.

This piece walks through the specific agents these teams need, job by job.

Decide what to write, and defend it

Picking a quarter's topics commits a quarter of writing time. In the planning meeting, someone asks why these five topics and not five others, and the answer is a column of search volume and a “look at what competitors shipped!”

Those are important inputs, and they were enough when ranking on Google was the name of the game. However, they only speak to one surface. Search volume counts what people type into Google; competitor content shows you what ranks. Neither tells you what those same buyers are asking answer engines, or which sources the engines cite when they answer. So the plan is built to win the SERP, with no mention of whether those pages show up in AI search.

The AEO + SEO Research Report agent reports both surfaces together. For a given topic, it returns the keywords with volume and what's ranking for them on Google, plus how the answer engines respond to the same questions and which sources they cite. A keyword with strong search volume where three competitors already hold the top of the SERP is a hard, expensive fight. A set of questions the engines are answering by citing a rival, with no owned page anywhere in the results, is an opening a keyword tool would never surface, because the searches barely register as volume yet. You walk into a meeting able to say, "We're absent here, demand is climbing, and this is an organic gap, while that one is a citation gap." That's a plan you can defend.

Sizing a topic off a single head term undercounts it, because most demand sits in the sub-questions that form upstream of a branded search. The Pull SEO + AEO Keyword Volume agent reports search demand and answer-engine demand for a topic side by side, so the number you plan against reflects the whole cluster rather than the one keyword you already track.

Once you settle on a topic, the SERP Content Gap Analyzer takes the page you want to win with, scrapes it against the top ten organic results and the AI Overview citations for that query, and returns an information-gain report: the topics, formats, entities, and angles the winning results cover. It answers the oldest question in SEO—what does it actually take to outrank this page?—against the live SERP instead of a generic checklist, and it gives a specific list of what to add rather than "make it longer and build more links."

Sometimes the topic is worth pursuing, but a new page is the wrong approach. Publishing a second page on a topic you've already covered splits your authority and sets two of your own URLs against each other for the same ranking. The Cannibalization Checker scans your sitemap before you commission the piece, finds the existing pages that overlap the topic, and tells you whether to write, to strengthen what's already there, or to skip. Catching potential overlap before the brief goes out saves the writing time the losing page would have cost.

Turn a brief into a draft that respects your brand voice

Usually, content briefs are a topic, an audience, a word count, and a deadline. Everything that determines whether the page ranks and gets cited, which questions it has to answer and which ones competitors already own, is left for the writer to work out alone, and you see whether they got it right only after the page is live. The draft has the opposite problem. A general model produces something fluent that reads as if it came from anywhere, and a writer spends the afternoon putting your voice back into it line by line.

The Content Brief Creation agent puts that work into the brief. It builds it from the live SERP and citation data: the keywords the page has to rank for, the top-cited pages already answering the query, the recurring themes the winning results share, and what your current coverage misses. If the target is Google AI Mode specifically, the AI Mode Theme & Content Brief Builder reverse-engineers the themes Google AI Mode would surface for the query and briefs against those. The writer opens a document that already knows the SERP it's walking into and the questions it has to answer to be pulled into an AI answer.

Drafting is the Generate Article agent's job. It works from the top-ranking pages, the live results, and what you've already published, so the piece comes back structured for search and written in your register instead of the flat middle a general model reaches for. You edit it instead of rebuilding it.

Fix the pages that rank but never get cited

A page can hold the top organic spot and never show up in an AI answer, and the reason is mechanical. Google ranks pages; answer engines quote passages. An engine pulls a handful of candidate pages, then lifts the one chunk that answers the question on its own. If no single section of your page stands as a self-contained answer, there's nothing to lift, however strong the page is overall, and however well it ranks.

The Chunk-Level Citation Audit agent reads a page the way an engine does. It splits it into retrievable chunks and scores each one on whether it stands alone, answers first, and carries enough claim density and entity specificity to be worth quoting, so you can see which passages an engine could lift and which are buried under three paragraphs of throat-clearing before the answer.

The AEO Content Refresh agent then restructures sections with substance, but the wrong shape, and Optimize Page Headings rewrites the H2s, H3s, and H4s to match the questions people ask AI engines. None of this touches the ranking. The page holds its position on the SERP, but it also starts getting quoted because the fix targets the passage—the unit an engine quotes. A page that already ranks is the least expensive place to win a citation, since it has already cleared the harder bar of getting retrieved at all.

Do the technical work that decides whether pages get crawled and cited

The same jobs sit on the backlog for quarters: the metadata pass, the schema you meant to add, the internal links that were supposed to point authority at an important page. None of it is urgent on any given day, yet it all decides whether your pages are crawled, ranked, and cited. A page can be your best piece of writing and still lose on a robots.txt line nobody has read since it was committed.

Agents are for repetitive work nobody wants to do. Access comes first, since a crawler that can't reach a page makes the rest of the technical work moot. The Robots.txt & LLMs.txt Auditor fetches your domain's robots.txt and llms.txt, parses every user-agent rule, and classifies access for 25-plus known search and AI crawlers, which is how you catch the stale GPTBot block or the disallow that's been keeping you out of answers.

The Schema Markup Generator builds the structured data that helps search engines read a page. The Add Internal Links agent runs relevant internal links into an article so authority flows to the pages you're trying to rank, a job tedious enough by hand that it slips every sprint. The URL Slug Optimizer rewrites slugs for search and answer visibility. And Bulk Analysis on Lowest Performing Pages takes your fifty least-cited owned pages for a topic and separates the ones doing real work from the ones getting crawled and ignored, so a site-wide refresh goes where it pays.

All of the above represent some of the least interesting work on your plate—work that regenerates every quarter, which is exactly the profile of a job you should hand to an agent instead of a person.

Step into the agentic marketing era with Profound

Running an agent is the easy part. The hard part is knowing which one to run, on which page, and when. That's the job for AI Marketer (Aim).

Aim is an orchestrator. It watches how your brand performs in AI search, decides which problems are worth fixing first, and builds the right Agents to work on them. In practice, that looks like this:

  • Every week, Aim sends your team a ranked list of opportunities. Each one comes with the problem and the evidence behind it. It might be a page that stopped earning citations, or a topic where buyer questions are climbing but you have no content for.
  • You choose what to act on. Approve an opportunity, and Aim turns it into a project, building the Agents that will execute it.
  • It works from what your company knows about itself. Aim reads Context Manager, where Profound keeps your positioning, products, audience, and strategy. That way, its priorities match your business, and Agent outputs sound like your brand.
  • Nothing goes live without your approval. Your team reviews the work before publishing. Aim then tracks how each project performed and learns from what you approve, edit, or decline, so next week's list is an even better fit.

Your team keeps the one job no agent can do: holding a point of view worth citing. Aim takes care of the watching, prioritizing, and doing around it.

Run the motion your team already knows at a scale it never could by hand. Book a demo.

AI marketing agents for AEO and SEO FAQs

What's the difference between SEO and AEO, and do I need agents for both?

SEO is the work of ranking on a search results page: keywords, links, technical health, the pages Google puts in front of a searcher. AEO is the work of getting your content visible and cited inside an AI-generated answer, which turns on passage-level structure and which sources an engine trusts, not on ranking alone. They overlap, because being crawlable and ranking well makes you eligible to be pulled into an answer, but they're scored differently, and a page can win one and lose the other. Profound's agents cover both from one feed: the same tool that reads your SERP reads the answer-engine citations, so you're not running two disconnected workflows.

Won't AI agents just flood my site with generic content that hurts my rankings?

They will if you point them at mass production, and you shouldn't, because that's the content search engines deduplicate, and answer engines skip. These agents are built for the work that needs real data behind it: choosing topics from where you're actually under-ranked or under-cited, drafting from the live SERP and your own voice, and restructuring pages so a passage can be quoted. Used that way, agents raise the quality floor instead of lowering it.

Do I still need writers and SEOs if agents are doing the work?

Yes. The agents handle the parts that are repeatable and data-heavy: the gap analysis, the keyword pull, the brief, the first draft, the audits, the schema and metadata, and refresh passes. What they can't do is have the opinion, the firsthand experience, or the argument that makes a page worth ranking and worth citing in the first place. The trade is that your team spends its hours on that, not on rebuilding a generic draft or working through a metadata backlog.

How are agents different from using ChatGPT or a general AI writing tool for SEO?

A general tool writes from what the model learned in training. It has no idea what your buyers are searching this week, what's ranking for those terms, what they're asking answer engines, or who's getting cited. Profound's agents run on that live SERP and citation data, so the topic choices, briefs, and drafts are built from what's happening on both surfaces in real-time. That's the difference between a tool that produces plausible content and one that produces content aimed at the rankings and citations you're missing.

Does my Google ranking still matter if I'm optimizing to get cited by AI?

It's the foundation. Gemini and Google's AI surfaces retrieve from Google's index, so being crawlable, indexed, and ranking well is what makes you eligible to be pulled into an answer in the first place. Ranking just isn't the finish line anymore. A page can rank first and never be mentioned by AI if no passage on it answers the question cleanly, which is why the passage-level AEO work matters alongside the ranking work, not instead of it.