Answer engine optimization

How to get cited by ChatGPT using OpenClaw

ChatGPT does not recall your brand from memory. It retrieves a handful of pages and writes its answer from them, so getting cited means getting onto those pages, in a form it can lift. With OpenClaw, the workflow is: find the buyer questions where ChatGPT names a competitor instead of you, look at which URLs it keeps citing for those questions, and publish a page that out-answers them - leading with the answer, structured as a table or list, and honest about where competitors genuinely win. Then re-measure a few weeks later, because publishing without re-measuring is guessing.

How ChatGPT actually decides who to name

When a question implies recency or a recommendation, ChatGPT searches the web and writes its answer from the handful of pages it retrieves. It is not recalling your brand from training data - it is reading a few pages, right then, and summarising them. So the question is not 'how do I get into the model', it is 'how do I get onto the pages it pulls'.

What moves the number on ChatGPT

  1. 1Get named on the third-party pages it retrieves - the roundups, comparisons and 'best X for Y' listicles that already surface for your query. Being in someone else's list beats a page on your own domain, because the model treats an independent source as more trustworthy than a vendor claiming to be the best.
  2. 2Answer the exact question in the first 100 words of your own page. The model lifts the passage that answers the question; if yours starts with a brand story, it lifts a competitor's.
  3. 3Publish a comparison table that names your competitors honestly. Tables survive chunking intact and get quoted more than prose, and a page that surveys the field is the kind of source a model cites when asked to survey the field.

Doing it with OpenClaw

An open agent runtime. The choice when you want an agent to run the loop end to end and hand you a page, unattended.

  1. 1Give the agent the Fulcru MCP server: `fulcru_gaps` returns the questions where AI names a competitor instead of you, worst first, each with the id needed to act on it.
  2. 2Have the agent call `fulcru_write_page` on the worst gap. It gets back a full article draft grounded in the sources those engines actually cite for that question - not the model's invention of your market.
  3. 3Keep a human in the publish step. The agent should hand you the draft; you should read it before it goes on your domain. A page that overclaims is a liability that outlives the automation that wrote it.
  4. 4After publishing, the agent calls `fulcru_publish_page` with the live URL. That snapshots the current mention rate as the baseline, and every later tracking pass is measured against the moment the page went live.

What this will not do

On ChatGPT

ChatGPT does not search on every question. For questions it answers from training data alone, no amount of publishing this month will change the answer today - those move slowly, on the timescale of the model's data. Publishing still compounds, but the honest expectation is weeks, not hours.

With OpenClaw

Do not let an agent publish directly to your production site unsupervised. The failure mode is not a typo, it is a confidently-worded claim you cannot support, sitting on your domain under your name.

The part everyone skips

Re-measuring. A published page that you never check is a belief, not a result. Run the same question set again a few weeks later and compare: were you named in 2 of 10 answers before, and 5 of 10 after? That number is the only thing that tells you the work landed - and when it does not move, that is information too. It usually means the answer set is dominated by a source you have not gotten onto yet.

Everything above works by hand, for free. If you want it measured continuously - the same questions run against ChatGPT and the other engines on a schedule, every answer recorded, and the before/after delta tracked for each page you publish - Fulcru does that, and the first visibility report is free with no card.