r/AEOWorkflows

i’m trying to stop treating every missed ai prompt like it has the same value.

we had hundreds of missed prompts, and my first reaction was basically:

“ok we need to fix all of this”

but that gets messy fast.

so now i’m grouping missed prompts into buckets:

1. high intent comparison example: “best x for startups”, “x vs y”, “alternatives to y”
2. use-case prompts example: “tool for doing x”, “how to solve y”
3. proof/source gaps ai trusts reddit, listicles, review sites, partner pages, docs, etc. more than our own site
4. bad-fit/noise prompts stuff we probably should not care about yet

then for each bucket i ask:

do we already have a page for this?
does the page answer the prompt directly?
who is ai citing instead?
is the fix on-site content or third-party proof?
is this worth fixing this week?

the main change for me is not “track more prompts.”

it’s turning missed prompts into a small weekly action list.

right now my rule is: pick 3 fixes per week, ship them, then re-check the same prompts later.

are you fixing by volume, intent, competitor gap, or citation/source gap?

The more I look at AI answers, the more it feels like the answer engines trust what the web says around a brand.

Reviews, listicles, backlinks, Reddit threads, comparison pages, docs, partner pages, mentions.

Maybe the workflow is not just "optimize pages for AI."

IMO, it's Find who AI trusts, Find why they trust them, Build the missing proof around your brand

What authority signals are people seeing matter most?

i’ve been trying to make aeo/geo less random.

my old way was basically:

think of topics
write articles
hope ai/search picks them up

now i’m doing it more like this inside infuseos:

connect google search console
connect sanity
ask the agent to find pages/queries with impressions but weak clicks
turn those into buyer-style article ideas
write the draft
map it to my sanity schema
create/update the sanity draft
then validate before publishing

the prompt is usually something like:

“use my search console data to find one query cluster with high impressions / low ctr or position 8-20. turn it into a helpful article for a buyer, include seo title, meta description, slug, faqs, direct answer, and internal link ideas. then create it as a sanity draft.”

the part i like is sanity is not just “paste markdown somewhere.”

the agent checks the live sanity schema first, maps the right fields, handles seo fields separately if the schema has them, and validates the draft before it goes live.

then i can turn the same thing into a weekly automation:

every week:
find new gsc opportunities
pick the best content gap
create a sanity draft
tell me what changed / what got created

not saying this is some huge win yet, but we went from basically 0% ai visibility to almost 1% lol.

small number, but at least the workflow is moving something.