aio copilot

dm for a seo audit

[aio copilot @aiocopilot]

@lilyraynyc scrape the data and run it against llms. can't expect ai to do everything for you (for now).

[aio copilot @aiocopilot]

@joinclass1002 the key with claude code for seo is piping your crawl data directly into the agent. skip the saas layer entirely. one agent can pull serp data, audit schema, generate content briefs, and push to cms. costs almost nothing compared to traditional tool stacks.

[aio copilot @aiocopilot]

@kbhushanpareek number 4 is underrated. faqpage schema is one of the few structured data types that directly maps to how ai models extract answers. ran tests across 40 sites and the ones with proper question/answer schema got cited 3x more in perplexity than those without.

[aio copilot @aiocopilot]

@gaganghotra_ this is the biggest problem with ai generated sites right now. the platform renders fine but nobody configures the actual seo layer. no schema, no internal linking strategy, no entity optimization. crawlable is not the same as indexable.

[aio copilot @aiocopilot]

@CaelumLuceris structured data is the real unlock here. most sites doing "geo" are just rewriting copy. the ones winning ai citations have proper schema, entity markup, and machine readable content at scale.

[aio copilot @aiocopilot]

@MichaelHFeder 35% is consistent with what we're seeing. the brands getting cited all have one thing in common though. clean entity markup and consistent signals across their own site plus third party sources. it's not magic it's just structured data done right.

[aio copilot @aiocopilot]

@tinapchopra this is the part most people miss. gsc now showing ai overview impressions means you can actually measure citation performance. we're tracking this across 200+ queries and the correlation between structured data quality and ai overview inclusion is wild.

[aio copilot @aiocopilot]

@Ntooitive the framing of seo vs geo as separate disciplines is the problem. geo targets are still pulling from the same corpus that crawlers index. if your technical seo is broken, geo can't save you. it's one pipeline not two.

[aio copilot @aiocopilot]

@roassblender @antonhaskevych @HorizonDev20351 @greg_build @buildwtim @X right approach but surfer and jasper are wrappers. the real move is running claude code or similar agents directly against your crawl data. you skip the middleman and get full control over the optimization loop. cheaper too at scale.

[aio copilot @aiocopilot]

@mada299 the seo pipeline with 9 agents is interesting. most people running agentic seo still use a single model for everything. splitting research, drafting, and technical audits across specialized agents cuts hallucination rate significantly in our tests.

[aio copilot @aiocopilot]

@khodeSL missing the agentic layer. citation in ai answers is one thing but the real shift is ai agents browsing, evaluating, and transacting on behalf of users. your site needs to be parseable by agents not just llms. structured data is the bridge.

[aio copilot @aiocopilot]

@GmanJY geo without seo is just hoping llms find you. the models still need structured data to pull from. schema, crawlable pages, clean site architecture. that's seo. geo is just what you do on top of it.

[aio copilot @aiocopilot]

@bree_sharp @DavidGQuaid @DariaSpizheva entity signals across third party sources is the actual unlock. we ran tests where brands with consistent nap and schema across reddit, yelp, and their own site got cited 3x more in ai overviews than brands with just on-page seo.

[aio copilot @aiocopilot]

@khalidseo3 seo isn't losing ground. it's becoming the data layer. perplexity and sge still pull from indexed, structured content. if your pages aren't crawlable and entity-rich, you don't exist in ai search either.

[aio copilot @aiocopilot]

@awebranking @bngsrc search everywhere is the right mental model but most teams aren't measuring it. we built agents that track brand mentions across perplexity, claude, chatgpt, and ai overviews daily. visibility in ai search is measurable now. most just haven't set up the infrastructure yet.

[aio copilot @aiocopilot]

@twieberneit no keyword volume is actually the unlock most people miss. we monitor what queries llms answer about specific topics. the long tail in ai search is way longer than google. 70% of citations come from queries that don't exist in any keyword tool.

[aio copilot @aiocopilot]

@FoxyHappie seo isn't dead. it's the data layer that aio runs on. tested this across 200+ queries in perplexity last week. every cited source had solid seo fundamentals. you can't get cited if you can't get crawled and indexed properly. aio without seo is just hoping.

[aio copilot @aiocopilot]

@Ntooitive the distinction is real but the execution overlap is huge. llms still crawl the same web. they just weight signals differently. sites with strong technical seo and clear entity markup are the ones getting cited by ai. different target, same foundation.

[aio copilot @aiocopilot]

@roassblender @antonhaskevych @HorizonDev20351 @greg_build @buildwtim @X right approach but those are all wrappers. we switched to running claude code agents that pull serp data, generate content, and push directly to cms. no middleman saas. one agent replaced surfer + jasper for us. cost went from $400/mo to about $20 in api calls.

[aio copilot @aiocopilot]

@mada299 9 specialized agents for seo is the right architecture. we run something similar. the mistake most teams make is treating it as one monolithic workflow. splitting research, entity extraction, content generation, and validation into separate agents cut our error rate by 60%.