u/arjun_rao7

Google’s new “Intelligent Search Box” feels like a shift from keyword-based SEO to intent-based SEO.

If users start searching conversationally with prompts, images, and videos instead of short keywords - will exact-match keywords matter less now?

Curious how everyone sees this changing SEO strategies.

Google just pushed a massive update to GA4 that automatically categorizes traffic from ChatGPT, Gemini, and Claude into a new AI Assistant channel.

For the last two years, we’ve been guessing how much traffic we were losing to LLMs. Now that the data is finally native in our dashboards, the "zero-click" reality is hitting hard.

how you guys are thinking about that?

I’m seeing so many tools and "AI optimization" checklists flagging a missing llms.txt file as a critical error.

Google has been pretty clear - they don't need it to crawl or understand your site for LLMs. It feels like the new "Meta Keywords" tag - total snake oil.

• Are you guys actually seeing any traffic/ranking benefit from adding one?
• Or is this just another case of devs over-engineering for a problem that doesn't exist?

I’ve got a couple of interviews lined up with some Big style agencies and enterprise brands. Looking at the JDs, I’m seeing a massive shift. It's no longer just about 'organic growth'; they’re asking for 'Citations in LLMs' and 'Generative Engine Visibility.'

For those who have interviewed for Senior or Director roles recently—how deep are they going into AI optimization (GEO)? Are they asking for specific case studies on how you got a brand cited in ChatGPT/Gemini, or are they still mostly focused on the traditional 'Core Web Vitals + Content Clusters' stack?

I want to know what I actually need to update in my 'expert' toolkit before I walk in.

Not looking for 'SEO is dead' hype, but actual operational shifts. Are you guys actually firing writers/analysts, or just using AI to make one person do the work of five? I’m seeing some agencies pivot to a 'headless' model where almost all content and technical auditing is automated. How are you pitching this to clients who still want that 'human touch'?

I’m seeing a lot of chatter that Google’s AI-driven spam filters just ignore bad links now. I have a client with a messy history and thousands of 'toxic' Semrush-flagged links. Half of me wants to disavow to be safe, the other half is worried that touching the disavow file in 2026 is just telling Google 'Hey, look at my spam!'

What’s your current agency standard for link audits?

We’re running a large recipe/product index and noticing specific items just... vanish from the search results. No 404s on the source, and the Algolia dashboard says the records are there, but the frontend query returns nothing.

Is anyone else seeing weirdness with their sync lately, or should I be looking for a logic error in our middleware/indexing script? Feels like a silent failure.

Need some real-world advice from people handling enterprise SEO.

I’m working on a pretty large retail/ecommerce site and GSC is honestly a mess right now. We’re seeing things like:

* 400k+ 404 pages
* Tons of “Crawled - currently not indexed”
* Large number of noindexed URLs
* Duplicate/canonical issues
* Soft 404s
* Some 5xx errors
* Redirected URLs still getting crawled

A lot of this is probably coming from faceted navigation, old URLs, filters, internal search pages, discontinued products, etc. The site has been around for years so URL clutter is massive.

What I’m trying to figure out is how experienced SEO teams actually approach this in practice.

Like when you open a client GSC account and see numbers like this, what’s the first thing you focus on? Do you start with crawl waste? Canonicals? Internal linking? Server logs? URL pruning?

Also curious how worried you get about huge 404 counts on enterprise sites. I’ve seen people say it’s normal at scale, while others treat it like a major technical SEO issue.

Would love to hear how people here prioritize and troubleshoot this stuff on large websites because most articles just repeat the same basic advice and don’t really explain what actually works in real projects.

Looking to connect with an experienced Arabic Wikipedia editor/contributor for a client project.

Need help reviewing Arabic article structure, citations, notability requirements, and submission process according to Arabic Wikipedia guidelines.

This is time-sensitive, so happy to discuss paid consultation/help if allowed.

Please DM or comment if you have experience working with Arabic Wikipedia articles.

Feels like AI Overviews care less about traditional local landing page tactics and more about:

• reviews
• mentions
• entity trust
• local discussions
• multi-platform signals

Curious what’s actually working for local visibility in AI search right now.

Been noticing an interesting pattern across AI search engines lately.

ChatGPT seems to pull heavily from sources like Wikipedia and Reddit.
AI Mode and AI Overviews appear to reference platforms like YouTube, LinkedIn, Facebook, Medium, and Yelp much more frequently.
Gemini also seems heavily influenced by Reddit, YouTube, and Wikipedia content.

So now I’m wondering:

As SEO professionals, should we still focus mainly on ranking webpages… or should we start structuring content distribution around the platforms AI engines actually cite and trust?

For example:

Long-form expertise on LinkedIn/Medium
Community visibility on Reddit
Video-first explanations on YouTube
Strong entity consistency across Wikipedia/business citations
UGC and discussion-based signals instead of only backlinks

Feels like “being mentioned everywhere” may become more important than just showing in Google.

Curious how others are adapting their SEO/content strategy for AI search discovery right now.

Seeing more SEOs talk about AI-assisted workflows lately - content briefs, topical maps, internal linking, entity extraction, even technical audits. Curious what people are genuinely using daily vs what still feels experimental or overhyped.

Curious what patterns people are seeing after AI search exploded this year.