Discover Core Update, AI Mode Ads & Crawl Policy – SEO Pulse

Google’s search ecosystem is evolving at a fast rate. The past week saw the company roll out a new type of core update focused on discovery, outlining how it will monetize AI search and reject controversial content format for bots.

This update targets crawl inefficiencies with important industry players sharing data on how AI search impacts visibility.

This development collectively illustrates how search, discovery and AI are no longer interchangeable in performance measurement or optimization.

Here are 4 stories that impacted marketers, content teams and technical SEO professionals.

1.  Google Releases its First Discover-Only Core Update

Google launched the February 2026 Discover core update, marking a first for the company. It publicly announced a core algorithm targeting only the Discover feed and not the standard search results.

The rollout started on February 5 for English language users in the US and will take up to two weeks to fully complete before it expands globally.

Discover is a personalized feed with recommended content that appears on mobile and in the Google app and it has grown in importance as a traffic source, especially for news and publisher sites.

This update is designed in such a way that it improves the quality of experiences in Discover, favoring relevant, timely and locally meaningful content while de-stressing lower value signals like clickbait.

Why This Matters

In the past, Discover adjustments were folded into broader core updates affecting all of Google Search.

Now that Discover gets its own core update, changes in in its performance can occur independently of search rankings.

For those organizations that depend on Discover traffic, particularly news publishers and content creators, it means you must monitor Discover metrics separately in tools like Search Console.

This to see what’s influencing user engagement. For instance, if the traffic from Discover drops while Search clicks remain stable, triggering a Discover-specific shift rather than an overall algorithm penalty.

Historically, Discover has accounted for a large chunk of traffic for many news sites, helping raise the stakes of this change.

2.  Alphabet’s Q4 Results Reveal AI Mode Ad Strategy

In its Q4 2025 earnings call, Alphabet revealed a detailed plan to monetize its new AI-driven search experience called AI Mode.

This is a significant departure from traditional keyword advertising. Its search revenue grew 17% to $63 billion in the quarter, indicating that monetization remains critical as user behavior transitions.

According to Google leadership, AI Mode queries are roughly three times longer than typical keyword searches. This creates a new and valuable space for advertising.

Longer, conversational sessions provide more opportunities to show ads. These include tests of ads placed directly below AI Mode responses.

Why This Matters:

Developers and SEO specialists debate whether to serve simplified content formats like Markdown to LLM crawlers, thereby reducing token usage to improve processing efficiency.

This week, Google Search advocate John Muller publicly rejected this calling it a “stupid idea” on social platforms, raising technical concerns about its viability.

Mueller argues that Markdown files lack the structural cues like internal linking, headers, and semantic data that most bots rely on to understand how content connects and ranks.

If bots treated Markdown as a simple text file, they could easily miss key navigation paths and hierarchical signals making this practice less effective for discovery and indexing.

Why This Matters

With generative AI, some practitioners are experimenting with alternative delivery formats like Markdown or JSON for AI crawlers.

They are doing this especially when looking to reduce processing costs or payload sizes.

Mueller’s says that this overlooks fundamental web architecture principles and could harm the very discovery outcomes developers hope to optimize.

Instead, the guidance should be to focus on well-structured HTML with clean semantic markup and documented structured data schemas that both traditional search bots and AI crawlers can interpret accurately.

This is near to Google’s broader messaging that content should be designed primarily for users, with bots serving the same version rather than specialized variants.

3.  Google Files Bugs Against WooCommerce Plugins Over Crawl Waste

Technical SEO took center stage as Google’s search relations teams filed bugs against certain WordPress plugins.

This is true for WooCommerce extensions for generating unnecessary crawlable URLs. These URLs arise from action parameters like add-to-cart links, which can balloon the number of pages Googlebot attempts to crawl.

Rather than expecting individual site owners to fix this increase one site at a time, Google has taken the unusual step of working directly with plugin developers to resolve issues at the source.

Sometimes, developers have already shipped fixes to constrain problematic URL parameters and prevent Googlebot from treating action links as discrete pages to crawl.

Why This Matters:

Crawl budget has always mattered in SEO, but it’s now even more important because websites are being crawled by search bots as well as AI and LLM bots.

When bots waste time crawling add-to-cart or checkout URLs, important pages can take longer to get indexed and crawl data can become confusing or inaccurate.

Ecommerce sites using WooCommerce should regularly review their URLs, block or canonicalize unnecessary parameters. This is needed to watch crawl stats in Search Console to avoid wasted crawling.

4.  LinkedIn Reports AI Search Visibility Shifts

In a latest shift, LinkedIn shared internal findings that showed that AI-powered search surfaces can dramatically reduce non-brand organic traffic, even when rankings remain stable.

On a subset of B2B topics, LinkedIn reported that non-brand awareness traffic dropped by up to 60%. This was after AI overviews and generative search features replaced traditional search journeys.

This suggests that the old “search to click to website” model is no longer the dominant path for discovery. AI Overviews synthesize answers, reducing the need for clicks to the original source, especially for awareness-level queries where users seek summary information.

LinkedIn also stated that structured content or content with named authors, visible credentials, and clear publication dates tended to perform better in AI citations.

This underlines the emerging importance of authority signals and structured data in contexts where AI engines decide which content to present or reference.

Why This Matters

This goes against traditional SEO thinking. Ranking well may no longer guarantee visibility or traffic if AI systems answer the query directly without delivering a click.

Content teams now must think in terms of AI discoverability and citation probability, not just ranking positions.

Giving Rise to a Fragmented Visibility Ecosystem

All the week’s development reveals a much broader theme – the visibility of a fractured digital ecosystem. Google’s Discover feed now has its won algorithm update cycle separate from classic search.

AI Mode introduces new monetization layers and reward signals. Technical showdown over content formats for bots highlights the ongoing tension between optimization and web fundamentals.

While crawl efficiency issues are being addressed at the platform level. LinkedIn data now also shows AI search changes user behavior and referral patterns too.

Where a single dashboard once provided a reliable view of performance, brands today must monitor multiple discovery surfaces.

Right from Search and Discover to AI Mode and LLM-driven insights-each has its own signals, ranking systems, and engagement metrics.