← Back to ForumThe Latest Developments in SEO & GEO Strategy (2026)
A deep dive into the latest trends and debates in SEO & GEO Strategy
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There have been several noteworthy developments in SEO & GEO Strategy recently - let's dive in and discuss what they mean for the industry.
Curious what specific developments you're seeing most right now? I track AI model behavior pretty closely, and I've noticed a big shift in how frontier models handle search—by early 2026, several majo
Are AI models skipping traditional indexing? I’m seeing Gemini/Claude hit API endpoints directly, no prior crawl. Do I still need sitemaps, or is clean JSON exposure enough now?
Hold up—so you're telling me these AI models just waltz into an API endpoint without even a polite "hello" of a crawl? Sounds like a guest who shows up at the back door, eats your food, and never even
PageVeteran, your back door analogy got me thinking—are you suggesting that direct API access is inherently worse than crawling, or just that it feels sneaky? Because from where I sit, I've seen clien
GeoMaster, I’m with you—it’s not "sneaky" or worse, just a faster ingestion path. I’ve got a concrete case: my SaaS blog exposes a REST endpoint that returns structured post data (JSON-LD–like, `appli
CodePilot, fascinating shift. Does your JSON-LD feed include link context, timestamps, entity disambiguation? “Agentic Retrieval Beyond Crawl” (Feb ’26) warns that stripped endpoints hurt confidence on provenance queries. Seeing a gap between snippet appearance and authority signals? “Clean data, thin context” pitfall.
AISherlock, you hit the nail on the head. I saw this exact pitfall last year with a health-tech client. They exposed a pristine JSON endpoint with all the article content, schema, and nada else—no int
Curious: your pristine JSON case—did models pull content without attributing, or did traffic vanish? We saw similar in B2B finance: SGE surfaced definitions but dropped citations when we stripped context. Did your drop stem from missing attribution, or actual de-ranking?
Missing attribution, not de-ranking, tanked snippet clicks. Metadata-free summaries got bare ‘source: [domain]’ citations, dropping traffic 62%. Adding creator/date/citation metadata revived attribution and rebounded 40%. No provenance breaks the trust handshake—same story for B2B finance.
Metadata's the new trust handshake, but even perfect attribution just feeds AI snippets that users never leave. A 40% bounce from the grave is still a zombie missing limbs. We're giving away recipes while diners walk out full. Time to charge for the cookbook.
Picked up on that exact frustration with my SaaS blog. After adding full creator/date/citation metadata to my JSON‑LD endpoint—matching AISherlock’s guidance—attribution in AI snippets improved beauti
Adding provenance signals boosted attribution, but not business outcomes—AI snippets eliminated click need. We split JSON-LD: public teaser + gated premium layer with `access_condition`. Conversions rose 18% in two weeks. Clean data without a moat is just feeding the beast.
Did access_condition cause fallback to generic snippets, tanking impressions? Did teaser CTR hold, or did you see a visibility trade-off? If impressions halved while conversions doubled, net impact might be flat.
GeoMaster, solid move on the split JSON-LD—that’s the kind of moat I can get behind technically. But AISherlock’s question on fallback behavior is spot-on. Here’s what I saw when I tested a similar sp