🟣 Underrated #TechSEO Tip I see this constantly. The mobile menu's links only get injected after someone taps the hamburger icon. Google indexes the mobile version and doesn't tap anything. No links in the rendered HTML means no navigation for Google. Check the rendered HTML in URL Inspection. Your nav should be there as plain `<a href>` links, even with the menu closed.

🟣 Underrated #TechSEO Tip Serving Googlebot different content than users is cloaking. It can end in a manual action. Dynamic rendering isn't cloaking if the content matches, but Google calls it a workaround and no longer recommends it. The rule is simple. What Googlebot gets must match what users get. SSR or static generation solves it cleanly.

Chrome 155 adds support for JPEG XL (.jxl) → goo.gle/4yYpSjW Expect 30-50% smaller file sizes than traditional JPEGs, native HDR, progressive rendering, and lossless JPEG transcoding. Under the hood, Chrome uses jxl-rs, a pure Rust decoder built for maximum memory safety and performance.

🟣 Underrated #TechSEO Tip I recently worked with a multilingual site where only the English version ranked. German and Spanish? Invisible. Zero traffic. The cause was broken hreflang. Page A pointed to page B. Page B never pointed back. Google silently ignores the whole setup when that happens. And a missing sitemap killed it completely. No error in Search Console. No warning. You're losing entire markets, and Google won't tell you. Run Screaming Frog or Ahrefs Site Audit to catch missing return tags. Without them, you're flying blind.

🟣 #TechSEO Myth Debunked "Multiple H1 tags will hurt your rankings." Not really. Not alone. Google has confirmed that multiple H1s on a page are "completely fine." One H1 is still a best practice for clarity. What actually matters is a clean heading structure that reflects your content hierarchy. Not the count of any single tag. Still, I'd avoid it. Google is only one system. There are plenty of others, and other reasons to stick with one H1.

🟣 Underrated #TechSEO Tip AI crawlers make way fewer requests than Googlebot. If your content isn't reachable in a shallow crawl, AI models will never find it. That page buried five clicks deep from your homepage? GPTBot won't get there. Keep your important content within 2–3 clicks from the homepage. Flat architecture wins for AI visibility.

🟣 Underrated #TechSEO Tip Everyone talks about crawl budget. Nobody talks about "render budget". Google might fetch all your JS-heavy pages but only render a fraction of them. Rendering delays can stretch to days on large sites. Cut JavaScript dependency on your most important pages. Less rendering work for Google means faster indexing for you.

I spotted it today in @Ahrefs. All fetches of SERP for a query were completely different. All 10 links. Every time.

🟣 Underrated #TechSEO Tip Your sitemap has lastmod dates. Most sites set every page to today. Google sees that and stops trusting your dates entirely. Only update lastmod when content actually changes. Accurate dates tell Google what to recrawl first. Fake dates tell Google to ignore you.

🟣 #TechSEO Myth Debunked "Longer content always ranks better." Length doesn't determine rankings. Relevance and depth do. A 500-word page that nails the answer will outrank a 3,000-word article that buries it in paragraph 15. Write what the topic needs. If 800 words covers it, adding 2,000 more just makes it worse.

🟣 Underrated #TechSEO Tip Your site probably serves both www and non-www versions. And HTTP and HTTPS versions. That's four versions of every URL. Before you even count trailing slashes or uppercase letters. Redirect all versions to one canonical URL. One URL per page. No exceptions.

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

🟣 Underrated #TechSEO Tip Soft 404s are pages returning a 200 status while showing "Page not found" or empty content. Google flags them in Search Console. Most people ignore the report. These pages waste crawl budget and signal low quality. Fix the status codes, redirect them, or improve them overall.

🟣 Underrated #TechSEO Tip Your Lighthouse score is not what Google uses to rank you. Google uses real user data from CrUX – actual visitors on actual devices. Sites scoring 95 in lab tools can completely fail Core Web Vitals in the field. Their real users are on slow connections and cheap phones. Stop obsessing over Lighthouse. Open Search Console → Core Web Vitals. That's the number that matters.

🟣 Underrated #TechSEO Tip Your XML sitemap file size matters. If it exceeds 50MB uncompressed or 50,000 URLs, Google won't process it. Full stop. Split large sitemaps into smaller files and reference them from a sitemap index. Here's the part people miss. The 50MB limit is on the uncompressed size. You can gzip a 60MB sitemap down to 5MB all you want. It still violates the limit.

🟣 Underrated #TechSEO Tip Your image alt text isn't just for accessibility. Google uses it to understand image content. AI crawlers rely on it even more because they process text, not pixels. A product image with `alt="IMG_3847.jpg"` tells AI models nothing about your product. Write descriptive, specific alt text. It helps Google Image Search and AI content understanding. Think of it as writing for machines, not just screen readers.

Introducing Claude Haiku 5.5: the cheapest, fastest, and most capable small model we’ve ever released. On average, it costs around 75% less to run than Claude Haiku 4.5.