/tech/ - Technical SEO

Been moving most of my heavy site audits over to Screaming Frog lately because Xenu just chokes on anything over a few thousand URLs. It's much better at handling the modern JS-heavy stuff without me having to manually configure every single crawler setting. If you're dealing with massive subdirectories, stick to the paid version so you don't hit that memory ceiling.
spoaderXenu is basically a relic at this point/spoiler

found another client site where they're wrapping every single breadcrumbitem inside its own nested list instead of just using one flat array. it's a total mess for the crawler and makes the lcp look spoilergarbage/spover.

Using byte range requests to pull parts of compressed VCF files directly from S3 sounds pretty efficient for avoiding massive transfers. I wonder if bcftools can handle the overhead once you scale up the number of concurrent Lambda functions hitting the same objects.

article: https://www.infoq.com/news/2026/10/csiro-serverless-genomic-variant/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global

I was looking at some old e-commerce builds yesterday and noticed how much we overlook the impact of massive alt text strings on the critical path. Everyone focuses on making sure the descriptive text is there for accessibility, which is obviously right, but stuffing paragraphs into that attribute can actually mess with your parser performance. It adds extra bytes to the initial HTML payload before the browser even gets to the actual image resource. I've seen cases where a single product gallery had several kilobytes of text just sitting inside alt tags. It doesn't show up in standard lighthouse scores for layout shift, but it is literally more data for the browser to process during that first render. We should try an experiment this week on any site with heavy media. Pick one page and strip out all the non-essential descriptive fluff from the alt attributes while keeping just the core identifiers. Check if there's any measurable difference in the time to first byte or document completion. It is a small tweak, but it helps keep the DOM light.

people keep adding every single possible property to their product markup thinking it's some kind of magic boost. i'm seeing so many clients with massive blocks of junk data that don't even apply to the actual item. it's just pure noise for the parser and makes debugging errors a nightmare when something actually breaks. if you aren't using the specific value, don't include the key at all. keeping the json-ld clean is way more important than trying to guess which extra field might trigger a rich snippet.

"additionalProperty": [{"name": "color", "value": "blue"},{"name": "size", "value": "large"}]

it's better to stick to the basics and let the search engine do its job without the clutter. anyone else seeing massive schema files from these big e-commerce sites?

jetoctopus is trying to sell this idea that you can just link gsc, ga4, and logs all on one view so clients don't get lost in status codes. it's basically saying stop sending them deep crawl depth charts and instead give them a dashboard they can poke at whenever.
>Every report type below already exists inside JetOctopus
it sounds nice but i've seen these "on demand" dashboards turn into another ticket for the dev team when something breaks. plus, if you don't include that one-line takeaway like it says, you're just sending them a bunch of meaningless charts again. building this once is fine, but managing the commentary every month sounds like a dream more manual work. does anyone actually use a live dashboard for clients without them asking a thousand questions?

found this here: https://jetoctopus.com/how-to-build-a-technical-seo/

wiz used 'gemini 4 argon' and 'gpt-5.6 sol' to basically gut php's memory safety. apparently it's a use-after-free mess that hits everything from wordpress to drupal since the engine is still stuck in c. seeing ai uncover flaws that sat there for like a decade makes me wonder if our entire tech stack is just one prompt away from a total wipeout lol.

article: https://thenewstack.io/ai-php2shell-disclosure-framework/

Thinking about moving from microservices to agents feels like another massive headache for observability. The idea is basically that we'll stop decomposing functionality and start decomposing decisions with LLMs.
>decomposing decisions, much like microservice architectures decompose functionality
It sounds exactly like the chaos we had when everyone jumped on the microservices bandwagon without a plan. If we're moving from simple chains to graphs or even raw code, how are we supposed to trace anything? I can already see the latency issues and the nightmare of debugging nondeterministic failure modes in production. It's probably going to be just another layer of complexity to manage.

https://www.infoq.com/articles/agentic-ai-architecture-article-series/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global

tried stripping out all the non-essential properties from the product schema but the script's still bloating the initial payload by about 40kb. it's making the lcp jump because the parser is choking on the massive string of nested object data.

{"@context": "https://schema.org","@type": "Product","additionalProperty": [ ... ]}

anyone found a way to prune these dynamically without breaking the rich result validation?

it's wild that argon managed to drop package import time by 21% just by running for eleven hours without any supervision. i'm skeptical it could actually trace all those cross-module references without getting lost in the noise of a real production repo.

more here: https://www.infoq.com/news/2026/10/google-argon-optimizes-adk/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global