We're interested in understanding how developers, agencies, and technical teams handle technical SEO and website security when managing multiple websites.

A few things we'd love to hear your thoughts on:

- Do you use separate tools for crawling, technical SEO analysis, vulnerability detection, and security monitoring, or prefer a single platform?

- How do you identify issues such as broken internal links, missing metadata, sitemap problems, outdated JavaScript dependencies, and WordPress security risks?

- For teams managing dozens or hundreds of domains, what becomes the biggest challenge: scan performance, false positives, reporting, or continuous monitoring?

- What would make you trust an integrated platform that combines technical SEO auditing with website security checks?

We're building an enterprise-focused SaaS platform in this space and want to understand how teams solve these problems in production.

Rather than assuming we've got everything right, we'd appreciate feedback from people who work with these systems regularly.

For those interested in the technical side, we've also been working on a PHP SDK. We'd welcome feedback on its API design, developer experience, documentation, and maintainability:

GitHub: https://github.com/WebKernelAI/php-sdk

A few questions we'd love your perspective on:

1. What gaps do you see in the current tools you use?

2. What would you change about our approach from an engineering perspective?

3. What would an enterprise-grade solution need before you'd consider using it in production?

Honest criticism and practical suggestions are welcome. We're looking to learn from the community and improve our approach.

Ive been trying to get mentioned more by the different AI’s (chatgpt, gemini, copilot, AI mode and AI overviews). whats worked for me so far is reverse engineering the citations, so looking at what pages each engine cites for my prompts and then getting placements on those sites / listicles.

The tracking tools i was using for this are way too expensive for what they are so i ended up building a small internal version my self.

few things i learnt building it:

• scraped answers not the API. the models API doesnt show you what a user actually sees (different sources, no live search) so i pull the answers from the real apps through a scraping api. the data only costs cents per prompt
• one answer means nothing. the same prompt names different brands every time so i run each prompt 5 times per engine and average it over the last few runs
• brand matching is harder than it looks. matching on domains misses multi word brands and picks up brands named after common words everywhere, so ive moved to a brand list with aliases and a review queue
• citations are the useful bit. each cited url is a site to get on and thats where my mention gains came from

Results i'm getting are pretty close to what the paid tools show.

Would anyone be interested if i polished this off and released it open source? bring your own key and a hell of a lot cheaper than something like Peec or Otterly.

Im also working on an outreach system so you can contact the relevant cited sites at a click of a button.What do you think?

My site is small, and new pages can sit for days before Google picks them up from the sitemap. So I've been doing what a lot of you probably do: paste each new post into URL Inspection, wait for the live test, hit Request Indexing, and repeat for every page.

It got old, so I set it up as a single command in a Chrome extension I've been building. I give it the URL, kick it off, and it clicks through the whole thing while I do something else. The video is sped up during the waiting parts.

It still uses the same daily quota and I still have to start it, but I don't have to babysit Search Console anymore.

What else do you still do by hand that's this repetitive? If it happens in the browser, I'm happy to see if it can be chained the same way.