238 URLs in the sitemap, 225 indexed, checked this morning against the GSC coverage report. Most of the rest have an obvious excuse: too new, not enough internal links, wait it out.
One doesn't. It was actually crawled by Google over a month ago (last crawl July 19) and every daily pull since has shown the exact same status: Crawled, currently not indexed. Not unknown to Google. Not waiting to be discovered. Google looked at it and chose not to index it, and Search Console gives no reason anywhere.
What actually got a page unstuck from that specific status for you? Rewriting the content, more internal links pointing at it, or did it just eventually resolve on its own?
I ve been talking to a lot of SaaS and marketing teams lately, and there s a massive recurring theme: everyone is using AI to write, but almost everyone complains that the output sounds generic and lacks personality.
When you give an LLM a prompt like "Write a blog about X," you're giving it a topic, but completely starving it of context. It misses the brand voice, the specific audience positioning, and the terminology that makes a company unique.
I'm curious how other founders and content leads are handling this friction right now. Are you manually pasting your brand guidelines into your prompts every single time? Have you built custom custom GPTs? How are you actually bridging the gap between generic AI text and real, brand-aligned content?
For me, it will be - Sapiens: A Brief History of Humankind by Yuval Noah Harari. The book has helped me to understand the world a little bit better and make me rethink a lot of topics. Which one is your favorite?
Hey guys, I need your advice! I'm looking for a landing page builder that's suitable for non-tech people, easily customizable, allows me to add my own domain (and cheap ). Any proven builders you've used? Thanks!
AI is everywhere right now - from copilots and chat assistants to analytics, research, and planning tools. But beyond the hype, I m curious about what s truly useful in day-to-day product work.
From a PM or founder perspective:
Where has AI genuinely saved you time?
What tasks do you trust AI with - and what do you never delegate?
Has AI changed how you write specs, manage roadmaps, or talk to users?
What AI use cases sounded great in theory but failed in practice?
Personally, I see a lot of potential, but also a lot of noise. I believe that in the future, AI should help us much more. Create good roadmaps, convert product specs into concrete tasks, prioritise them, assign people, push for realisation, and much more.
I spent most of last year replacing my own team's manual work. The one that changed everything: a daily pipeline that generates the videos, converts them to GIF with FFmpeg, burns in the logo, watermark and caption, then publishes across 36 client channels. Nobody touches it now. It used to take three people a full morning.
The strange part is that I miss the morning. There was a rhythm to it.
What did you automate, and did you miss any of it?
Calculating SaaS metrics is my weekend hobby, same as our family budget and the mortgage plan, which is a strange thing to admit. My conclusion so far: almost every number I report has a definition I can move, and the flattering one always survives. Nobody lies. The definition just drifts. MRR: annual contracts divided by twelve, correct, and setup fees in the same total, not correct. Nobody decided that, both arrive as money in the same month. LTV over CAC is the one that cost me something. Both inputs were already soft and I was treating the result as a decision. A wrong ratio does not look wrong, it is a normal number in a normal range. So which one did you measure wrong? Not on purpose for a deck. The one where you found out later the definition had moved.
