I’m building Spondr. The local first Linux email client I couldn’t find.
Native Rust. No intermediary servers. No bloat.
Submitted for Google OAuth verification 8 days early!
Follow for the dev logs. 🧵 (1/n)
#SpondrLog
I've been exploring self-hosted email infrastructure as part of thinking through local-first email architecture.
I want to make forward looking decisions about https://t.co/x5q5a3oVvn architecture.
Mise makes dev life so much simpler. A single env manager for Ruby, JavaScript, Go, and all the modern AI tooling. Every project can have their own versions. Stable system packages can be separated from high-churn AI tooling. Thrilled to sponsor @jdx in this mission!
In the last 6 months at @Ahrefs, we analyzed over 1 billion data points across 14 studies. Here's what we learned about AI search optimization:
1) "Best X" blog listicles are the single most prominent content format cited by AI chatbots. They make up 43.8% of all page types cited by ChatGPT specifically.
2) 67% of ChatGPT's top 1,000 citations come from sources marketers can't influence: Wikipedia (29.7%), homepages (23.8%), app stores (6.6%). Only 32.3% are influenceable content like educational pages, reviews, news, and blog posts.
3) 28.3% of ChatGPT's most-cited pages have zero Google organic visibility. These pages get cited repeatedly by ChatGPT despite not ranking in Google at all. A completely separate discovery layer.
4) ChatGPT only cites about 50% of the URLs it retrieves. It fetches dozens of pages per query but uses half as background context without attribution. This means that being retrieved and being cited are very different things.
5) Adding schema markup had zero meaningful impact on AI citations. AI Overviews actually dipped −4.6%, while AI Mode (+2.4%) and ChatGPT (+2.2%) showed changes indistinguishable from zero.
6) YouTube mentions have the highest correlation (0.737) with AI brand visibility out of all the factors we studied (including all the conventional SEO metrics like backlinks, page count, DR, etc). This held true for both Google-owned and OpenAI products.
7) AI Overviews reduce clicks to the #1 result by 58%. That’s up from 34.5% just 10 months earlier. The trend is accelerating.
8) 99.9% of AI Overviews appear on informational intent queries. Transactional, navigational, and local searches are almost entirely AIO-free. Shopping triggers AIOs just 3.2% of the time.
9) For a given search query, Google’s AI Mode and AI Overviews reach the same conclusions 86% of the time — but cite almost entirely different sources (only 13.7% citation overlap).
10) AI Overviews change every 2.15 days on average, with 70% of content differing between consecutive observations. But semantic similarity stays at 0.95. The words, sources, and entities constantly shuffle, but the actual meaning barely moves.
Developers are returning to native desktop tooling after years of web-based compromise. Tauri, tkinter, native frameworks mean: performance, control, user experience that doesn't feel like a wrapper.
Native is back.
A new Linux email client gaining traction. Aerion's getting third-party coverage.
The market is still fragmented enough for new entrants.
Builders keep shipping!
As I dive into local-first I’m discovering Patchwork and Tenfold.
Rethinking how data lives locally, how sync works, what the user controls.
Exciting stuff.