Self-Hosted OpenSearch Search Engine with Vector Indexing

pure semantic search falls short whenever you need exact keyword matches. pairing SQLite and sqlite-vec with BM25 gives you fast keyword lookups alongside vector recall without adding external infrastructure.

Search code by meaning: keyword, dense and hybrid — controlled 1M-function test Sources show no 1M-function code-search corpus, hybrid-versus-BM25 ranking test or recall result, and separate storage costs from the 31.6% agent-output figure. https://lnkd.in/d49EkdFz

From page 5 to page 1 in three months. Here's the exact roadmap, no fluff. Month 1: full technical audit - indexing, crawl errors, site speed, duplicate content. Fixed the foundation before touching a single keyword. Month 2: content. Rewrote the pages already ranking on page 2-3 to actually answer the searcher's question completely, added the pages that didn't exist yet, and built the internal linking to connect them. Month 3: authority. Earned backlinks from directories and partners actually relevant to the niche, not volume-based link farms. Average position moved from 53 to 7.5 over that window. Nothing exotic - just doing the fundamentals in the right order instead of all at once. If your rankings have been stuck for months, which of these three - technical, content, or authority - have you actually addressed?

Your sitemap.xml is not the only sitemap you get to have. Build an HTML sitemap, an actual page listing every URL on your site, and link it from the footer so it lives on every page. Now Google has a second hub it can hit to grab all your URLs and reach full crawl depth. Same move for locations: a locations page that links out to every individual location, ten to twelve to fifteen links deep.

OKF vs Schema. Schema tells a search engine what your page is. OKF goes a step further by handing over the actual knowledge in Markdown, so an agent can read it, understand the context, and follow how it connects to the rest of your content. They’re not competing formats. Schema labels your page. OKF packages your knowledge. I wrote up the difference, including code examples for both and where each one fits. Link in the first comment. #GEO #AEO #AISearch

I am always thrilled and give a little "Woot!" - pinch myself then share my newest published article on Search Engine Land - grab it there are great tips in here you can use without tools or cash! https://lnkd.in/enYrRzpi

If you're exploring snippets tools, take a look at Litmus Community Snippets. A collection of HTML email snippets submitted by Litmus users. More: https://lnkd.in/ewSZRHjJ #emailgeeks #emailmarketingresources #emailtips #emailmarketing https://lnkd.in/ewSZRHjJ

Shipped: Screener X-Ray I built a Chrome extension for Screener.in because I felt the data was great, but the experience could be much better. So I built a layer on top of Screener that adds: → Research notes → Charts & visualisations → Connected financial statements → More meaningful calculations without misleading outputs It’s free to use, built for educational purposes, and runs completely locally. Not on the Chrome Web Store yet. Just download the ZIP from GitHub, load it as an unpacked extension, and you’re good to go. GitHub: https://lnkd.in/dn3vFRT5

Sometimes a website has two pages quietly competing for the same search term. Neither one wins clearly. Both rank a little worse than either would alone. It usually happens by accident; someone writes a new page without checking what already exists. Has your site ever had two pages competing like that without anyone noticing?

Keenable Search is now native to Baseten. You turn on hosted web search and page fetch in your Baseten request, Baseten runs the tool and passes the retrieved content back to the model. The model searches, reads, and keeps reasoning inside that same request. No separate search API key and agent loop to manage now. We want models to search more: to check an assumption instead of guessing, and to follow a lead before answering. Baseten is our first inference-platform partner, and context management, quality, and latency are what we'll keep working on.