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We cannot predict the AI future, but we can invent it. One month ago I attended LangChain Interrupt in SF (thanks Harrison Chase Julia Schottenstein and team for organizing) and it was eye-opening. Eye-opening to see how far along some teams had gotten building agentic applications in

Just explored pgvectorscale by Timescale (now TigerData). A wrapper around pgvector with optimizations. Crazy how postgres is slowly replacing dedicated vector DBs like pinecone or qdrant. Having your vector search + relational data in one place is such an ease.

kind of sucks that cl**ly and certain other startups are what's representing gen z in the startup world so many better startups and gen z founders should be the face disappointing

seriously why are you not using pgvector and Timescale (now TigerData)'s pgvectorscale

Let's. Go. 🐯🚀

I predict: Cursor gonna rip out their entire vector search implementation, replacing it w/ lexical search similar to Claude Code. Cursor Agents alrdy does this to an extent Which means turbopuffer loses a massive customer Another L for vector databases Jo Kristian Bergum

A key use case of fast database forking is supporting dev workflows for both humans and agents: "branch" a database to test a schema migration, and allow agents to create/destroy databases quickly during code generation. If you had a similar ability for instant copy-on-write

Timescale (now TigerData) We've already surpassed 500,000 events tracked in less than 24h since launch! We track every action in the game; every block placed, broken, mob killed, bed slept, etc. We use the data to power real-time player profiles and leaderboards. I'm sure the database guru Aaron Francis

Cloudflare chose TimescaleDB to power its Digital Experience Monitoring and Zero Trust Analytics products. cfl.re/4nCM3a8

AI is just search. Love this new post by jacky on why: - Semantic search fails where precision matters - Vector databases are doomed - Claude Code’s grep-powered search destroys Cursor’s vectors - Hybrid search (combining lexical, full-text, and semantic) is the

I'm excited to be sharing the MarketReader story and a bit of how we are able to generate real-time explanations for market movements with some help from our friends at Timescale (now TigerData) !