John P @sql_johnpruitt
Joined October 2021-
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It's Mat (@cevianNY) from @TigerDatabase again. This week I am announcing a new open-source tool for evaluating and improving LLM-based text-to-SQL systems for PostgreSQL. We built this because in developing the semantic catalog text-to-SQL tool I discussed last week, we thought…
LLMs are becoming new users of the database. But unlike human users, it’s not enough to ask “did the query run?” We need ways to evaluate how well they interact with our data. Over the past few months, our team built an internal library to better understand text-to-SQL…
Stop paying the OpenAI tax. The best AI devtools are actually open-source, free to use, and give you full control over your data and privacy. While proprietary AI dominated early headlines, the true revolution is happening in open source - where a flourishing ecosystem of…
Engineer: "Should we upgrade to the latest OpenAI model? It's cheaper and performs better on benchmarks." Tech lead: "We should explore it, but re-embedding all our data is too much work right now. Let's revisit next month." Engineer: "Hold my beer..." With pgai Vectorizer,…
One of the major challenges with building AI chat apps and agents powered by RAG is the complexity of creating, storing, and syncing embeddings with real-time source data. If this isn't managed effectively, your AI app will likely generate outdated, inaccurate information…
𝗧𝗵𝗲 𝗵𝗮𝗿𝗱 𝗽𝗮𝗿𝘁 𝗼𝗳 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗵𝗮𝗻𝗱𝗹𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝗮𝗶𝗹𝘂𝗿𝗲 𝗰𝗮𝘀𝗲𝘀. Yesterday, we launched pgai Vectorizer, a tool that automates embedding generation directly from data stored in the database and keeps it synced as the…
Vector Databases should actually be Vector Indexes Imagine if every time you inserted or updated a row, you had to reach out to an external system to update the associated B-trees. Each call risks failure, rate-limits, and throws in queuing, tracking, staleness handling, and…
🛑 Vector Databases Are the Wrong Abstraction. Here’s Why. They treat embeddings as standalone data, disconnected from their source, leading to outdated embeddings, constant sync issues, and endless maintenance. That’s why we built pgai Vectorizer for Postgres—so every engineer…
The original SQL paper (1974) really stands the test of time CPUs were 20,000,000,000x more expensive per flop in 1974! SQL is 50 years old: older than the Internet, hard disks, Linux, x86, and CMOS RAM; yet SQL remains in service to people today, for the exact same use cases
After my team built this we only had one question: why doesn’t everyone do embedding this way?
🔥 𝗘𝘃𝗲𝗿𝘆 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗶𝘀 𝗻𝗼𝘄 𝗮𝗻 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿: 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗽𝗴𝗮𝗶 𝗩𝗲𝗰𝘁𝗼𝗿𝗶𝘇𝗲𝗿 🔥 𝗽𝗴𝗮𝗶 𝗩𝗲𝗰𝘁𝗼𝗿𝗶𝘇𝗲𝗿 is a developer tool that automatically creates and syncs embeddings right in your PostgreSQL database. In other…
VECTOR DATABASES ARE THE WRONG ABSTRACTION. Here’s a better way: introducing pgai Vectorizer, a new open-source PostgreSQL tool that automatically creates and syncs embeddings with source data, just like a database index. ❌ Why vector databases fail Vector databases treat…
Timescale expands open source vector database capabilities for PostgreSQL venturebeat.com/data-infrastru…
🚀 Every Developer is Now an AI Developer - Introducing pgai Vectorizer No need for specialized tools or vector databases—pgai Vectorizer lets you create, sync, and manage embeddings with just one SQL command. 🔹 Embeddings in Postgres: Build, store, and sync embeddings…
Here's how @techscienceandy built a content recommendation system using just PostgreSQL "This was the major eureka moment for our company: having modern LLMs available right from our database. No dependency management, no infrastructure, no additional costs. We do not require…

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