# How to be AI-fancy

DevFeed: [How to be AI-fancy](<https://devfeed.tech/articles/how-to-be-ai-fancy-5370.md>)

Original publisher: [Read original article](<https://neon.com/blog/how-to-be-ai-fancy>)

Author: Eduard Dyckman

Published: 2024-11-04T16:48:02Z

Content type: article

Language: en

Sources: [Blog -- Neon Docs](<https://devfeed.tech/sources/blog-neon-docs.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [SQL](<https://devfeed.tech/topics/sql.md>), [Databases](<https://devfeed.tech/topics/databases.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [errors](<https://devfeed.tech/tags/errors.md>), [experimental](<https://devfeed.tech/tags/experimental.md>), [generation](<https://devfeed.tech/tags/generation.md>), [llm](<https://devfeed.tech/tags/llm.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [product](<https://devfeed.tech/tags/product.md>), [sql](<https://devfeed.tech/tags/sql.md>)

## AI overview

Neon describes AI-driven features for its SQL playground. Users can generate SQL from natural-language prompts, assign meaningful names to query history entries, and request fixes for failed queries using PostgreSQL errors and database schema as context. Generated queries are left for users to review and execute, and can be tested in a database branch.

## Source excerpt

Despite the fact that Postgres has been around for almost 30 years, Neon has always been an innovative company supporting experimental ideas. So, obviously, we couldn't miss the AI fever. 🙂 We started our first experiments with AI a little more than a year ago, but only recently...