Before Perplexity, Aravind Srinivas built a Twitter search tool that changed his startup’s direction

Before Perplexity became an AI-powered search product, Aravind Srinivas and his co-founders built a tool that let users ask natural language questions about Twitter data. The system translated those questions into SQL queries to retrieve information of mutual followers and tweets liked by multiple users. The idea was to make information buried in the platform’s data easier to find without requiring users to write complicated database queries.

The project was an early experiment in using large language models to improve search. But collecting enough Twitter data was difficult, and the approach was not scalable. An unexpected response to a feature in Perplexity’s first release eventually gave the founders confidence to focus on regular web search instead.

In his conversation with Lex Fridman in his podcast, Srinivas explained how the team moved from experimenting with Twitter’s social graph to developing a broader vision centred on knowledge and curiosity.

Aravind Srinivas Wanted to Build an AI-First Product

Srinivas said he brought together his co-founders, Dennis and Johnny, to build products using large language models. At the time, it was unclear where AI companies would create the most value, but he saw an opportunity in products that could put generative AI directly in users’ hands.

GitHub Copilot was an important inspiration. Srinivas wanted to build a company whose product would improve as AI advanced, attracting more users and generating more data that could help…