We transitioned from a Twitter search demo to building Perplexity by recognizing the potential for a more general solution that could index various databases.

Deep research is capable of handling complex queries that traditional search methods struggle with, such as finding specific markets based on multiple constraints.

We initially focused on large law firms, but learned that not all firms are ready to adopt new technology quickly, leading us to pivot towards smaller firms that found significant value in AI.

We focused on one approach rather than spreading our resources too thin, which is a key takeaway for startups.

We decided to focus solely on couples after realizing that our initial broad approach diluted the app's effectiveness.

We started doing user research in earnest, which opened our minds to the entire world of urban planning we now work in.

Initially, we faced challenges with our website as users preferred YouTube over our platform, leading us to pivot our strategy based on user feedback.

We prioritize tackling big problems in the industry, which leads to discovering larger opportunities, as we did when shifting focus from autonomous vehicles to AI's geopolitical implications.

Google's original search algorithm struggled to scale as the web grew, leading to a period where users received stale search results. This crisis prompted the development of MapReduce, a system for parallelizing web crawling and indexing.