The balance between speed and quality in search results is crucial; users are willing to wait longer for more complex queries but expect quick responses for simpler ones.

The relationship between search and users is dynamic; understanding how long users are willing to wait for information helps tailor the search experience to their needs.

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

Customization of large language models is crucial for differentiation, as everyone has access to the same base models, but tailoring them to specific contexts enhances user experience.

We have to help users find the exact part of Intercom that meets their needs, which requires a tailored experience for each user.

Custom-designed software tailored for individual users may emerge, but there are challenges in achieving this level of personalization effectively.

Personas are a valuable tool for understanding specific user needs and tailoring the product accordingly.

The model is effective at following complex instructions, allowing users to request multiple types of information in one query, such as product details, comparisons, and reviews from various sources.

Deep research is designed to be the most comprehensive tool for search queries, while the 03 model is better suited for medium-level searches.