How data teams are actually building the context layer
By Jakub Jurovych
•Updated on September 1, 2026
Deepnote research: our notes on building agents
Blog
Introducing Deepnote Agent Workspace
By Jakub Jurovych
•Updated on August 3, 2026
Latest releases
Ultimate guide to Pandas library in Python
Pandas is an open-source library for the Python programming language, designed to simplify data manipulation and analysis.
By Katerina Hynkova
•Updated on August 18, 2025
Deepnote acquires Hyperquery
Deepnote has signed a definitive agreement to acquire Hyperquery, a visionary startup in the data analytics space. We are unifying the data analytics market and integrating Hyperquery’s capabilities and customers into Deepnote, the leading AI-powered data notebook.
By Jakub Jurovych
•Updated on July 29, 2024
How we made data apps 40% faster
New and existing apps of our customers are now much faster. How did we achieve that?
By Patrik Gallik
•Updated on April 24, 2024
How to effectively prompt Deepnote AI
Deepnote AI is a powerful tool, assisting you with your data projects through your prompts in natural language. But how do you effectively structure your prompts in order to get the most out of Deepnote AI and fully utilize its deep contextual awareness?
By Ondřej Romancov
•Updated on March 26, 2024
Deepnote AI: So, what’s the impact? (Part 1)
In Part 1 of our series focusing on the real impact of generative AI in Deepnote, we delve into the creation of AI code completion, our approaches to measuring success, and some of the lessons we've learned along the way.
By Gabor Szalai
•Updated on December 11, 2023
DLT & Deepnote in women's wellness and violence trends: A Visual Analysis
Hiba Jamal from dlthub combines dlt and Deepnote to explore trends in women's wellness and violence, where dlt formatted her deeply nested datasets into my desired destination with minimal supervision and Deepnote acted as an interactive dashboarding tool.
By Megan Lieu
•Updated on November 14, 2023