3 things to learn from Cursor's popularity
Cursor's been blowing up on socials the last few weeks, in no small part thanks to this video from Fay Robinett which has been viewed 2.5m times:
What can an 8-year-old build in 45 minutes with the assistance of AI?
— Ricky (@rickyrobinett) August 19, 2024
My daughter has been learning to code with @cursor_ai and it's mind-blowing🤯
Here are highlights from her second coding session. In 45 minutes she built a chatbot powered by @CloudflareDev Workers AI 👀 pic.twitter.com/MJ6vAlmvnj
In a time when so many AI features/apps are falling short of the hype, what can you learn from Cursor to figure out which AI apps will win?
Three patterns:
1. They brought the LLM closer to where the user already works and closer to their data (the codebase, which is used as context).
2. There's a validity-check: does your code run (or tests pass)? If not add the stack trace back into the chat, and the LLM fixes it. This combats hallucinations.
3. There's a human in the loop. Automation usecases are underpeforming. Augmentation use cases are going great.
Full video:
And in tweet form:
Three patterns to learn from Cursor's popularity to help you think about which AI apps will win.
— Greg Baugues (@greggyb) September 6, 2024
1. They brought the LLM closer to where the user already works and closer to their data (the codebase, which is used as context).
2. There's a validity-check: does your code run… pic.twitter.com/tAt9vQe7GP