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Frame from Cursor Team: Future of Programming with AI | Lex Fridman Podcast #447 Plays via YouTube's privacy-enhanced embed

Cursor Team: Future of Programming with AI | Lex Fridman Podcast #447

48 videos recommended on HN
YouTube
2 HN users recommended this podcast episode2 months2024–2025 score 2
Years with an HN recommendation, 2007–2026

HN commenters point to it as the best first-hand account of Cursor's technical internals, straight from its founders.

A Lex Fridman podcast conversation with the four creators of Cursor, the AI-assisted code editor. They discuss how the editor integrates models into programming workflows, including custom completion models and techniques like speculative decoding to speed up applying edits.

“The founders did an episode on Lex Fridman's podcast that covers the technical sides of Cursor far better than I ever could” (HN, 2024)

2 recommendations · 3 citations · Podcasts · intermediate · partly dated

5 Hacker News comments

From the HN archive; up to 20 kept per video, favoring different commenters. Recommendations first.

@rco8786 Oct 2024 Recommends
on HN thread How I write code using Cursor
The founders did an episode on Lex Fridman's podcast that covers the technical sides of Cursor far better than I ever could: [this video] But to summarize, Copilot is an okay ChatGPT wrapper for single line code completion. Cursor is a full IDE with AI baked in natively, with use-case specific models for different tasks, intelligent look-ahead, multi-line completion, etc. If Copilot is a horse, Cursor is a Model T.
Cursor founders explain the technical side of the editor
@light_triad Feb 2025 Recommends
on HN thread You can’t build a moat with AI (redux)
Read more
AI enables new tools & features but in itself is not a product. There's a good essay from Andrew Chen on this topic: Revenge of the GPT Wrappers: Defensibility in a world of commoditized AI models "Network effects are what defended consumer products, in particular, but we will also see moats develop from the same places they came from the past decades: B2B-specific moats (workflow, compliance, security, etc), brand/UX, growth/distribution advantages, proprietary data, etc etc." [1] Also check out the podcast with the team at Cursor/Anysphere for details into how they integrate models into workflows [2] [1] [link] [2] [this video]
Details on how Cursor integrates models into workflows

Citations, criticism and jokes

@viraptor Oct 2024 Cites it
on HN thread How I write code using Cursor
That's the basic part. Cursor people talked about effectively streaming in and other ideas. See [this video]
Cursor team discuss streaming and related ideas
@cbhl Nov 2024 Cites it
on HN thread New OpenAI Feature: Predicted Outputs
If you use the Cursor IDE: the folks that wrote it talked about their use of speculative decoding to make "Apply" faster on the Lex Friedman podcast last month. Here it is on YouTube, although you can also find it on Spotify and other podcast platforms: [this video]
Cursor team discuss speculative decoding for faster Apply

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