Sign up to save your podcasts
Or
Share Ep 33: CTO and Co-Founder of Sourcegraph on Current Landscape and Future of Software Development, How to Make RAG Better, and Building Towards the Agentic Future
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
Ep 33: CTO and Co-Founder of Sourcegraph on Current Landscape and Future of Software Development, How to Make RAG Better, and Building Towards the Agentic Future
On this week’s Unsupervised Learning, Pat and I sat down with CTO and Co-Founder of Sourcegraph, Beyang Liu. Sourcegraph is a leader in the AI coding space, and recently launched AI coding assistant, Cody. Beyang shared with us his view on the current landscape of AI coding and the future of coding and software development. He also shared how Sourcegraph has tried to make RAG better, and their model eval approaches.
(0:00) intro
(0:47) advice for young coders
(3:34) AI products at Sourcegraph
(6:17) the current state of AI coding
(12:33) what happens when a new GPT model comes out?
(20:16) what types of developers benefit from these AI tools?
(30:45) how important is inference cost?
(35:31) how does Sourcegraph structure AI teams?
(41:27) what metrics does Sourcegraph use to evaluate their products?
(50:02) customizing RAG
(56:55) getting ahead of the agentic future
(1:05:05) will there be more or less engineers in the future?
(1:13:50) over-hyped/under-hyped
(1:16:56) surprises during the Sourcegraph journey
(1:18:26) cognition buzz and Devin
(1:26:48) Jacob and Pat debrief
With your co-hosts:
@jacobeffron
- Partner at Redpoint, Former PM Flatiron Health
@patrickachase
- Partner at Redpoint, Former ML Engineer LinkedIn
@ericabrescia
- Former COO Github, Founder Bitnami (acq’d by VMWare)
@jordan_segall
- Partner at Redpoint
View all episodes
By by Redpoint Ventures
4.9
3838 ratings
On this week’s Unsupervised Learning, Pat and I sat down with CTO and Co-Founder of Sourcegraph, Beyang Liu. Sourcegraph is a leader in the AI coding space, and recently launched AI coding assistant, Cody. Beyang shared with us his view on the current landscape of AI coding and the future of coding and software development. He also shared how Sourcegraph has tried to make RAG better, and their model eval approaches.
(0:00) intro
(0:47) advice for young coders
(3:34) AI products at Sourcegraph
(6:17) the current state of AI coding
(12:33) what happens when a new GPT model comes out?
(20:16) what types of developers benefit from these AI tools?
(30:45) how important is inference cost?
(35:31) how does Sourcegraph structure AI teams?
(41:27) what metrics does Sourcegraph use to evaluate their products?
(50:02) customizing RAG
(56:55) getting ahead of the agentic future
(1:05:05) will there be more or less engineers in the future?
(1:13:50) over-hyped/under-hyped
(1:16:56) surprises during the Sourcegraph journey
(1:18:26) cognition buzz and Devin
(1:26:48) Jacob and Pat debrief
With your co-hosts:
@jacobeffron
- Partner at Redpoint, Former PM Flatiron Health
@patrickachase
- Partner at Redpoint, Former ML Engineer LinkedIn
@ericabrescia
- Former COO Github, Founder Bitnami (acq’d by VMWare)
@jordan_segall
- Partner at Redpoint
More shows like Unsupervised Learning
View all
a16z Podcast
1,005 Listeners
The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
507 Listeners
Y Combinator Startup Podcast
207 Listeners
Practical AI
187 Listeners
Machine Learning Street Talk (MLST)
90 Listeners
Dwarkesh Podcast
352 Listeners
Big Technology Podcast
395 Listeners
The Logan Bartlett Show
191 Listeners
No Priors: Artificial Intelligence | Technology | Startups
129 Listeners
This Day in AI Podcast
196 Listeners
Latent Space: The AI Engineer Podcast
72 Listeners
BG2Pod with Brad Gerstner and Bill Gurley
433 Listeners
AI + a16z
33 Listeners
Lightcone Podcast
21 Listeners
Training Data
37 Listeners