Coding in collaboration with AI can reduce human toil in the software development process and lead to more accurate and less tedious work for coding teams. This week on No Priors, Sarah talked with Beyang Liu, the cofounder and CTO of Sourcegraph, which builds tools that help developers innovate faster. Their most recent launch was an AI coding assistant called Cody. Beyang has spent his entire career thinking about how humans can work in conjunction with AI to write better code.

Sarah and Beyang talk about how Sourcegraph is thinking about augmenting the coding process in a way that ensures accuracy and efficiency starting with robust and high-quality context. They also think about what the future of software development could look like in a world where AI can generate high-quality code on its own and where that leaves humans in the coding process.

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Show Notes:

(0:00) Beyang Liu’s experience

(0:52) Sourcegraph premise

(2:20) AI and finding flow

(4:18) Developing LLMs in code

(6:46) Cody explanation

(7:56) Unlocking AI code generation

(11:00) search architecture in LLMs

(16:02) Quality-assurance in data set

(18:03) Future of Cody

(22:48) Constraints in AI code generation

(30:28) Lessons from Beyang’s research days

(33:17) Benefits of small models

(35:49) Future of software development

(42:14) What skills will be valued down the line