Nextdoor engineers build faster with Codex

Nextdoor engineers are using OpenAI's Codex to accelerate development, enabling end-to-end feature building and faster debugging.

Nextdoor logo with OpenAI Codex branding elements.
Nextdoor utilizes OpenAI's Codex for enhanced engineering.· OpenAI News
Visual TL;DR
Nextdoor EngineeringDriver
social networking platform serving over 110 million users globally
From the article 7 mentionsCory Dolphin, Head of Engineering at Nextdoor, describes Codex as an essential tool that empowers individual engineers to own product experiences end-to-end.
OpenAI's CodexCore
AI system that translates natural language into code
From the article 7 mentionsNextdoor is leveraging OpenAI's Codex to fundamentally alter its software development lifecycle.
Accelerated DevelopmentEffect
engineers move beyond specialized roles to embrace outcome engineering
From the article 2 mentionsThis increased autonomy and efficiency have accelerated productivity to a point where the bottleneck is no longer engineering execution, but rather strategic decision-making.
End-to-end Feature BuildingEffect
empowers individual engineers to own product experiences end-to-end
From the articleEngineers now spend less time on the "how" of building and more on the "what." This could involve translating product mockups or videos into functional features, achieving specific performance benchmarks, or rapidly iterating on new ideas.
Faster DebuggingEffect
streamlining the process of identifying and fixing complex system issues
From the articleThe platform team also relies on Codex for tackling challenging debugging scenarios, particularly within embedded Rust databases and systems prone to race conditions.
Outcome EngineeringContext
From the article 5 mentionsThe social networking platform, serving over 110 million users globally, is seeing engineers move beyond specialized roles to embrace "outcome engineering," where the focus shifts to defining the desired result rather than the intricate steps to achieve it.
Reduced BottlenecksOutcome
From the articleThis increased autonomy and efficiency have accelerated productivity to a point where the bottleneck is no longer engineering execution, but rather strategic decision-making.
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Nextdoor is leveraging OpenAI's Codex to fundamentally alter its software development lifecycle. The social networking platform, serving over 110 million users globally, is seeing engineers move beyond specialized roles to embrace "outcome engineering," where the focus shifts to defining the desired result rather than the intricate steps to achieve it.

Engineering without limits

Cory Dolphin, Head of Engineering at Nextdoor, describes Codex as an essential tool that empowers individual engineers to own product experiences end-to-end. This increased autonomy and efficiency have accelerated productivity to a point where the bottleneck is no longer engineering execution, but rather strategic decision-making.

"Codex has fundamentally changed how we think about engineering, to the point that we can’t even imagine engineering without it," Dolphin stated.

Engineers now spend less time on the "how" of building and more on the "what." This could involve translating product mockups or videos into functional features, achieving specific performance benchmarks, or rapidly iterating on new ideas.

Accelerated feature development

A prime example is Nextdoor's Opportunity Alerts feature. Previously, adding a map view for service providers would have necessitated collaboration across mobile, frontend, and backend teams, potentially stalling progress. With Codex, one engineer was able to develop the feature autonomously, driving both speed and a deeper understanding of the user experience.

"As engineers start to shift up the stack, they get to be more responsible for the product that they’re building. You really see individual engineers start to drive products," Dolphin explained.

Debugging complex systems

The platform team also relies on Codex for tackling challenging debugging scenarios, particularly within embedded Rust databases and systems prone to race conditions. By providing Codex with a controlled environment, engineers use it to diagnose issues ranging from Kubernetes pod startup failures to intricate data analysis trends.

Dolphin highlighted the recent advancements in Codex, noting its persistence and ability to delve into esoteric technical details to pinpoint root causes. He also commented on the speed, stating, "A lot of the team are addicted to it. When you have a quick feedback loop with the problem that you’re working on, the feeling is exhilarating as an engineer."

This speed has shifted organizational pressures, with engineering no longer the primary constraint.

The focus has moved to identifying the right product strategies and features to pursue.

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Daniel Singer

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.

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