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title: 'Building ambitious software — Jonathan Kelley, Dioxus Labs & Cognition'
description: >-
  The Dioxus team got excited, maxed out their coding agent subscriptions, and
  turned out tens of thousands of lines of Rust covering features they had
  wanted for years. Almost none of it cleared the bar for merging. Those lines
  sat in draft, and Jonathan Kelley says they are sitting there still. He calls
  the failure mode becoming a slop cannon. Kelley founded Dioxus Labs five years
  ago, spending his last undergraduate summer on a cross platform Rust app
  framework instead of taking an internship, and the project now carries roughly
  37,000 GitHub stars and an estimated 200 million cumulative end users across
  apps from voting software to collision avoidance for satellites. Getting there
  meant building almost everything from scratch, including a rendering engine
  with a browser grade CSS engine lifted out of Firefox, and a hot reload engine
  that patches running native code in place in about 100 milliseconds. The
  interesting turn is what changed when the agents got good at Rust. Kelley's
  team spent five years trying to file down Rust's learning curve, and now
  treats that curve as a feature, because the agents absorb the borrow checker
  and the edge cases on the developer's behalf. He is specific about where this
  pays and where it does not. Deeply integrated Kotlin and Swift build plugins
  went from years of hand written work to weeks. Release checklists, backports,
  and documentation accuracy became tractable for a team of three. Tests did
  not, because agents write tests for any API but rarely the right ones, though
  they excel at fuzzing harnesses. His verdict: code is cheap now, quality is
  not, and architecture is where the time goes. Speaker info: -
  https://www.linkedin.com/in/jonathan-r-kelley - https://jonathan-kelley.com -
  https://github.com/dioxuslabs/dioxus Timestamps: 0:00 - Five years ago, a
  first commit 2:49 - Where the project stands now 4:35 - Blitz and Subsecond
  6:15 - The moment agents got good at Rust 7:07 - Why a hard language became an
  advantage 10:32 - Agents as patient specialists 13:04 - The mundane work worth
  automating 15:37 - Where tests fall short, where fuzzing wins 16:28 -
  Architecture is still an art 17:19 - Reading code over writing code --- Watch
  along with the corrected transcript, summary, timestamps and resources on this
  talk's official AIE page:
  https://ai.engineer/talks/H7vFrcNWXzs-youtube-3f75483912b55b5ce56b Join our
  upcoming AI Engineer conferences (see https://ai.engineer landing page): -
  AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and
  engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference
  returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS
  2026 in Sydney ---
canonical: 'https://liquidgold.cc/watch/H7vFrcNWXzs'
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parent: 'https://liquidgold.cc/channel/aidotengineer.md'
channel: aidotengineer
updated: '2026-10-24T03:47:35.737Z'
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# Building ambitious software — Jonathan Kelley, Dioxus Labs & Cognition

The Dioxus team got excited, maxed out their coding agent subscriptions, and turned out tens of thousands of lines of Rust covering features they had wanted for years. Almost none of it cleared the bar for merging. Those lines sat in draft, and Jonathan Kelley says they are sitting there still. He calls the failure mode becoming a slop cannon. Kelley founded Dioxus Labs five years ago, spending his last undergraduate summer on a cross platform Rust app framework instead of taking an internship, and the project now carries roughly 37,000 GitHub stars and an estimated 200 million cumulative end users across apps from voting software to collision avoidance for satellites. Getting there meant building almost everything from scratch, including a rendering engine with a browser grade CSS engine lifted out of Firefox, and a hot reload engine that patches running native code in place in about 100 milliseconds. The interesting turn is what changed when the agents got good at Rust. Kelley's team spent five years trying to file down Rust's learning curve, and now treats that curve as a feature, because the agents absorb the borrow checker and the edge cases on the developer's behalf. He is specific about where this pays and where it does not. Deeply integrated Kotlin and Swift build plugins went from years of hand written work to weeks. Release checklists, backports, and documentation accuracy became tractable for a team of three. Tests did not, because agents write tests for any API but rarely the right ones, though they excel at fuzzing harnesses. His verdict: code is cheap now, quality is not, and architecture is where the time goes. Speaker info: - https://www.linkedin.com/in/jonathan-r-kelley - https://jonathan-kelley.com - https://github.com/dioxuslabs/dioxus Timestamps: 0:00 - Five years ago, a first commit 2:49 - Where the project stands now 4:35 - Blitz and Subsecond 6:15 - The moment agents got good at Rust 7:07 - Why a hard language became an advantage 10:32 - Agents as patient specialists 13:04 - The mundane work worth automating 15:37 - Where tests fall short, where fuzzing wins 16:28 - Architecture is still an art 17:19 - Reading code over writing code --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/H7vFrcNWXzs-youtube-3f75483912b55b5ce56b Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---

Canonical: https://liquidgold.cc/watch/H7vFrcNWXzs · Channel: [AI Engineer](https://liquidgold.cc/channel/aidotengineer.md)

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