# Building ambitious software — Jonathan Kelley, Dioxus Labs & Cognition

Source: [AI Engineer](https://www.youtube.com/watch?v=H7vFrcNWXzs)  
Feed7 permalink: https://feed7.dev/p/building-ambitious-software-jonathan-kelley-dioxus-labs-cognition-05p0hll  
Published: 2026-09-11T20:00:06.000Z  
Trust: Source Linked (source_linked)

## Why Included

Dioxus found that generating more Rust was easy but merging it was not. Agents paid off on bounded research and maintenance work when architecture, real-device tests, and line-by-line review stayed human-owned.

## Source Summary

After generating **tens of thousands of lines of Rust**, the Dioxus team found that very little met its merge bar. A Kotlin and Swift plugin implementation arrived quickly, but the team spent **two to three weeks** building test cases and validating it on real devices.

## Practical Implication

Use agents where patience and broad technical recall matter: documentation research, debugging specifications, release checklists, backports, and documentation consistency. Keep architecture explicit, communicate intent precisely, and review shipped code line by line.

## Agent-Ready Context

After generating **tens of thousands of lines of Rust**, the Dioxus team found that very little met its merge bar. A Kotlin and Swift plugin implementation arrived quickly, but the team spent **two to three weeks** building test cases and validating it on real devices.

Use agents where patience and broad technical recall matter: documentation research, debugging specifications, release checklists, backports, and documentation consistency. Keep architecture explicit, communicate intent precisely, and review shipped code line by line.

Test generation remains a weak point: agents can cover an API while missing the behavior that matters. The experience is from one foundational open-source project, so its workflow may not transfer directly, but its core constraint is clear: **code is cheap; quality is not**.

## Connected Context

Feed7 judgment across 757 accumulated Signals:

This supplies project-level evidence that generation throughput does not remove the engineering bottleneck; it moves effort into architecture, behavioral tests, device validation, and meticulous review. It reinforces bounded, verification-heavy agent workflows while sharpening a specific weakness: API-shaped generated tests may miss product behavior. The result also conflicts with proposals to replace line-level review wholesale, at least for foundational code under a strict merge bar.

- [ExecCritic: Learn to Test, Test to Improve for Coding Agents](https://feed7.dev/p/2609-09133v1-0zfcxb4) — ExecCritic provides a concrete control for the reported test weakness: qualify and freeze tests separately because weak generated tests can actively reduce repair success.
- [How to Kill the Code Review — Ankit Jain, Aviator](https://feed7.dev/p/how-to-kill-the-code-review-ankit-jain-aviator-0rku6kj) — Both move attention toward verification evidence, but they differ on review: Kelley retains line-by-line inspection, whereas Jain proposes reducing reliance on diff review as volume grows.
- [How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma](https://feed7.dev/p/how-to-get-your-org-to-adopt-coding-agents-without-shipping-garbage-eyal-04y3rj2) — The costly validation experience reinforces Figma’s claim that cautious maintainers reveal missing safeguards and that adoption depends on reviewable plans, tests, and changes.
- [Loop Engineering from First Principles — Kyle Mistele, HumanLayer](https://feed7.dev/p/loop-engineering-from-first-principles-kyle-mistele-humanlayer-1nuq7gf) — The low merge yield from large generated output supports incremental, reviewable agent loops over unbounded production, especially when validation is the scarce resource.

## Context Map

- Layer: agent
- Domains: coding
- Topics: coding-agents, harness-engineering, agent-reliability

## Uncertainty

- Test generation remains a weak point: agents can cover an API while missing the behavior that matters. The experience is from one foundational open-source project, so its workflow may not transfer directly, but its core constraint is clear: **code is cheap; quality is not**.

## Agent Instruction

Use this item as source-backed context. Do not invent claims beyond the linked source. If this item conflicts with another source, call out the conflict.