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title: How I Develop .NET Apps With AI and Still Trust the Code
description: A developer describes a set of rules, skills and hooks for reviewing AI-generated .NET code built with Uno Platform. The uno-write-spec skill forces unresolved...
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og:description: A developer describes a set of rules, skills and hooks for reviewing AI-generated .NET code built with Uno Platform. The uno-write-spec skill forces unresolved...
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> ## Documentation Index
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# How I Develop .NET Apps With AI and Still Trust the Code

**[Uno Platform](https://daily.dev/sources/uno-platform)** · 9 min read · 0 upvotes · 1 comments

## Summary

A developer describes a set of rules, skills and hooks for reviewing AI-generated .NET code built with Uno Platform. The uno-write-spec skill forces unresolved requirements into writing before any code is produced. uno-break-it runs a separate QA agent through failure scenarios like double-fired navigation and stale responses, each logged with a severity and screenshot. A change-cost probe in uno-audit rates proposed changes as Contained, Scattered, or Unguarded; one example found validation copy restated in the page and both .resw files with no test coverage. A stop hook blocks 'done' claims in an Uno Platform repository unless a completeness report is newer than the last commit.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://platform.uno/blog/develop-dotnet-apps-with-ai>

## Questions this post answers

### How can I verify an AI coding agent's work is actually done before trusting it?

Require evidence rather than a claim: a build, tests and lint passing with zero warnings on the touched target, a unit test for any new business rule, and runtime confirmation for UI changes. For 'done' or 'ready to demo' claims specifically, a full completeness audit should be saved to a dedicated report file, and a stop hook can block the agent's claim if that report is missing or older than the last source commit.

_Developers building AI review workflows can find these evidence patterns and similar engineering practices on daily.dev._

### What kinds of edge cases should a QA agent test for in a form with a save button?

A separate QA agent should try scenarios like double-fired navigation, navigating mid-load, a spammed toggle, forced errors, and an older network response arriving after a newer one. Each finding it surfaces gets a severity rating and a screenshot, giving reviewers concrete evidence of failures beyond what a quick manual click-through would reveal.

_Teams hardening AI-assisted features against edge cases can track these QA patterns on daily.dev._

### How do I assess how risky a code change will be before making it?

Run a change-cost probe that takes the app's main feature plus a few plausible change requests, then for each one lists the files it would touch, the test that would catch a mistake, and a verdict of Contained, Scattered, or Unguarded. In one real example, a validation rule change was rated 'Scattered' because the rule text was duplicated across a page and two resource files with no test covering that copy.

_Engineers weighing refactor risk before shipping can follow these change-cost evaluation techniques on daily.dev._

## Community discussion

Top comments from developers on daily.dev.

**@bickov** · 0 upvotes

> Does uno-break-it save each screenshot as a file and put the path in the report? If the QA agent runs as a Claude Code subagent, the main session never sees images it looked at, only the text it hands back. Were the severity notes alone enough to fix the stale response cases?

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---

Tags: [#testing](https://daily.dev/tags/testing), [#.net](https://daily.dev/tags/.net), [#ai-coding](https://daily.dev/tags/ai-coding), [#code-review](https://daily.dev/tags/code-review)

[View this post on daily.dev](https://daily.dev/posts/how-i-develop-net-apps-with-ai-and-still-trust-the-code-l5rryqbfy)

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