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    <title>DEV Community: David Hillier</title>
    <description>The latest articles on DEV Community by David Hillier (@davidhillier_final01).</description>
    <link>https://dev.to/davidhillier_final01</link>
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      <title>DEV Community: David Hillier</title>
      <link>https://dev.to/davidhillier_final01</link>
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      <title>Everyone Is Teaching AI To Create Images. I Wanted To See If It Could Judge Them.</title>
      <dc:creator>David Hillier</dc:creator>
      <pubDate>Sat, 13 Jun 2026 07:30:21 +0000</pubDate>
      <link>https://dev.to/davidhillier_final01/everyone-is-teaching-ai-to-create-images-i-wanted-to-see-if-it-could-judge-them-3pah</link>
      <guid>https://dev.to/davidhillier_final01/everyone-is-teaching-ai-to-create-images-i-wanted-to-see-if-it-could-judge-them-3pah</guid>
      <description>&lt;p&gt;I've spent more than 20 years in architectural visualisation, reviewing thousands of renders for architects, developers and design teams.&lt;br&gt;
Like most people, I was fascinated when AI started generating images.&lt;br&gt;
But after playing with the latest models, I found myself asking a different question:&lt;/p&gt;

&lt;p&gt;Could AI evaluate images instead of creating them?&lt;/p&gt;

&lt;p&gt;Creating and judging are very different skills.&lt;/p&gt;

&lt;p&gt;Most 3D artists know when an image feels "off", but identifying exactly why it feels off is much harder. Professional art direction is largely about visual judgement — understanding which few changes will have the biggest impact on an image.&lt;/p&gt;

&lt;p&gt;As a non-developer who has spent the last year teaching myself software development with AI-assisted tools, I decided to run an experiment: Could professional art direction be delivered autonomously if the AI was supported by the right knowledge system?&lt;/p&gt;

&lt;p&gt;What surprised me was that the AI wasn't the hard part. Modern vision models are incredibly capable. The hard part was calibration.&lt;br&gt;
Without guidance, the model was:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;too generous&lt;/li&gt;
&lt;li&gt;inconsistent&lt;/li&gt;
&lt;li&gt;overly focused on surface-level observations&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;The breakthrough came when I stopped focusing on prompts and started focusing on standards. Instead of asking "What do you think of this image?", I built a structured framework around how professional architectural renders are actually reviewed:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;Composition &amp;amp; Camera&lt;/li&gt;
&lt;li&gt;Lighting &amp;amp; Grading&lt;/li&gt;
&lt;li&gt;Materials &amp;amp; Geometry&lt;/li&gt;
&lt;li&gt;Landscaping &amp;amp; Context&lt;/li&gt;
&lt;li&gt;Realism &amp;amp; CG Artefacts&lt;/li&gt;
&lt;li&gt;Narrative &amp;amp; Mood&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;I also introduced visual reference imagery, because I realised something important: People don't just need feedback. They need to see what good looks like.&lt;/p&gt;

&lt;p&gt;The biggest lesson from the project was that AI doesn't magically create expertise but it can amplify it. A weak framework produces weak results.&lt;br&gt;
A strong framework produces surprisingly useful ones.&lt;/p&gt;

&lt;p&gt;As AI continues to improve, I think we'll see more focus on evaluation rather than generation. Once everyone can create images, code and content, the scarce resource becomes judgement.&lt;/p&gt;

&lt;p&gt;I'd be interested to hear whether others have found the same thing when building AI products. Has the challenge been the model itself, or the knowledge system behind it?&lt;/p&gt;

&lt;p&gt;If you want to check out the site and try it out, it's &lt;a href="https://www.final01.app" rel="noopener noreferrer"&gt;Final01&lt;/a&gt;&lt;/p&gt;

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      <category>ai</category>
      <category>design</category>
      <category>machinelearning</category>
      <category>softwaredevelopment</category>
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