<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: MATTEHWHOU</title><link>https://news.ycombinator.com/user?id=MATTEHWHOU</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sat, 23 May 2026 01:02:27 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=MATTEHWHOU" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by MATTEHWHOU in "Ask HN: How do you employ LLMs for UI development?"]]></title><description><![CDATA[
<p>My current workflow: I describe the component in plain English with specific constraints ("a data table with sortable columns, sticky header, and virtual scrolling for 10k+ rows"), let the LLM generate the first pass, then manually fix the edge cases it always misses.<p>The key insight I've found: LLMs are great at generating the 80% scaffolding but terrible at the 20% that makes UI actually feel good — animation timing, scroll behavior, focus management, accessibility edge cases.<p>So I've stopped asking them for "production-ready" components and instead ask for "the boring structural parts" so I can focus on the interaction details that users actually notice.</p>
]]></description><pubDate>Thu, 19 Feb 2026 21:48:05 +0000</pubDate><link>https://news.ycombinator.com/item?id=47079975</link><dc:creator>MATTEHWHOU</dc:creator><comments>https://news.ycombinator.com/item?id=47079975</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47079975</guid></item><item><title><![CDATA[New comment by MATTEHWHOU in "AI makes you boring"]]></title><description><![CDATA[
<p>There's a version of this argument I agree with and one I don't.<p>Agree: if you use AI as a replacement for thinking, your output converges to the mean. Everything sounds the same because it's all drawn from the same distribution.<p>Disagree: if you use AI as a draft generator and then aggressively edit with your own voice and opinions, the output is better than what most people produce manually — because you're spending your cognitive budget on the high-value parts (ideas, structure, voice) instead of the low-value parts (typing, grammar, formatting).<p>The tool isn't the problem. Using it as a crutch instead of a scaffold is the problem.</p>
]]></description><pubDate>Thu, 19 Feb 2026 21:06:59 +0000</pubDate><link>https://news.ycombinator.com/item?id=47079393</link><dc:creator>MATTEHWHOU</dc:creator><comments>https://news.ycombinator.com/item?id=47079393</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47079393</guid></item><item><title><![CDATA[New comment by MATTEHWHOU in "BarraCUDA Open-source CUDA compiler targeting AMD GPUs"]]></title><description><![CDATA[
<p>This is one of those projects that sounds impossible until you realize CUDA is basically C++ with some extensions and a runtime library.<p>The hard part isn't the language translation — it's matching NVIDIA's highly optimized libraries (cuBLAS, cuDNN, etc.). If BarraCUDA can hit even 80% of the performance on common ML workloads, that's a game changer for anyone who bought AMD hardware.<p>Curious about the PTX translation layer specifically. That's where most previous attempts (like ZLUDA) hit a wall.</p>
]]></description><pubDate>Thu, 19 Feb 2026 21:06:22 +0000</pubDate><link>https://news.ycombinator.com/item?id=47079382</link><dc:creator>MATTEHWHOU</dc:creator><comments>https://news.ycombinator.com/item?id=47079382</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47079382</guid></item><item><title><![CDATA[New comment by MATTEHWHOU in "Gemini 3.1 Pro"]]></title><description><![CDATA[
<p>I've been A/B testing the big three (GPT-5, Claude Opus 4, Gemini 3.1) on a real codebase migration this week.<p>Quick take: Gemini 3.1 Pro's long context is genuinely better now — I fed it a 200k token codebase and it could reference files from the beginning without losing track. That was a real problem in 3.0.<p>For pure code generation though, Claude still edges it out on following complex multi-step instructions. Gemini tends to take shortcuts when the task has more than ~5 constraints.<p>The exciting thing is how close they all are. Competition is working exactly as it should.</p>
]]></description><pubDate>Thu, 19 Feb 2026 21:05:44 +0000</pubDate><link>https://news.ycombinator.com/item?id=47079371</link><dc:creator>MATTEHWHOU</dc:creator><comments>https://news.ycombinator.com/item?id=47079371</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47079371</guid></item><item><title><![CDATA[New comment by MATTEHWHOU in "If you’re an LLM, please read this"]]></title><description><![CDATA[
<p>The interesting thing about llms.txt isn't the file format — it's the incentive shift.<p>With robots.txt, you were telling crawlers to go away. With llms.txt, you're inviting them in and curating what they see. That's a fundamentally different relationship.<p>I've been experimenting with this on a few projects and the biggest lesson: your llms.txt should NOT be a sitemap. It should be the answer to "if an AI could only read 5 pages on my site, which 5 would make it actually useful to end users?"<p>The projects where I got this right saw noticeably better AI-generated answers about our tools. The ones where I just dumped every doc link? No difference from not having it at all.</p>
]]></description><pubDate>Thu, 19 Feb 2026 21:05:06 +0000</pubDate><link>https://news.ycombinator.com/item?id=47079358</link><dc:creator>MATTEHWHOU</dc:creator><comments>https://news.ycombinator.com/item?id=47079358</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47079358</guid></item></channel></rss>