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		<title>Sharpening on AIBussin — AI applications, systems and books</title>
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				<title>Self-Improving Agents: Applying the Sharpening Framework to Local LLMs</title>
				<link>https://aibussin.com/post/sharpen/</link>
				<pubDate>Tue, 20 May 2025 09:23:16 +0100</pubDate>
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				<description>&lt;blockquote&gt;&#xA;&lt;p&gt;This is the second post in a 100-part series, where we take breakthrough AI papers and turn them into working code building the next generation of AI, one idea at a time.&lt;/p&gt;&#xA;&lt;/blockquote&gt;&#xA;&lt;h2 id=&#34;-summary&#34;&gt;🔧 Summary&lt;/h2&gt;&#xA;&lt;p&gt;In my previous post, I introduced &lt;code&gt;stephanie&lt;/code&gt; a &lt;strong&gt;modular implementation of the AI co-scientist concept&lt;/strong&gt;, inspired by DeepMind’s recent paper &lt;em&gt;&lt;a href=&#34;https://arxiv.org/abs/2502.18864&#34;&gt;Towards an AI Co-Scientist&lt;/a&gt;&lt;/em&gt;.&lt;/p&gt;&#xA;&lt;p&gt;But now, we’re going deeper.&lt;/p&gt;&#xA;&lt;p&gt;This isn’t just about &lt;strong&gt;running prompts through an agent system&lt;/strong&gt; it’s about building something radically different:&lt;/p&gt;</description>
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