
		<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
			<channel>
				<title>José David Baena – Distributed Systems Engineer</title>
				<link>https://josedavidbaena.com</link>
				<description>Production notes and source-backed analysis on distributed systems, messaging infrastructure, open-source internals, and model engineering.</description>
				<language>en-us</language>
				<managingEditor>josedab@gmail.com (José David Baena)</managingEditor>
				<webMaster>josedab@gmail.com (José David Baena)</webMaster>
				<lastBuildDate>Wed, 29 Jul 2026 00:00:00 GMT</lastBuildDate>
				<atom:link href="https://josedavidbaena.com/tags/production/feed.xml" rel="self" type="application/rss+xml"/>
				
		<item>
			<guid>https://josedavidbaena.com/blog/kimi-k3/03-api-production-state-tools-caching</guid>
			<title>Kimi K3 API State: Tools, Caching, and Failure Modes</title>
			<link>https://josedavidbaena.com/blog/kimi-k3/03-api-production-state-tools-caching</link>
			<description>Kimi K3 is conversation-stateless at the API boundary; preserve full assistant messages, tool results, cache identity, and terminal-state checks.</description>
			<pubDate>Wed, 29 Jul 2026 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>kimi-k3</category><category>api</category><category>tool-calling</category><category>context-caching</category><category>production</category>
		</item>
	
		<item>
			<guid>https://josedavidbaena.com/blog/tiny-language-models/tiny-llm-case-studies-production</guid>
			<title>Tiny LLM Deployment Patterns: Architecture Blueprints from Published Benchmarks</title>
			<link>https://josedavidbaena.com/blog/tiny-language-models/tiny-llm-case-studies-production</link>
			<description>Deployment patterns for tiny LLMs in healthcare, legal, manufacturing, and edge—grounded in published benchmarks from Microsoft, Apple, and MLPerf.</description>
			<pubDate>Mon, 13 Oct 2025 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>machine-learning</category><category>deployment-patterns</category><category>production</category><category>benchmarks</category><category>architecture</category>
		</item>
	
			</channel>
		</rss>
	