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				<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, 02 Sep 2026 00:00:00 GMT</lastBuildDate>
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			<guid>https://josedavidbaena.com/blog/distilled-engineering/llm-compression-decision-matrix</guid>
			<title>LLM Compression Decision Matrix: Let the Bottleneck Pick the Technique</title>
			<link>https://josedavidbaena.com/blog/distilled-engineering/llm-compression-decision-matrix</link>
			<description>Choose pruning, quantization, distillation, LoRA, or MoE from the production bottleneck, then re-gate the exported artifact on target hardware.</description>
			<pubDate>Wed, 02 Sep 2026 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>llm</category><category>model-compression</category><category>quantization</category><category>pruning</category><category>distillation</category><category>lora</category><category>mixture-of-experts</category>
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			<guid>https://josedavidbaena.com/blog/distilled-engineering/model-distillation-antipatterns</guid>
			<title>Model Distillation Breaks in the Same Ten Places Every Time</title>
			<link>https://josedavidbaena.com/blog/distilled-engineering/model-distillation-antipatterns</link>
			<description>A field guide to ten recurring distillation failures across data, evaluation, compression, serving, safety, and release governance.</description>
			<pubDate>Wed, 26 Aug 2026 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>model-distillation</category><category>llm</category><category>ai-safety</category><category>mlops</category><category>quantization</category><category>ai-engineering</category>
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		<item>
			<guid>https://josedavidbaena.com/blog/distilled-engineering/synthetic-data-factory</guid>
			<title>A Synthetic Data Factory Needs Four Gates Before It Needs More Prompts</title>
			<link>https://josedavidbaena.com/blog/distilled-engineering/synthetic-data-factory</link>
			<description>Build a synthetic-data factory with curriculum allocation, schema checks, deduplication, decontamination, quarantine, and versioned release manifests.</description>
			<pubDate>Wed, 19 Aug 2026 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>synthetic-data</category><category>model-distillation</category><category>llm</category><category>data-quality</category><category>python</category><category>ai-engineering</category>
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		<item>
			<guid>https://josedavidbaena.com/blog/distilled-engineering/dark-knowledge-soft-targets</guid>
			<title>Dark Knowledge: What a Teacher&#39;s Wrong Answers Are Actually Worth</title>
			<link>https://josedavidbaena.com/blog/distilled-engineering/dark-knowledge-soft-targets</link>
			<description>Learn what soft targets preserve beyond hard labels, how temperature and KL direction change the signal, and when top-k logit storage loses too much.</description>
			<pubDate>Wed, 12 Aug 2026 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>model-distillation</category><category>knowledge-distillation</category><category>llm</category><category>machine-learning</category><category>ai-engineering</category>
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		<item>
			<guid>https://josedavidbaena.com/blog/distilled-engineering/why-small-models-win-enterprise-ai</guid>
			<title>Why Small Models Win the Enterprise AI Cost Argument</title>
			<link>https://josedavidbaena.com/blog/distilled-engineering/why-small-models-win-enterprise-ai</link>
			<description>Use a measurable service envelope and break-even model to decide when a distilled student beats a frontier API — and when it does not.</description>
			<pubDate>Wed, 05 Aug 2026 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>model-distillation</category><category>llm</category><category>enterprise-ai</category><category>cost-optimization</category><category>ai-engineering</category>
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		<item>
			<guid>https://josedavidbaena.com/blog/frontier-model-engineering</guid>
			<title>Frontier Model Engineering: From Model Card to Production</title>
			<link>https://josedavidbaena.com/blog/frontier-model-engineering</link>
			<description>A four-workshop path from release forensics to durable agents, context storage, and topology-aware multi-GPU inference.</description>
			<pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>llm</category><category>ai-engineering</category><category>model-audit</category><category>distributed-inference</category>
		</item>
	
		<item>
			<guid>https://josedavidbaena.com/blog/nanochat/building-chatgpt-for-100-dollars</guid>
			<title>Build Your Own ChatGPT for $100</title>
			<link>https://josedavidbaena.com/blog/nanochat/building-chatgpt-for-100-dollars</link>
			<description>Train a complete ChatGPT-like system from scratch for $100: tokenizer, pretraining, SFT, RL, deployment—the full LLM pipeline for the price of dinner.</description>
			<pubDate>Tue, 14 Oct 2025 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>machine-learning</category><category>ai</category><category>tutorial</category><category>llm</category><category>deep-learning</category><category>pytorch</category>
		</item>
	
		<item>
			<guid>https://josedavidbaena.com/blog/tiny-language-models/tiny-llm-architecture-comparison</guid>
			<title>Tiny LLM Architecture Comparison: TinyLlama vs Phi-2 vs Gemma vs MobileLLM</title>
			<link>https://josedavidbaena.com/blog/tiny-language-models/tiny-llm-architecture-comparison</link>
			<description>Seven tiny models, one decision. Phi-2 wins on reasoning (56.7% MMLU). MobileLLM on speed (120 tok/s). Qwen on multilingual. Match constraints to model.</description>
			<pubDate>Sat, 20 Sep 2025 00:00:00 GMT</pubDate>
			<author>josedab@gmail.com (José David Baena)</author>
			<category>machine-learning</category><category>llm</category><category>architecture</category><category>benchmarks</category><category>comparison</category>
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