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      <title>Articles by Dan Orlando</title>
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    <guid>https://danorlando.com/blog/genai/harness-engineering-paradox</guid>
    <title>The Harness Engineering Paradox: Building Stuff to Delete Is Harder Than Keeping It</title>
    <link>https://danorlando.com/blog/genai/harness-engineering-paradox</link>
    <description>Somewhere in your codebase there&#39;s a pipeline nobody touches. It was built because the model couldn&#39;t do something. But the model can now, and yet the pipeline still runs. The problem isn&#39;t awareness. It&#39;s that adding a component has a clear champion and deletion has none. Here&#39;s what it actually takes to make &quot;build to delete&quot; a practice instead of a principle.</description>
    <pubDate>Wed, 25 Mar 2026 00:00:00 GMT</pubDate>
    <author>undefined (Dan Orlando)</author>
    <category>generativeai</category><category>harnessengineering</category><category>architecture</category><category>systemdesign</category><category>agentsystems</category>
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    <guid>https://danorlando.com/blog/genai/multi-agent-is-a-trap</guid>
    <title>Multi-Agent AI Is a Trap</title>
    <link>https://danorlando.com/blog/genai/multi-agent-is-a-trap</link>
    <description>One team running a six-agent debate system switched to two agents with a strict state machine. Latency dropped from 18 seconds to 3. Cost per query dropped from $8-12 to $0.40. Accuracy changed by less than 1%. This wasn&#39;t a fluke. Information theory explains exactly why multi-agent systems can never outperform a single agent with full context.</description>
    <pubDate>Wed, 13 May 2026 00:00:00 GMT</pubDate>
    <author>undefined (Dan Orlando)</author>
    <category>generativeai</category><category>agenticai</category><category>architecture</category><category>systemdesign</category><category>agentsystems</category><category>informationtheory</category>
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    <guid>https://danorlando.com/blog/genai/retrieval-as-generation</guid>
    <title>Retrieval as Generation: The Architecture That Kills External Orchestrators</title>
    <link>https://danorlando.com/blog/genai/retrieval-as-generation</link>
    <description>An 8B-parameter model matches GPT-4o across five knowledge-intensive benchmarks and beats it on two. It does this by replacing the entire retrieval orchestration layer—confidence classifiers, query routers, rerankers, fusion logic—with four special tokens. No external components. When it fails, you read a transcript. That&#39;s the whole debugging story.</description>
    <pubDate>Thu, 16 Apr 2026 00:00:00 GMT</pubDate>
    <author>undefined (Dan Orlando)</author>
    <category>generativeai</category><category>rag</category><category>architecture</category><category>systemdesign</category><category>agentsystems</category><category>agenticai</category>
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    <guid>https://danorlando.com/blog/genai/single-agent-vs-multi-agent</guid>
    <title>Single vs. Multi-Agent: The Cognition-Anthropic Schism and Why Both Are Right</title>
    <link>https://danorlando.com/blog/genai/single-agent-vs-multi-agent</link>
    <description>Two frontier teams published production data that directly contradicts each other. Cognition says multi-agent architectures cause compounding information loss and single-threaded execution is the fix. Anthropic says multi-agent delegation beat a single agent by 90.2% on their research eval. Both are right—for the model version they tested on. Architectural best practices in agent systems have a six-month half-life.</description>
    <pubDate>Mon, 25 May 2026 00:00:00 GMT</pubDate>
    <author>undefined (Dan Orlando)</author>
    <category>generativeai</category><category>agenticai</category><category>architecture</category><category>systemdesign</category><category>agentsystems</category><category>informationtheory</category>
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    <guid>https://danorlando.com/blog/genai/why-your-rag-is-obsolete</guid>
    <title>Why Your RAG Is Already Obsolete (And What Works Instead)</title>
    <link>https://danorlando.com/blog/genai/why-your-rag-is-obsolete</link>
    <description>If your RAG pipeline runs the same retrieval strategy for every query, you&#39;re in one corner of a five-dimensional design space—and it&#39;s the worst-performing corner. Static pipelines leave up to 15% accuracy on the table and spend 3x the tokens they need to. The move to agentic retrieval is incremental, and each step compounds with every model generation.</description>
    <pubDate>Sat, 18 Apr 2026 00:00:00 GMT</pubDate>
    <author>undefined (Dan Orlando)</author>
    <category>generativeai</category><category>rag</category><category>architecture</category><category>systemdesign</category><category>agentsystems</category><category>agenticai</category>
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