<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Diagenic AI Library</title><description>Practitioner frameworks and insights on enterprise AI, workflow platforms, systems of record, governance, orchestration, and services economics.</description><link>https://diagenic.ai/</link><language>en-us</language><item><title>Enterprise Software Layer Model</title><link>https://diagenic.ai/frameworks/enterprise-software-layer-model/</link><guid isPermaLink="true">https://diagenic.ai/frameworks/enterprise-software-layer-model/</guid><description>A practical model for placing enterprise AI work across systems of record, data platforms, semantic meaning, inference, orchestration, and governance.</description><pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate><category>enterprise AI</category><category>systems of record</category><category>workflow</category><category>governance</category><category>architecture</category></item><item><title>AI Governance and Control Layers</title><link>https://diagenic.ai/frameworks/governance-density/</link><guid isPermaLink="true">https://diagenic.ai/frameworks/governance-density/</guid><description>Governance should rise with operational consequence, not model novelty. Production AI needs control, evidence, and an owner inside the workflow.</description><pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate><category>governance</category><category>AI agents</category><category>risk</category><category>workflow</category></item><item><title>Inference vs Orchestration</title><link>https://diagenic.ai/frameworks/inference-vs-orchestration/</link><guid isPermaLink="true">https://diagenic.ai/frameworks/inference-vs-orchestration/</guid><description>Inference is the model producing an output. Orchestration is the logic around that call: what happens before, during, and after, including data access, tools, permissions, retries, and action.</description><pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate><category>orchestration</category><category>AI agents</category><category>workflow</category><category>governance</category></item><item><title>Services Operating Leverage</title><link>https://diagenic.ai/frameworks/si-operating-leverage/</link><guid isPermaLink="true">https://diagenic.ai/frameworks/si-operating-leverage/</guid><description>AI hits labor-heavy delivery first. Lasting services value requires economics that do not depend on adding a person for every unit of work.</description><pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate><category>services economics</category><category>systems integrators</category><category>private equity</category><category>operating leverage</category></item><item><title>Systems of Record After AI</title><link>https://diagenic.ai/frameworks/systems-of-record-as-substrate/</link><guid isPermaLink="true">https://diagenic.ai/frameworks/systems-of-record-as-substrate/</guid><description>ERP and core systems of record remain official and slow while daily work moves into faster workflow, inference, and interface layers above them.</description><pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate><category>systems of record</category><category>ERP</category><category>workflow</category><category>enterprise architecture</category></item><item><title>The Consulting Pyramid Has Collapsed. Can AI Services Become a Diamond?</title><link>https://diagenic.ai/insights/consulting-pyramid-to-diamond/</link><guid isPermaLink="true">https://diagenic.ai/insights/consulting-pyramid-to-diamond/</guid><description>AI hits the bottom of the consulting labor pyramid first. The question is whether a services firm can change shape, or only pass efficiency back to clients as price pressure.</description><pubDate>Mon, 22 Jun 2026 00:00:00 GMT</pubDate><category>services economics</category><category>systems integrators</category><category>consulting</category><category>private equity</category></item><item><title>What Should PE Ask Before Buying an AI Services Firm?</title><link>https://diagenic.ai/insights/pe-questions-ai-services-firm/</link><guid isPermaLink="true">https://diagenic.ai/insights/pe-questions-ai-services-firm/</guid><description>AI readiness in services firms cannot be measured by demos or partner badges. Diligence should test revenue quality, delivery margin, and whether AI changes economics.</description><pubDate>Mon, 15 Jun 2026 00:00:00 GMT</pubDate><category>private equity</category><category>services economics</category><category>diligence</category><category>AI services</category></item><item><title>Systems of Record Are Losing the User Interface War</title><link>https://diagenic.ai/insights/systems-of-record-losing-ui-war/</link><guid isPermaLink="true">https://diagenic.ai/insights/systems-of-record-losing-ui-war/</guid><description>The system of record may remain authoritative, but AI agents, workflow platforms, and orchestration tools increasingly own where users work.</description><pubDate>Mon, 08 Jun 2026 00:00:00 GMT</pubDate><category>systems of record</category><category>AI agents</category><category>workflow platforms</category><category>user experience</category></item><item><title>ERP Is Not Dead. It Is Becoming Infrastructure.</title><link>https://diagenic.ai/insights/erp-is-not-dead/</link><guid isPermaLink="true">https://diagenic.ai/insights/erp-is-not-dead/</guid><description>AI is not replacing ERP and systems of record. It is changing where work happens, pushing the official record toward infrastructure while faster tools own the action surface.</description><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><category>systems of record</category><category>enterprise AI</category><category>ERP</category><category>enterprise architecture</category></item></channel></rss>