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Technical Debt Groupings The technical debt headings can be grouped as follows: · Structural Debt: Architecture, Integration, Data, Platform · Execution Debt: Code, Testing, Process, Operations · Knowledge Debt: Documentation, Comprehension · Experience Debt: UX · Risk Debt: Security · Economic Debt: Portfolio Accumulation Patterns of Debt Categories Not all debt grows linearly. Each has a distinct accumulation curves and trigger mechanisms. How Cost Compounds (Hidden Econo

For intelligence to be applicable, fluid, and effective, it needs a good substrate of technology to work on. All Enterprises have technical debt due to various reasons. It is necessary to keep track of it and pay off certain types of debt to fully utilize Applicable Intelligence. Technical debt has various components to it: depending on the source of the debt and the area it pertains to. Different types of debt have different origin stories, accumulation patterns, and costs t

(originally published here) Enterprises do not experience technology as abstract capability. They experience it through applications. Applications are where work gets done. They are where employees make decisions, customers receive service, suppliers interact, transactions flow, exceptions get resolved, and business processes become real. For all the talk about Artificial Intelligence, Applications are the conduit for any and all intelligence to surface, engage, and effect an

The most useful writing about AI does not start with tools. It starts with decisions. That is the thread running through the Applicable Intelligence newsletter on LinkedIn: artificial intelligence matters when it helps leaders make better choices, build stronger teams, reduce risk, and create measurable value. The promise is not magic. The promise is practical intelligence applied to real business problems. This post brings together a set of summary-style reflections inspired

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