Insights
Original guides to analytics, AI, application development and the business decisions that connect them.
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Read articleEvaluate technology through explicit outcomes, full ownership costs, and credible evidence. Separate capacity from cash savings and use review gates to decide whether to expand, revise, or stop.
Read articleReduce legacy-system risk through incremental changes, explicit boundaries, and tested recovery. Prioritise business pain while protecting existing behaviour, data integrity, and day-to-day operations.
Read articleEvaluate forecasts against realistic baselines and historical decision conditions. Use time-aware testing, business-relevant error measures, and uncertainty to guide planning without treating predictions as facts.
Read articleBuild automation with clear boundaries, proportionate approvals, visible exceptions, and tested recovery. Keep responsibility with people while reducing repetitive work in suitable business processes.
Read articlePlan integrations around ownership, business events, and recovery. Learn how API contracts, duplicate handling, permissions, and reconciliation keep connected tools from creating new operational confusion.
Read articleDefine an MVP that tests a business assumption through a complete user journey. Control scope without neglecting permissions, data integrity, accessibility, or operational readiness.
Read articleUnderstand when retrieval, fine-tuning, or simpler prompting fits a business task. Compare information freshness, behaviour, permissions, evaluation, and ongoing maintenance before choosing an approach.
Read articleAssess data quality against the task you want AI to support. Prioritise critical fields, trace problems to their source, and establish ownership before scaling a pilot.
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