AI OperationsRetail
Product-Level P&L: The Margin Leak No Dashboard Will Show You
How product-level contribution P&L connects retail orders, inventory, advertising and fulfilment data to reveal which SKUs to scale, repair, test or clear.
Read more →Practical writing on AI training, implementation, and what actually works in production.
How product-level contribution P&L connects retail orders, inventory, advertising and fulfilment data to reveal which SKUs to scale, repair, test or clear.
Read more →Owners already know their winners. The margin leaks in the few hundred products nobody has time to think about. Here is the five-source join and the weekly loop that turns them into decisions.
Read more →People keep asking me what AI means for their role. I always struggle to answer, and I finally worked out why: the question asks for a prediction, and AI quietly changed which decision strategy wins.
Read more →A website with no CMS, no plugins and no passwords. The owner publishes by approving drafts from AI agents wired to his own operations data.
Read more →A fast-growing apparel brand needed to detect hero SKUs before they stocked out. We built two AI agent workspaces, a breakout probability engine, and 75 automated tests in 10 days. Here's the full case study.
Read more →You invested in dashboards, alerts, and automated reports. Decisions didn't speed up. They slowed down. Here's the mechanism nobody talks about.
Read more →We keep seeing the same thing: teams with more dashboards than decisions. Here's what's actually missing.
Read more →37 Python scripts. One ads manager who'd never opened a terminal. She generated more reports than the engineer who built it.
Read more →We audited 84,624 Display placements across 5 accounts and uncovered gaming sites, bot traffic, and spam eating ad budgets. Here's what we learned.
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