Notes from Forja
Operational notes on AI in retail.
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How Magalu's Lu became a WhatsApp salesperson that converts 3x the app
Lu converts better on WhatsApp than in Magalu's own app. But the channel and twenty years of brand move the number, not the model. Here's what you could copy.
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Shelf-out has three causes. Only one is a forecasting problem.
We audited a regional chain's shelf-out SKU by SKU. Only a third was forecasting. The director was about to buy a better forecast to fix the wrong problem.
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What is a forward-deployed engineer and why the term matters in retail
A forward-deployed engineer isn't a consultant or a remote developer. It's who writes code against your real data and hands the running operation back to your team.
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McDonald's ended the IBM drive-thru AI. It lacked a number, not technology.
In 2021 McDonald's and IBM tested drive-thru voice ordering. In 2024 they ended it. The AI kept improving, but nobody set the number that lets the human leave.
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Linear: issue tracking is dead. The 25% says more about retail AI than the 75%.
Linear: 75% of enterprise workspaces run agents; 25% of issues are now written by agents. The number behind it changes how retail AI projects need to be organized.
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Forward-deployed engineer vs traditional consultancy vs AI platform
There are three paths to do AI in retail: platform, consultancy, or implementer. The right question is not which is best. It is which fits your operation.
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Before the code, the criterion: what to measure in week one
Before the first line of code, three things have to be decided: the number, the range, and the review trigger. Without them, an AI project is aspiration, not a project.
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Klarna didn't fail at AI. It failed to define when AI should have stopped.
In January 2024 Klarna announced $60M in savings from AI. In May 2025 it began rehiring. The AI worked. What was missing was the criterion for when it should have stopped.