Senior E-Commerce Manager & Digital Strategist
The hard part of building a chatbot was never the technology. I learned this in 2019, building a natural-language chatbot from scratch for a large hotel group, across dozens of locations and several languages, back when "conversational AI" was a research term and not a…
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RAG, retrieval-augmented generation, is a way of making an AI model answer from a specific, trusted set of documents instead of relying only on what it absorbed during training. Before the model writes its answer, the system goes and fetches the most relevant material from…
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A hallucination is when an AI model produces an answer that sounds completely plausible and is completely false. Not a glitch, not a bug in the usual sense, but a confident, fluent, well-formed answer that happens not to be true. Understanding why this happens is…
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MCP, the Model Context Protocol, is an open standard that gives AI models a single, consistent way to connect to external tools and data. Instead of building a custom integration for every combination of AI model and service, you build one MCP connection and any…
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A large language model is a system that has been trained to do one deceptively simple thing: predict the next word. Show it a stretch of text, and it guesses what most likely comes next, then it guesses again, and again, one piece at a…
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An AI agent is a system that takes a goal, breaks it into steps, uses tools to carry those steps out, and decides on its own what to do next based on what just happened. That last part is the whole difference. A chatbot answers…
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The honest answer to "which automation tool should I use?" is that it depends on three things: how technical your team is, how sensitive your data is, and how much volume you will run. But there is one detail underneath all of it that almost…
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If you have ever read an automation tutorial and quietly stalled at the words "webhook," "API," and "trigger," this is for you. These three terms sit underneath almost every automation you will ever build, and the jargon makes them sound far more technical than they…
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Almost every store pours its automation budget into the moment before the sale and abandons the customer the moment after it. Cart recovery, retargeting, checkout nudges, all heavily automated. Then the order goes through, and the experience falls off a cliff into a generic "thanks…
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Most automation advice is a list of things you should automate. This is the opposite list, and it is more useful, because the expensive mistakes in automation are almost never "we failed to automate something." They are "we automated something we should have left alone."…
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Before you automate anything, you need to know what your team actually does all day. Not what the org chart says they do, not what they would say if you asked them in a meeting, but the real, fifteen-minute-by-fifteen-minute truth of where the hours go.
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If your audience lives entirely on a platform you don't own, you don't have an audience. You have a lease, and the landlord can change the terms overnight, without warning and without explanation. I was reminded of this last week in the bluntest possible way,…
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Here is the whole distinction in one sentence: a scheduled automation runs at a fixed time whether or not anything has happened, and an event-driven automation runs the moment something happens, whether or not the clock says it should. Everything else is detail. That detail…
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In December 2025, one of Amazon's own internal AI tools failed and quietly took down a system for thirteen hours before anyone noticed. Thirteen hours. At Amazon. With Amazon's engineering resources and monitoring budget behind it. I open with that because it settles an argument…
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Ask most e-commerce teams what their operations cost, and they will point you to the obvious line items. Software subscriptions. Fulfilment fees. Headcount. What almost nobody can tell you is the cost of the work itself, the hours that disappear every week into copying data…
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