Senior E-Commerce Manager & Digital Strategist
After actually using AI across real e-commerce work rather than reading about it, here is the honest summary: AI is genuinely transformative for a specific, narrow band of tasks, and a confident waste of time for a surprising number of others. The skill in 2026…
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"Serverless" is one of the most misleading words in technology, because it does not mean there are no servers. It means you do not have to think about them. With serverless computing, you hand a small piece of code to a cloud provider, it runs…
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This blog has no database, no web server running around the clock, and nothing on it that can really be "hacked" in the usual sense. It is a set of plain HTML files, built on my own laptop, stored in AWS, and delivered fast to…
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The single biggest thing slowing down your online store is almost certainly the very thing you put there to sell the product: the images. On a typical e-commerce page, images make up more than half of everything the browser has to download, and unoptimised product…
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If you want a fast, cheap, reliable way to serve your website's files, images, pages, assets, to customers anywhere in the world, the combination of two AWS services does almost all of the work: S3 stores the files, and CloudFront delivers them fast to every…
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You do not need to understand all of AWS. You need to understand maybe six services and one mental model, and that is enough to make good decisions, ask the right questions, and stop nodding along blankly when your developers or a vendor start talking…
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If you want to understand how an AI model turns your words into something a machine can actually work with, three ideas do almost all of the explaining: tokens, embeddings, and vectors. In one chain: an AI breaks your text into tokens (small chunks), then…
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Artificial intelligence, machine learning, and deep learning are not three competing things you choose between. They are three nested ideas, each one a more specialised part of the one before it. AI is the big outer goal: machines doing things that would normally need human…
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The real choice when you build a chatbot in 2026 is not "which of these three platforms." It is a choice between two fundamentally different approaches, and the three options split cleanly across that line. Amazon Lex and Google Dialogflow are managed conversational-AI platforms: they…
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Conversational AI is the umbrella term for any technology that lets a machine understand, process, and respond to human language in something close to a natural conversation, by text or by voice. That is the whole definition. It is not one product or one technique.
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If you want an AI assistant that actually knows your store, your real products, your current prices, your live stock, your specific return policy, the technique you need is RAG, retrieval-augmented generation. It connects the AI to your live business data so it answers from…
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The loudest take in 2026 is that the old rule-based chatbot is dead, that large language models have made the intent-based bot obsolete, and that you should rip out the scripts and let a generative model handle everything. It is a clean story, and it…
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Most chatbot projects are lost before anyone opens a tool. By the time the building starts, the decisions that decide success or failure, what the bot is for, what it will handle, how it will be measured, who will maintain it, have usually already been…
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Here is the trap almost every multilingual chatbot project falls into: treating "support more languages" as a translation task. You build the bot in one language, get it working, then hand the whole thing to a translation step and assume you are done. You are…
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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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