Hello — I’m Anaïs Dupont. Over the years I’ve spent time inside engineering teams, poking at data pipelines, and helping organisations ask the awkward questions about what exactly is feeding their models. In this piece I’ll walk you through a practical audit mindset for enterprise AI training datasets, focusing on five red flags that often precede data leaks, privacy violations, or...
I’ve been testing compressed vector embeddings for search pipelines for a while now, because the promise is...
I spent the last few weeks pushing a Pixel Tablet through a set of pro-photography chores: rapid culling, raw...
I bought a cheap smart plug for my kitchen lamp last month. It was under £50, tucked into a sale, with shiny app...
I spent a month living with the Tilt Five mixed-reality dev kit on my desk, on my coffee table, and — embarrassingly...
I wanted a private, offline note-taking assistant that I could carry around on a cheap, low-power device. The Raspberry...
I’ve helped teams evaluate incident management tooling from both an engineering and product perspective, and one...
I test AI products for a living, and one thing that never stops surprising me is how often "explainability" is treated as either a checkbox or a vague marketing line. Reviewers will praise a model for being "transparent" or criticize it for being a "black box" without giving readers concrete...
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I’ve spent years watching teams drown in time-series telemetry: terabytes of sensor data streaming into lakes, dashboards overflowing with metrics, and engineers still caught off guard when a pump or motor fails. The irony is that more data rarely equals better predictions — what matters is the...
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I’ve spent years helping teams choose and deploy security controls that actually get used — not just tick boxes for compliance. When it comes to multifactor authentication (MFA), the biggest failure isn’t cryptography or standards: it’s human behavior. Deploy the most secure method in the...
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I’ve spent years testing and explaining how software actually behaves in the wild, and bias in AI-powered hiring tools is one of those topics where nuance matters. On paper, an automated resume screener or an interview-sentiment model promises efficiency and consistency. In practice, those same...
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I’ve been obsessed with the idea that real intelligence doesn't have to live in the cloud. Watching devices that run for years on coin cells or tiny LiIon packs do genuinely useful, low-latency inference has felt like a slow-moving revolution for the last few years. TinyML — machine learning...
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I’ve been tracking the slow, steady shift toward passwordless authentication for years now — testing products, probing security claims, and watching organizations wrestle with the trade-offs. Passwordless is no longer a futuristic checkbox; for many enterprises it’s a practical way to reduce...
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I’ve spent years testing AI tools, writing about their quirks, and helping teams pick the right tech that actually fits their day-to-day work. Choosing an AI assistant for your team isn’t just about picking the model with the highest benchmark — it’s about matching capabilities to workflow,...
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I want developer pipelines that are secure, fast, and simple to understand. Over the years I’ve seen teams over-engineer CI/CD so much that it becomes the riskiest part of their product: secrets scattered in variables, build steps that run as privileged, and complex umbrella scripts no one dares...
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I’ve spent years building and securing cloud-native apps, and one lesson keeps coming back: even a single small virtual machine (VM) exposed to the internet can become your weakest link if you don’t harden it. This guide walks you through a pragmatic, step-by-step approach to hardening a small...
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I get asked a lot: can you trust OpenAI’s API with sensitive business data? As someone who tests and writes about cloud services and security, my short answer is: “it depends.” But that’s not very useful on its own. Below I walk through a practical, evidence-based risk checklist you can use...
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