Field Notes

I sit down with Augstin Da Fieno Delucci, co-founder of Trilogica Global and former Director of Global Data and AI at Microsoft, to unpack a shift that changes how global teams should think about AI: treating context as a system, not a prompt. We’ve all gotten better at generation, better models, better prompting, better fine-tuning. Agustin argues that progress is real, but it hits a ceiling when...

Your translation management system might not be failing, but it can still be quietly throttling your localization program. Stephanie and Giulia Greco unpack why many client-side localization professionals feel stuck right now: TMS platforms that looked “end to end” in the sales cycle start showing real product gaps once you add more content types, more stakeholders, tighter release cycles, and mor...

Translation is no longer a single lane that runs through one department. We are watching localization spread into marketing stacks, product releases, support tools, and AI features like chatbots, sometimes without any coordination at all. That shift can feel empowering and fast, but it also creates a new question that companies cannot dodge: who owns quality when everyone can ship multilingual con...

Someone on your team ships a translated page overnight, looks like a hero, and nobody filed a localization request. Then you stumble on the copy later and think, “Did we do this?” That moment has a name: shadow localization. We dig into why it shows up even in mature programs, why AI and machine translation make it explode, and why treating it like a turf war is the fastest way to lose trust and r...

AI has made translation dramatically cheaper, yet a lot of localization leaders still feel like budgets are tightening and quality pressure is rising at the same time. We dig into why that paradox is real and how it shows up inside modern localization programs. The key is recognizing two different economic forces at work: a scale curve where lower unit costs drive more demand and explode the amoun...

AI translation has never looked better on the surface, yet plenty of teams still can’t make it work reliably in production. We dig into the uncomfortable reason: large language models are probabilistic systems, so the failure modes shift from obvious “bad machine translation” to believable, fluent mistakes that can quietly change meaning, introduce the wrong product definition, or slip in biased o...

Translation is getting faster every month, yet localization risk keeps rising. That’s not a paradox, it’s a signal that the bottleneck has moved. Stephanie from Argos sits down with Erik, an independent advisor at Vogt Strategy, to name the real constraint most enterprise teams are feeling: subject matter expert feedback loops that can’t keep up with AI-driven volume.  We dig into what SMEs actual...

“Quality” in translation sounds like a simple promise until you ask one uncomfortable question: what happens if it’s wrong? Stephanie and Erik unpack why so many localization pricing conversations get stuck on a single, vague standard, and how that confusion leads teams to either overbuy heavy workflows or quietly push risk onto vendors without paying for it.  We walk through three distinct ways t...

Metadata sounds like the boring part of localization until you realize it can be the difference between a scalable operation and a constant fire drill. We get specific about what’s at stake when a major share of a multi-billion-dollar industry goes to coordination, project management overhead, and transactional friction rather than value creation. If you’ve ever felt like your team is moving fast...

Localization is changing so fast that our old labels might not survive it. Stephanie sits down with Erik Vogt to unpack “solutions design,” the strategic discipline of turning a real business problem into a technology-supported solution that is both executable and commercially viable. If you have ever watched a team sprint to a proposal and then struggle to deliver, this conversation puts language...

“Just connect the systems” is the phrase that launches a thousand painful integration projects. We sit down to get honest about why connectors in localization and content operations are rarely plug and play, even when a vendor says they have one. Once you’re dealing with hundreds of possible content systems, dozens of TMS options, and different ideas of what a “job,” “string,” or “approval” even m...

AI can crank out marketing copy at a speed that feels like science fiction. The problem is that your audience still has the same 24 hours in a day, and their patience for generic content is getting thinner. Steph and Erik dig into what that means for AI marketing in the real world: the bottleneck has moved from production to attention, and the only sustainable edge is relevance, precision, and mes...

A CEO says “add AI,” a team nods, and suddenly everyone is shopping for tools instead of solving a problem. We dig into why that move derails so many AI initiatives and how to convert a fuzzy mandate into a project you can scope, staff, and measure without burning months on ambiguity.  Eric Vogt and I walk through a practical way to anchor AI implementation to business value: cost reduction, new r...

Fuzzy matches have been treated like a law of physics in localization: higher similarity means lower effort, so the discount grid must be fair. But when we look closely, that assumption starts to wobble. Steph sits down with Erik Vogt to ask the blunt question many teams are now debating out loud: are fuzzy matches dead, or are we just finally admitting we never proved they saved time the way we c...

AI LQA sounds like the shortcut every localization team wants, but the real story is more nuanced and a lot more useful. We sit down with Erik Vogt to define AI-driven linguistic quality assurance and quality estimation in plain terms, then follow the practical question that matters: how do you use AI to review more content without blowing up cost, time, or trust? If you manage translation quality...