I was a team leader by chance, as I was a good Individual Contributor (IC) with knowledge of localization quality assurance and good communication skills. My transition was difficult and bumpy, as I was not ready and did not know the differences between being an IC and a Localization Team Manager. Despite the challenges, my capacity to adapt helped me succeed. To successfully transition from an IC role to a Localization Manager role, one must have the right mindset, be surrounded by skilled professionals, and have a supportive manager. I now understand the differences and want to share my learnings with others.
Before any great translation comes great source content. In this post, I compare what I’ve learned from golf lessons to the localization world: success depends on how well you set up from the start. I share real examples, red flags to watch out for, and four practical pillars : governance, clarity, style, and global mindset that can make or break your localization process. If you want smoother workflows, better quality, and fewer headaches, the fix might not be downstream… it might be in your stance.
Talking to executives is never easy and feeling ignored makes it even harder. I’ve been there…..pitched a localization project I truly believed in… and never heard back. That experience stayed with me. Over time, I’ve learned what works (and what doesn’t) when trying to influence decision-makers.
In this post, I share 5 practical tactics that helped me go from feeling overlooked to getting buy-in (without changing the heart of what we do in Localization)
What if inclusive localization isn’t just the right thing to do but also the smartest way to break free from outdated pricing models? In this post, I explore the core elements of an inclusive localization strategy and why it might be the key to escaping the trap of price-per-word thinking.
Much is said about AI's threat to professionals in the localization industry. But the truth is that the AI + human combo has a lot of potential. In this blog post, you can learn about the role of an internal Localization team in the AI era.
Understanding in which areas AI is really powerful, and the ones that a human professional is superior is critical nowadays to maximize our impact and possibilities to stay relevant in the generative content world we are living in nowadays
If we want to treat localization like a product, we need to measure it like one. Traditional metrics like cost per word and delivery time still matter, but they don’t capture the full picture. In this post, I share four categories of product-style metrics: adoption, automation impact, strategic influence, and internal visibility that they can help you track the real value your localization team is creating across the company.
Localization as a Product means building solutions that make it easier for others to work with localization by turning our expertise into systems that are scalable and reusable.This shift doesn’t replace the service mindset. It builds on it.
We still support teams but we also design tools, workflows, and automations that reduce repetitive work and increase impact. Instead of translating on request, we enable content flows.
Instead of fixing the same problems again and again, we build systems that prevent them. This is how localization grows from being reactive support to becoming part of how the company builds and scales globally.
Just like the flywheel on a spinning bike, it’s hard to get going at first , there’s resistance. But once you build speed, it gets easier to keep the momentum.
In Globalization, it works the same way. You can enter at any point quality, user feedback, tooling, content…. and that push will start turning the wheel.
Each action builds on the next, and little by little, it helps the company move faster toward market expansion.
Consistently posting about our accomplishments on platforms like LinkedIn can quickly become tiresome for others. At the same time, not giving visibility to what we do or achieve can cause our work to go unnoticed, causing us to miss out on certain professional opportunities to advance our careers further.
Seven years ago, my twin Maria and I stood on the LocWorld stage in Warsaw and talked about Cultural Intelligence ….how culture shapes trust, feedback, leadership, and collaboration. Back then, the big question was: How can humans work better across cultures?
Today, that same question still matters but with a twist:
How can AI LLMs can work better across cultures?
In an AI-driven world, we’re seeing that language alone isn’t enough. Multilingual doesn’t mean multicultural. And as we rush to scale AI globally, cultural nuance is too often left behind.
Maybe it’s time to rethink how we build. Maybe it’s time for Cultural LLMs.