For the 10th year in a row, the Uruguayan Chamber of Information Technologies (CUTI) gathered Uruguayan tech companies to celebrate the “International Day of Women and Girls in Science” and inspire girls to explore tech careers. On April 25th, we welcomed over 30 girls aged 14 to 16 to our office.
In this blog post, I’ll share with you how “Techy por el Día” came about and how the day went in our office with the girls from Liceo 47.
The Gender Gap in Tech
Technology shapes our world in countless ways, from how we work and communicate to how we learn and understand the world around us. However, there’s a significant global challenge that we can’t ignore: the gender gap in tech. Women are often underrepresented in tech-related educational and professional fields, limiting their opportunities to contribute to and benefit from the industry (Píriz, 2024).
This disparity isn’t unique to any one country. Studies suggest that girls’ interest in technology tends to wane as they grow older due to a mix of cultural, social, institutional, and economic factors (ANEP, 2024). Uruguay stands out as a key player, being the largest per capita exporter of software in Latin America and the fourth-largest exporter in terms of dollars in Latin America (Uruguay XXI, 2021).
Bridging the Gender Gap: Initiatives in Uruguay
In 2015, the United Nations General Assembly declared February 11th as the International Day of Women and Girls in Science. The goal? Achieve full and equal access to and participation in science for women.
In Uruguay, institutions like the National Administration of Public Education (ANEP) are working to ensure girls and women have equal access to and participation in science and technology fields. This effort is crucial to reducing the gender gap and harnessing the diverse talents and perspectives that drive innovation.
According to ANEP (2024), “Promoting, encouraging, incentivizing, and inspiring the study of sciences and technology is essential to contribute to the personal and professional growth of girls, young women, and women, and key to enriching the scientific and technological field with diverse talents and creative and innovative perspectives to face current challenges and sustainable development.”
Our Experience Hosting Techy por el Día 2024
On Thursday, April 25th, we had the pleasure of welcoming over 30 girls aged 14 to 16 to our offices.
We kicked off the day with a shared lunch and an introductory talk about what we do at Kaizen Softworks, the meaning of our company’s name, our different teams, and introducing our horizontal and collaborative approach.
To introduce the following activities, we explained the process of creating a digital product: ideation, design, development, testing, and implementation. Then, we randomly divided the girls into four groups to carry out workshops on UX design, development, Quality Assurance (QA), and Information Technology (IT).
Workshops
IT Activity
This activity began in the entrance hall of our office, where we organized a comprehensive tour of our facilities. During this tour, we provided a detailed explanation of our infrastructure—its composition and why it’s crucial for the smooth functioning of the company. In the server room, we introduced the rack, the nerve center from which all information is distributed throughout the office.
Key concepts like access points, cabling, and smart devices present in different areas were discussed. In the workspaces, we highlighted the installed equipment and underscored its importance to ergonomics and the overall employee experience.
Apart from work areas, we toured common areas like the kitchen, barbecue zone, courtyard, and pool—essential spaces for leisure and downtime for our team members. Our People Care team took the opportunity to share information about our dynamics, benefits, and integration activities that contribute to making Kaizen’s culture unique.
UX Design Workshop
Our UX Design Workshop started off with an engaging presentation about our dedicated UX design team. We highlighted each team member’s unique roles and emphasized the importance of collaborative effort in crafting meaningful and user-friendly experiences.
Using real-life examples, we painted a vivid picture of how good and bad user experiences are part of our everyday lives. For the hands-on activity, we chose Instagram as a case study—being a widely recognized and used app among the participants. Together, we identified usability issues they encountered when using the app, and then collectively brainstormed solutions using creative techniques like the prioritization matrix and the “crazy 8” tool.
The fun activity served as a practical introduction to the subsequent stages that a design team would undertake, such as prototyping, testing, and implementing the design.
Development Workshop
In the Development Workshop, we aimed to provide a sneak peek into a developer’s daily life. We steered clear of overly advanced concepts, considering the participants’ basic or zero level of knowledge. Using an example of a project task board, we explained the significance of “To Do,” “In Progress,” “Testing,” and “Done”—fundamental for fostering collaboration within a development team.
To make the experience relatable to the participants, we turned once again to Instagram, exploring what new functionalities could be implemented or fine-tuned. We broke down several functions into small tasks that the participants could work on, making the experience interactive and engaging.
Quality Assurance (QA) Workshop
Our QA workshop aimed to demystify the functional tester role in a fun and practical way. We used a simple device—a calculator—as an example to facilitate understanding of more complex concepts. Various versions of the calculator with different bugs were projected on a screen for an interactive, hands-on experience.
Through collaboration and creating exploratory test cases together, we encouraged participants to identify bugs. We also used everyday examples to emphasize the importance of detecting and fixing bugs, highlighting how this improves the user experience.
Wrapping Up Techy por el Día
Finally, we gathered all the teams together to share experiences from the different activities they participated in. One of our goals was to ignite the girls’ interest in technology, so we also shared resources such as Ceibal, Jovenes a Programar, and INEFOP where they could further expand their knowledge if they wish.
We want to extend a big thank you to the girls and staff from Liceo 47, as well as those girls who came to participate in this edition with us. We hope this is just one of many opportunities where we can contribute our bit to stimulate interest and the development of local talent in our country!
For the 10th year in a row, the Uruguayan Chamber of Information Technologies (CUTI) gathered Uruguayan tech companies to celebrate the “International Day of Women and Girls in Science” and inspire girls to explore tech careers. On April 25th, we welcomed over 30 girls aged 14 to 16 to our office.
In this blog post, I’ll share with you how “Techy por el Día” came about and how the day went in our office with the girls from Liceo 47.
The Gender Gap in Tech
Technology shapes our world in countless ways, from how we work and communicate to how we learn and understand the world around us. However, there’s a significant global challenge that we can’t ignore: the gender gap in tech. Women are often underrepresented in tech-related educational and professional fields, limiting their opportunities to contribute to and benefit from the industry (Píriz, 2024).
This disparity isn’t unique to any one country. Studies suggest that girls’ interest in technology tends to wane as they grow older due to a mix of cultural, social, institutional, and economic factors (ANEP, 2024). Uruguay stands out as a key player, being the largest per capita exporter of software in Latin America and the fourth-largest exporter in terms of dollars in Latin America (Uruguay XXI, 2021).
Bridging the Gender Gap: Initiatives in Uruguay
In 2015, the United Nations General Assembly declared February 11th as the International Day of Women and Girls in Science. The goal? Achieve full and equal access to and participation in science for women.
In Uruguay, institutions like the National Administration of Public Education (ANEP) are working to ensure girls and women have equal access to and participation in science and technology fields. This effort is crucial to reducing the gender gap and harnessing the diverse talents and perspectives that drive innovation.
According to ANEP (2024), “Promoting, encouraging, incentivizing, and inspiring the study of sciences and technology is essential to contribute to the personal and professional growth of girls, young women, and women, and key to enriching the scientific and technological field with diverse talents and creative and innovative perspectives to face current challenges and sustainable development.”
Our Experience Hosting Techy por el Día 2024
On Thursday, April 25th, we had the pleasure of welcoming over 30 girls aged 14 to 16 to our offices.
We kicked off the day with a shared lunch and an introductory talk about what we do at Kaizen Softworks, the meaning of our company’s name, our different teams, and introducing our horizontal and collaborative approach.
To introduce the following activities, we explained the process of creating a digital product: ideation, design, development, testing, and implementation. Then, we randomly divided the girls into four groups to carry out workshops on UX design, development, Quality Assurance (QA), and Information Technology (IT).
Workshops
IT Activity
This activity began in the entrance hall of our office, where we organized a comprehensive tour of our facilities. During this tour, we provided a detailed explanation of our infrastructure—its composition and why it’s crucial for the smooth functioning of the company. In the server room, we introduced the rack, the nerve center from which all information is distributed throughout the office.
Key concepts like access points, cabling, and smart devices present in different areas were discussed. In the workspaces, we highlighted the installed equipment and underscored its importance to ergonomics and the overall employee experience.
Apart from work areas, we toured common areas like the kitchen, barbecue zone, courtyard, and pool—essential spaces for leisure and downtime for our team members. Our People Care team took the opportunity to share information about our dynamics, benefits, and integration activities that contribute to making Kaizen’s culture unique.
UX Design Workshop
Our UX Design Workshop started off with an engaging presentation about our dedicated UX design team. We highlighted each team member’s unique roles and emphasized the importance of collaborative effort in crafting meaningful and user-friendly experiences.
Using real-life examples, we painted a vivid picture of how good and bad user experiences are part of our everyday lives. For the hands-on activity, we chose Instagram as a case study—being a widely recognized and used app among the participants. Together, we identified usability issues they encountered when using the app, and then collectively brainstormed solutions using creative techniques like the prioritization matrix and the “crazy 8” tool.
The fun activity served as a practical introduction to the subsequent stages that a design team would undertake, such as prototyping, testing, and implementing the design.
Development Workshop
In the Development Workshop, we aimed to provide a sneak peek into a developer’s daily life. We steered clear of overly advanced concepts, considering the participants’ basic or zero level of knowledge. Using an example of a project task board, we explained the significance of “To Do,” “In Progress,” “Testing,” and “Done”—fundamental for fostering collaboration within a development team.
To make the experience relatable to the participants, we turned once again to Instagram, exploring what new functionalities could be implemented or fine-tuned. We broke down several functions into small tasks that the participants could work on, making the experience interactive and engaging.
Quality Assurance (QA) Workshop
Our QA workshop aimed to demystify the functional tester role in a fun and practical way. We used a simple device—a calculator—as an example to facilitate understanding of more complex concepts. Various versions of the calculator with different bugs were projected on a screen for an interactive, hands-on experience.
Through collaboration and creating exploratory test cases together, we encouraged participants to identify bugs. We also used everyday examples to emphasize the importance of detecting and fixing bugs, highlighting how this improves the user experience.
Wrapping Up Techy por el Día
Finally, we gathered all the teams together to share experiences from the different activities they participated in. One of our goals was to ignite the girls’ interest in technology, so we also shared resources such as Ceibal, Jovenes a Programar, and INEFOP where they could further expand their knowledge if they wish.
We want to extend a big thank you to the girls and staff from Liceo 47, as well as those girls who came to participate in this edition with us. We hope this is just one of many opportunities where we can contribute our bit to stimulate interest and the development of local talent in our country!
A while ago we noticed something pretty common: everyone wanted to share more knowledge internally, but nobody wanted another heavy corporate ritual.
Internal talks usually start with good intentions and slowly disappear. They take time, preparation, and energy. And at some point people start feeling like they need to be experts before presenting anything.
So we tried the opposite.
15 minute talks.
Small topics.
Low pressure.
And one important rule: every session had to leave something useful behind. A tool, a workflow, an idea, a shortcut, a new way to approach a problem. Something people could actually use after the talk ended.
We didn’t want theory that went nowhere.
Somehow, that ended up working much better than we expected.
The idea was to reduce friction
Screenshot of the shared topic pool
Tiny Knowledge Bytes is intentionally simple:
anyone can suggest topics
anyone can end up presenting
you don’t need to master the topic
talks can come from experiments, client problems, tools or random discoveries
sessions should leave something practical behind
if nobody volunteers, the system picks someone for us
The goal was making knowledge sharing feel lightweight instead of exhausting.
Some of the best talks start with:
“I tried this yesterday and it was weird.”
The topic pool started growing on its own
Over time, topics started coming from everywhere.
Sometimes someone took a course and used a Tiny Knowledge Byte as a way to give something back to the team. Other times, a client problem triggered research into new tools, workflows or AI approaches.
A lot of sessions start from curiosity or necessity more than planning.
And honestly, the mix is part of what makes it interesting.
Sometimes a UX session drifts into Computer Vision. Sometimes someone technical shares a visual workflow that half the design team ends up adopting later.
There’s not much curation. It behaves more like a constant exploration system.
Then another problem appeared: choosing who presents
And this is where things became unnecessarily dramatic.
Nobody wanted to be “the person who chooses”. So we started adding absurd layers of randomness until we somehow ended up building a full internal app called 2FS.
Two Factor Sorteo.
Yes, it’s real.
The wheel proposes. The oracle decides.
The logic is simple.
First, a wheel picks someone.
Then a Magic 8 Ball decides whether destiny approves the selection.
If the oracle rejects the person, the process starts again.
That’s it.
The app accidentally became part of the learning loop too
Apps developed for the Tiny Knowledge Bytes.
2FS originally started as an excuse to experiment with:
Claude Code
Claude Design
design systems
editorial interfaces
motion and microinteractions
Eventually those same explorations turned into future Tiny Knowledge Bytes.
The tool we used to select speakers started generating new topics itself.
The system started feeding itself
One of the most interesting side effects is that people started building things outside their usual role because of previous Tiny Knowledge Bytes.
2FS itself is a good example. A designer saw sessions about Claude tooling and AI workflows and thought:
“Maybe I can actually build this.”
What started as a ridiculous speaker selection tool became a real product experiment involving Claude Code, interface systems and interaction design.
Then it came back into the Tiny Knowledge Bytes circuit as a new talk.
That loop became surprisingly valuable:
someone learns something,
tries it,
builds something with it,
and eventually inspires someone else to do the same.
What ended up mattering most
Final Oracle Certificate.
Over time we realized knowledge sharing works much better when:
it doesn’t require huge preparation
it’s allowed to be imperfect
it mixes different disciplines
it leaves something practical behind
and somehow involves a mystical wheel connected to a Magic 8 Ball
At that point, it stops feeling like another internal obligation and starts feeling like something people genuinely want to keep alive.
Just this month, I built a full design system in about 20 hours.
What used to take weeks, sometimes months, is now dramatically faster. So… what actually changed? And more importantly: what didn’t?
Design systems take time. On complex platforms, they can take hundreds of hours.
We were working with a large and complex product where inconsistencies had started to pile up. Different modules had evolved in isolation, teams were making independent decisions, and there were no shared guidelines. The answer was clear: we needed a design system.
AI tools were just starting to emerge back then. They were mostly useful for simple tasks as they tended to hallucinate when things got complex. Developers had started using them earlier than designers, MCP didn't exist yet, and Figma plugins were the best automation we had.
But the context has changed. Fast.
The Manual Era
We did what most teams did. We stopped, and we built it. Manually.
Picture two designers, a mountain of inconsistencies, and no map. We had to cross-reference information manually, digging through the code, detecting what could be merged, agreeing on naming conventions, deciding how to name components. Hours and hours of discussion until we finally landed on a solution.
In the end, we got there. A cleaner system, faster workflows, and for the first time, both teams speaking the same visual language. Hard-won, but it worked.
But now every month a new AI model seems to be released. Design is finally catching up with what developers faced about two years ago. New tools arose, and with that, the scope of our work as designers completely changed.
The Human Factor
For an internal project, I used our Kaizen site as a reference, combined with documentation from industry leaders as a guideline.
I started in v0, which is essentially a chat interface where you can generate UI components through prompts. I fed it the colors, typographies, and a reference image, and from there it was a back-and-forth: the AI generated, I reacted, adjusted, and pushed until the output matched what I had in my head. And just like that, I started prompting my way through a Design System.
Once a component was ready, I used the html.to.design plugin to bring it into Figma (yes, plugins are still alive!). Think of it as a bridge: the plugin exports designs directly from the browser into a Figma file.
Inside Figma, the intervention was more hands-on. First, I checked that everything was visually consistent with what was defined in v0: colors, typography, styles. Then I used Figma's built-in AI to rename all the component layers using BEM convention (something that would have taken a significant amount of time to do so manually).
BEM, which stands for Block Element Modifier, is a widely adopted naming convention in CSS. It structures layer names hierarchically and predictably, for example: button__label--disabled.
Using it keeps the code clean, readable, and consistent, especially when you're working alongside a developer who needs to understand what came out the other side.
Beyond naming, I also made sure the layer structure would generate the right properties when building component sets in Figma, so that all the variants would be correctly exposed and usable. My team also pointed out that adding descriptions to components and variants was key as context for any agent using them through an MCP.
The last step was connecting everything to Windsurf via MCP. With a frame selected in Dev Mode, Windsurf could read the Figma file and use the components to build more complex screens.
We worked closely with a developer throughout this phase. Not just for the technical knowledge, but because having someone who reads code fluently meant catching things we wouldn't have spotted otherwise. The design role here was direction and supervision: making sure the AI used the components correctly and didn't invent solutions where context was missing.
Every step of the process had a human decision behind it.
An Unexpected Discovery
At one point, before we had any of the naming conventions figured out, I selected a frame and asked Windsurf to build a form using the components inside it, styled to match a specific card. The developer next to me was skeptical until he saw the result, and then he was just as surprised as I was.
What we realized is that the MCP wasn't reading layer names to understand context. It was reading everything inside the frame, even the loose text sitting alongside the components. Good naming is still worth doing. But the MCP doesn't need it to understand what it's looking at.
Learning to Talk to an AI
The more specific and contained your prompt, the better the outcome. We started with the most atomic component: the button, and worked outward from there. Each approved component became context for the next one, so the system gradually picked up the visual language we were building.
At some point I got ambitious and asked for five cards in a single prompt: blog card, service card, testimonial card, stats card, feature card… structures, states and all. The AI delivered.
Visually, everything looked fine. Then the developer looked at the code and pointed out that all five cards were independent components instead of variants of one. For a design system, that breaks everything.
One correction prompt fixed it. But it was a good reminder: the AI does exactly what you ask, not what you mean. And fixing it after the fact can cost more than getting it right from the start.
Some Things Learned Along the Way
Precision is key. Natural language is fine when you're asking for a cooking recipe, but when referring to a component, if you say things like "create" instead of "add", you'll probably end up with a whole new set of components instead of additional variants of an existing one.
The "Frame" is the context: MCPs can read everything inside the frame you select. This is a game-changer. It means the "naming conventions" debate might be shifting. If the AI understands the context visually and structurally, will we still spend hours discussing nomenclature in 2027?
No matter what happens, you can always roll back in less than 5 minutes and start over.
Work closely with a developer: they can help you understand MCPs and clear up any code-related doubts. Once you start to grasp their logic, you'll learn very quickly how to prompt in ways that AI actually understands.
There's nothing to lose by asking the AI to follow a specific naming convention for the code. It keeps everything clean and readable, and it takes no extra effort.
The AI covers roughly 80% of the work (generation, variations, exploration...), but the remaining 20% is where quality lives, and that part is not delegable. The AI executes. The judgment is still yours. And if you skip the review, you're not saving time: you'll spend it later.
Context matters more than tooling. What you don't define, the AI will invent. Small components may be resolved well, but large interfaces require more definition from the start. A well-defined system scales. An undefined one generates inconsistencies faster than you can fix them.
Figma is no longer the mandatory starting point. It's useful as a visual reference, a QA space, or a consolidation layer. But the AI doesn't need it. We still do.
There's no single right workflow yet. What you do depends on the project. We're in a transition moment where the tools change faster than the standards. The best thing you can do right now is experiment.
What AI Still Can’t Replace
Through all of this, a few things became very clear. These are the parts that didn’t change:
Knowing when something looks off. The AI generates, but it doesn't notice when the result doesn't feel right. That eye is yours.
Direction and supervision. The AI used the components we gave it, but without someone supervising it, it invents solutions where there is no context to work from.
The definition of done is still a human call, whether it's a conversation with a PO, a stakeholder, or just the designer's criteria. There's no prompt for that.
The context: knowing why certain decisions matter, what a component should communicate, what the user will actually feel. Business knowledge, stakeholder dynamics, unwritten rules, empathy for the end user. These take years to build and live in the people doing the work, not in the tools they use.
My Two Cents
The tools changed, and that gave me the chills, but throughout this experience I found that the designer's role is more alive than ever.
What once took a team weeks can now be prototyped in hours. That’s not a threat; it’s an invitation to get curious.
I'm still figuring a lot of this out, and I suspect most of us are. There's no right workflow yet, and honestly, that's fine. We are in a transition where tools change faster than standards. The best thing you can do is experiment. Don't wait for a "definitive" workflow, it might be obsolete by next month.
Go ahead, try prompting your way through a component. You might be surprised how fast the system starts to take shape.
