“Design used to be the seasoning you’d sprinkle on for taste. Now it’s the flour you need at the start of the recipe.’’

— John Maeda, Designer and Technologist
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Privacy Policy

This Privacy policy was published on March 1st, 2020.

GDPR compliance

At UX GIRL we are committed to protect and respect your privacy in compliance with EU - General Data Protection Regulation (GDPR) 2016/679, dated April 27th, 2016. This privacy statement explains when and why we collect personal information, how we use it, the conditions under which we may disclose it to others and how we keep it secure. This Privacy Policy applies to the use of our services, products and our sales, but also marketing and client contract fulfilment activities. It also applies to individuals seeking a job at UX GIRL.

About UX GIRL

UX GIRL is a design studio firm that specialises in research, strategy and design and offers clients software design services. Our company is headquartered in Warsaw, Poland and you can get in touch with us by writing to hello@uxgirl.com.

When we collect personal data about you
  • When you interact with us in person – through correspondence, by phone, by social media, or through our uxgirl.com (“Site”).
  • When we get personal information from other legitimate sources, such as third-party data aggregators, UX GIRL marketing partners, public sources or social networks. We only use this data if you have given your consent to them to share your personal data with others.
  • We may collect personal data if it is considered to be of legitimate interest and if this interest is not overridden by your privacy interests. We make sure an assessment is made, with an established mutual interest between you and UX GIRL.
  • When you are using our products.
Why we collect and use personal data

We collect and use personal data mainly to perform direct sales, direct marketing, and customer service. We also collect data about partners and persons seeking a job or working in our company. We may use your information for the following purposes:

  • Send you marketing communications which you have requested. These may include information about our services, products, events, activities, and promotions of our partners. This communication is subscription based and requires your consent.
  • Send you information about the services and products that you have purchased from us.
  • Perform direct sales activities in cases where legitimate and mutual interest is established.
  • Provide you content and venue details on a webinar or event you signed up for.
  • Reply to a ‘Contact me’ or other web forms you have completed on our Site (e.g., to download an ebook).
  • Follow up on incoming requests (client support, emails, chats, or phone calls).
  • Perform contractual obligations such as invoices, reminders, and similar. The contract may be with UX GIRL directly or with a UX GIRL partner.
  • Notify you of any disruptions to our services.
  • Contact you to conduct surveys about your opinion on our services and products.
  • When we do a business deal or negotiate a business deal, involving sale or transfer of all or a part of our business or assets. These deals can include any merger, financing, acquisition, or bankruptcy transaction or proceeding.
  • Process a job application.
  • To comply with laws.
  • To respond to lawful requests and legal process.
  • To protect the rights and property of UX GIRL, our agents, customers, and others. Includes enforcing our agreements, policies, and terms of use.
  • In an emergency. Includes protecting the safety of our employees, our customers, or any person.
Type of personal data collected

We collect your email, full name and company’s name, but in addition, we can also collect phone numbers. We may also collect feedback, comments and questions received from you in service-related communication and activities, such as meetings, phone calls, chats, documents, and emails.

If you apply for a job at UX GIRL, we collect the data you provide during the application process. UX GIRL does not collect or process any particular categories of personal data, such as unique public identifiers or sensitive personal data.

Information we collect automatically

We automatically log information about you and your computer. For example, when visiting uxgirl.com, we log ‎your computer operating system type,‎ browser type,‎ browser language,‎ pages you viewed,‎ how long you spent on a page,‎ access times,‎ internet protocol (IP) address and information about your actions on our Site.

The use of cookies and web beacons

We may log information using "cookies." Cookies are small data files stored on your hard drive by a website. Cookies help us make our Site and your visit better.

We may log information using digital images called web beacons on our Site or in our emails.

This information is used to make our Site work more efficiently, as well as to provide business and marketing information to the owners of the Site, and to gather such personal data as browser type and operating system, referring page, path through site, domain of ISP, etc. for the purposes of understanding how visitors use our Site. Cookies and similar technologies help us tailor our Site to your personal needs, as well as to detect and prevent security threats and abuse. If used alone, cookies and web beacons do not personally identify you.

How long we keep your data

We store personal data for as long as we find it necessary to fulfil the purpose for which the personal data was collected, while also considering our need to answer your queries or resolve possible problems. This helps us to comply with legal requirements under applicable laws, to attend to any legal claims/complaints, and for safeguarding purposes.

This means that we may retain your personal data for a reasonable period after your last interaction with us. When the personal data that we have collected is no longer required, we will delete it securely. We may process data for statistical purposes, but in such cases, data will be anonymised.

Your rights to your personal data

You have the following rights concerning your personal data:

  • The right to request a copy of your personal data that UX GIRL holds about you.
  • The right to request that UX GIRL correct your personal data if inaccurate or out of date.
  • The right to request that your personal data is deleted when it is no longer necessary for UX GIRL to retain such data.
  • The right to withdraw any consent to personal data processing at any time. For example, your consent to receive digital marketing messages. If you want to withdraw your consent for digital marketing messages, please make use of the link to manage your subscriptions included in our communication.
  • The right to request that UX GIRL provides you with your personal data.
  • The right to request a restriction on further data processing, in case there is a dispute about the accuracy or processing of your personal data.
  • The right to object to the processing of personal data, in case data processing has been based on legitimate interest and/or direct marketing.

Any query about your privacy rights should be sent to hello@uxgirl.com.

Hotjar’s privacy policy

We use Hotjar in order to better understand our users’ needs and to optimize this service and experience. Hotjar is a technology service that helps us better understand our users experience (e.g. how much time they spend on which pages, which links they choose to click, what users do and don’t like, etc.) and this enables us to build and maintain our service with user feedback. Hotjar uses cookies and other technologies to collect data on our users’ behavior and their devices (in particular device's IP address (captured and stored only in anonymized form), device screen size, device type (unique device identifiers), browser information, geographic location (country only), preferred language used to display our website). Hotjar stores this information in a pseudonymized user profile. Neither Hotjar nor we will ever use this information to identify individual users or to match it with further data on an individual user. For further details, please see Hotjar’s privacy policy by clicking on this link.

You can opt-out to the creation of a user profile, Hotjar’s storing of data about your usage of our site and Hotjar’s use of tracking cookies on other websites by following this opt-out link.

Sharethis’s privacy policy

We use Sharethis to enable our users to share our content on social media. Sharethis lets us collects information about the number of shares of our posts. For further details, please see Sharethis’s privacy policy by clicking on this link.

You can opt-out of Sharethis collecting data about you by following this opt-out link.

Changes to this Privacy Policy

UX GIRL reserves the right to amend this privacy policy at any time. The latest version will always be found on our Site. We encourage you to check this page occasionally to ensure that you are happy with any changes.

If we make changes that significantly alter our privacy practices, we will notify you by email or post a notice on our Site before the change takes effect.

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Innovation

AI Tools for Visual Creativity: From Pixels to Art (Part 1)

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The number of AI tools is growing every week, and this trend is unlikely to change any time soon. Rather, we expect the use of AI algorithms and models to trend even further. The creators of almost every application we know are trying to use AI in their products in one way or another and not be left behind in this crazy technological race.

Today, practically every tool used for editing photos or videos can boast that it allows retouching or background removal with just one click. Almost every text editor allows for content generation based on a typed prompt. We can generate ideas, summarize articles, or write them in full by entering only a simple instruction. Tools from Microsoft or Google use AI models for data analysis, creating summaries, charts, and suggesting various solutions. Browser plugins allow for automatic email responses, or analyzing a page for SEO or conversion purposes. It's easy to create a video where we can speak in any foreign language, and no one will even realize that we don't know that language. People in business, marketing, creative fields, bloggers, artists, writers, data analysts, literally everyone can speed up their work today by taking advantage of AI benefits.

However, because there is so much choice, it's easy to become simply overwhelmed by it all. In the end, instead of speeding up our work and being like all those super-productive people who flood us with posts on LinkedIn or X (formerly Twitter), we don't know where to start and what tool to choose. We don't know what is actually worth attention and what should be avoided. I think it's obvious that if everyone started implementing AI in the solutions they offer, among the quite large number of great tools we will also find those that are still a long way from actually helping us. Many tools available on the Internet are still just cool toys, but when it comes down to it, unfortunately, we wouldn't want to use their results in our business.

Sure, there are a few tools that everyone talks about, tools that are currently enjoying a triumph of popularity, and therefore they must be the best. To a large extent, it's hard to disagree, but even these theoretically best tools have their drawbacks and won't always be suitable for what we specifically want to do. Additionally, there's the issue of cost, or what the entry threshold is to achieve really solid results. Besides, if we dig a little deeper, we'll find a range of products that are really quite good and often allow for quick completion of a specific task for free.

For the purposes of this article, we tested several dozen different AI tools ourselves and chose those that, in our opinion, really do the job or are simply worth keeping an eye on because they are developing in an interesting direction.

We decided to split the article into two parts. Firstly, to examine the recommended tools more closely and discuss, in our opinion, all the essential aspects. Secondly, to avoid boring you and not take up too much of your time. Shorter content will be easier to digest. So, in the first part, which you are reading now, we will present the first 5 tools. The next 5 will be in the second part. We recommend reading both, as it is in the second part that we will describe the less obvious tools.

Additionally, both parts will primarily focus on tools that specialize in working with images and videos. Topics like working with text, music, or enhancements in AI for productivity will be addressed in separate posts.

We will start with 3 well-known and recognizable tools that, in the context of generating and editing images, have recently become what ChatGPT is in the context of generating text. Even though probably everyone knows or is familiar with how they work, we believe that a post about AI tools omitting the most important players would simply be incomplete. Setting aside the various downsides of each tool, this trio really deserves special recognition!

Midjourney

If we talk about generating images using AI, one of the first names that comes to mind is indeed Midjourney. Not without reason, as it is currently one of the best tools for creating images based on a typed prompt.

A digitally rendered image of a diverse group of about fifteen children sitting or standing in a brightly lit, futuristic classroom or science lab. They are gathered in a circle around a glowing, holographic display of a human head with a detailed, illuminated brain inside, representing neuroscience or AI education

Currently, the most advanced and latest version is Midjourney V5.2 released in June 2023. However, it's worth keeping your finger on the pulse because it has just been announced that Midjourney V6 will see the light of day before Christmas 2023... we can't wait to see what the creators have prepared for us this time!

Midjourney, in addition to standard image generation, offers a bunch of interesting functionalities that diversify and improve the target results, namely:

  • Additional parameters - we have at our disposal a large number of various parameters that we can add to the prompt, thereby deciding, for example, what proportions the generated image should have, what elements it should not contain, what the image quality should be, or how much we want to deviate from the prompt and rely on the tool's creativity (level of artistry and abstraction).
  • Zoom Out - a feature that allows you to generate content around an existing image without changing the original. We can understand this as a literal zooming out, seeing what is beyond our frame - the tool enlarges the area/canvas of our photo and in a sense 'draws in' what is not visible. It works extremely well. I think many of us have taken a photo where a key part of the frame was accidentally cut off - now we can fix that!
  • Pan - similar to Zoom Out, but this time we can ask to generate a fragment of the image only in a specific direction.
  • Upscaler - the ability to enlarge a photo without losing quality.
  • Vary - the ability to generate new suggestions only for a given part of the image based on our selection. We can, for example, generate a robot and then select only its head and replace it with something else.
  • Video generation - in our opinion, some time is needed to refine this function, perhaps it will work much better in Midjourney V6. At this point, we have many tools that simply do it better.

What distinguishes Midjourney from the competition is primarily realism, refined compositions, attention to detail, and high-quality generated images.

However, Midjourney also has its disadvantages, and we are not talking about the price.

  • Reduced precision - in contrast to, for example, DALL-E 3 (which I'll discuss in a moment), Midjourney does not always adhere to the user's instructions and intentions. Sometimes the generated images significantly deviate from what we entered in the prompt. The tool allows for quite a bit of creative freedom.
  • Problem with generating text in images - this may be a limitation for some users, instead of text we often get some random shapes and smears.
  • Limited availability - the tool operates through Discord, which is not a major issue, but we realize that this may discourage some people. But, according to the latest news, it will change soon. 7 days ago Midjourney has begun testing an “alpha” version of its new website which includes image creation. For now, it’s accessible only for users who have generated 10000+ images.
  • Content Censorship - Midjourney implements content censorship that may be restrictive for users seeking complete creative freedom.
Cost

From $96 to $1152 per year (depending on the chosen subscription plan).

DALL-E 3

A product from OpenAI, which until recently couldn't really compare to what Midjourney offers. However, everything changed with version 3, namely DALL-E 3.

A digitally rendered, highly detailed image of various wild animals, including a prominent lion, several tigers, giraffes, and zebras, gathered in a lush, idealized savanna landscape with a small stream, large acacia trees, and mountains in the background, set up as a photo backdrop or mural

The tool is available as part of a ChatGPT Plus subscription or for free as part of Bing's Copilot service from Microsoft. It can be said that the fact that we can generate images completely free of charge is a huge advantage, but DALLE-3 also deserves recognition for several other reasons:

  • High quality of generated images - it's not yet the realism and attention to detail as seen in Midjourney, but the results are really impressive.
  • Precision - DALLE-3 is great at interpreting user intentions and reproducing entered prompts. Here it fares much better than Midjourney, offering a high degree of accuracy in realizing the users' vision.
  • Ability to generate text on images - unlike the competition, DALL-E 3 easily incorporates text into its graphic creations.
  • Ease of use - unlike traditional image generators that require specific prompts or instructions, DALL-E 3 allows users to interact through conversation, making it more accessible and intuitive.

The main downside of DALL-E 3, in our opinion, remains a certain limitation in generating realistic creations. Images generated using DALLE-3 have a specific style, and despite their excellent quality, it is often easy to notice that a given graphic was generated by AI.

In addition, our editing options are quite limited, i.e. we cannot, for example, correct a fragment of the generated photo. In this case, you need to regenerate the entire image and hope that the model goes in the right direction.As with Midjourney, DALL-E 3 is quite a heavily censored image generator, especially when used inside ChatGPT.

Cost

$20 per month, included in ChatGPT Plus. Free in Bing's Copilot.

Adobe Firefly

Adobe probably needs no introduction and it is also easy to guess that this technological giant has not been left behind in this race.

Adobe Firefly is actually a family of generative artificial intelligence models, offered as a separate product on the website https://firefly.adobe.com or in the form of functionalities integrated into various Adobe applications.

A graphic, stylized illustration in warm, muted colors featuring a large tiger with dark purple and pale yellow stripes standing in a savanna landscape. The background includes acacia trees and abstract, orange-and-purple mountainous formations under a muted gray sky

By entering the mentioned website, we currently have the following features available:

  • Text to image - a classic image generator, based on a typed prompt, similar to DALL-E 3 and Midjourney. However, what sets Adobe's approach apart is the remarkable simplicity of the tool. Initially, we get a simple text field to enter our instructions - there are no options for entering parameters, uploading files, etc. After generating images, we do receive an intuitive editing panel, where we can adjust our results. Besides numerous sliders, we get many predefined options that allow for adding specific effects, setting lighting, composition, color scheme, choosing between a more artistic approach and realism. We can also upload an image as a reference, then the algorithm will adjust subsequent results to the style of our reference.
  • Generative fill - this tool allows for modifying images using brushes and selection tools. We can remove objects from an image, generate new elements in the selected area, remove the background, etc. Image editing enters a completely new dimension, namely, for example, in a few seconds we can remove someone who accidentally appeared in the frame, or add sunglasses that we forgot to wear. In our opinion, it is better to use this functionality directly in Adobe Photoshop, where it offers much more.
  • Generative recolor - the tool allows you to automatically recolor vector images based on the entered prompt. Thanks to this, we can adapt the illustration to, for example, match a specific mood or theme.
  • Text effects - allows you to generate text with a specific visual effect, e.g. you can enter "Hello, my name is Stephany" and ask for the letters to be covered with eucalyptus leaves or to look like they are embroidered. In our opinion, it's still just a cool toy and not something we want to use every day.

What is fantastic about Adobe's solutions is that AI functionalities are also available directly in their applications.

In Adobe Photoshop, we have access to the already mentioned Generative fill with some enhancements. Specifically, we can use options like expand. Similar to the zoom-out and pan functions in Midjourney, here we can also generate something beyond the canvas area, allowing us to freely 'expand' our images.

In Adobe Illustrator, the most interesting option is generating vector illustrations using a prompt. This is a revolutionary approach to graphic design. We no longer need to know how to draw to prepare a beautiful illustration for a website or a book.

Additionally, there are also AI enhancements in Adobe Premiere Pro and Adobe Express, but we won't elaborate on that here.

What also deserves attention is the issue of ethics and copyright. Adobe trains its models based on licensed content from Adobe Stock and public domain content, where the copyright has expired. This means that everything we generate is based on data sets collected in a fully ethical manner, and the complete copyright of the produced image belongs to the generator.

In conclusion, Adobe offers its users a lot. After testing all the AI features, we can confidently say that the quality and results are really good, and this is complemented by ease of use and integration within Adobe's flagship applications.

Downsides? At this moment, we can point out three things that may discourage potential users, namely:

  • Although the generated images are really good, they still are not at the level of Midjourney. Adobe is characterized by a certain style, and this is often visible in the generated creations. Often, the results can seem too 'candy-like'.
  • In the case of Midjourney and DALL-E 3 within ChatGPT, we deal with quite strong censorship. However, it seems that Adobe Firefly leads in this regard. The censorship from Adobe is really significant and can often be a limitation. For example, attempts to generate creations using words like 'soldier' or 'bikini' are futile.
  • Adobe Firefly operates on a generative credits system, providing users with a set amount of image generations and edits. This means that users have a limited number of uses. Of course, additional credits can be purchased, but in our opinion, this could ultimately be more expensive than, for example, a Midjourney subscription. If someone is already paying for a Creative Cloud subscription, they are allotted a certain number of credits.
Cost

Varies according to the country. Has a free tier.

Leonardo.Ai

Another fantastic and rapidly developing tool is Leonardo.Ai. It is essentially a web application (along with an API) created by independent creators and based on Stable Diffusion models. Similar to the previous three applications, it allows for image generation and editing.

Screenshot of the Leonardo.AI interface for 'AI Image Generation,' showing the prompt 'face builded from rectangles, white background, minimalistic, Picasso style, vivid colors, pink, blue, orange,' and the resulting four generated images of abstract female faces composed of geometric shapes in a Picasso-inspired style

What characterizes this application is the ability to change the model used to generate our images. At the moment, we have access to dozens of models - some of them simply differ in version (older, newer), but others are models specifically trained for generating images with certain characteristics. For example, we can choose a model tailored for generating photorealistic images or a model that generates isometric views.

At the moment, among the most important functionalities of Leonardo.Ai we can distinguish:

  • Image Generation - generating images based on a textual prompt. Similar to Adobe, we have an intuitive panel with a range of additional options to customize our instructions.
  • Live Canvas - an interesting feature that allows for generating an image in real time based on what we are currently drawing. Of course, we can fully edit everything, determine the level of consistency with our sketch, and so on. At the moment, it's more like a toy, but it's developing in a very good direction.
  • Canvas Editor - an extensive editing environment that allows you to manipulate imported images. Removing unwanted objects from the photo, generating image fragments, adjusting the proportions, etc.
  • 3D Texture Generation - generating and modifying textures based on imported OBJ files. It can help, for example, in preparing game assets.
  • Motion - generating videos based on a textual prompt, the functionality is expected to be available in the near future.

The main drawback is that most of the features is locked in the free version of the tool. However, the tool itself, although heavily limited, remains available without the need to purchase a subscription. Every day, we have access to a total of 150 tokens, which we use to perform various actions in Leonardo.Ai. Not all actions consume the same number of tokens, e.g. high-resolution images cost more.

Cost

From $12 to $60 per month. Has a free tier.

HeyGen

Have you ever wondered what it would be like to speak fluently in dozens or even hundreds of foreign languages? HeyGen is a tool that won't teach you to speak these languages, but it will create the impression that you are using them perfectly.

Screenshot of the HeyGen platform interface, specifically the 'Voice' section, showcasing a selection of available AI voices (e.g., Tony - Professional, Jenny - Professional, Sara - Cheerful) categorized by language, gender, and use cases, with the main section encouraging users to 'Let Your Unique Voice Shine Brilliantly

HeyGen is currently one of the most popular and best-known tools for creating video avatars. We have quite a few interesting features at our disposal, allowing us to create professional videos based on a clip recorded by us, written text, and/or recorded audio. There are several combinations, including:

  • Creating a video avatar based on one of over a hundred available avatars and your own text or audio file.
  • Creating a completely custom avatar based on a provided video clip and your own text or audio file.
  • Translating a provided video into over 40 available foreign languages with lip-sync technology. The final result looks very natural.
  • Changing or improving your voice or generating audio for the entered text.

The tool has incredible potential in the field of marketing, promoting products, preparing offers, or training materials. From now on, you can, for example, put a video on your website where you talk about your product in Korean. The applications are enormous.

Cost

From $29 per month. Free plan for 1-min max duration video per month.

That's all the tools in this part. To read about the remaining 5, please visit the second part.

Besides, stay tuned and remember that these are still just tools. How we use them and whether they benefit us depends entirely on us. Thankfully, as of now, the most powerful tool at our disposal remains the human mind.

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5 min

Women in UX: Support, Mentorship & Community

The UX and UI industry is evolving at lightning speed-new tools, roles, and expectations emerge constantly. Yet despite progress toward inclusion, women working in this space still face clear challenges: underrepresentation, limited access to support networks, and lower visibility in high-impact projects.

That’s why women in UX/UI are increasingly turning to the power of networking-the intentional building of professional relationships that lead to real outcomes: mentorship, collaboration, access to clients, and greater confidence.

Why Women’s Networking Matters in UX/UI

According to PwC’s Women in Tech report, women represent only around 26% of the workforce in the European tech industry (Source: PwC UK). While UX tends to have better gender balance than other tech sectors, women are still less likely to hold leadership roles, as shown by the Design Forward Fund report by InVision (Source: InVision).

Having access to a supportive, like-minded network can help women grow faster, share experiences, and make better-informed career decisions. It’s not just about visibility-it’s about confidence, connection, and community.

Where to Find Mentorship and Support in UX/UI

Thankfully, there’s a growing ecosystem of initiatives built specifically for women in UX and UI. Here are some of the most valuable communities and mentorship platforms to explore:

  • Ladies that UX – A global community of women in UX with local chapters in cities like Warsaw, Kraków, and Gdańsk. Offers meetups, workshops, and an open, inclusive space to share experiences

  • Women in UX (UXPA) – Part of the UXPA network, offering events, resources, and a strong international network of women UX professionals

  • Dare IT – A Polish initiative offering mentoring, development programs, and hands-on projects for women entering tech

  • Tech Leaders Poland – A free mentoring program run by the Perspektywy Foundation, connecting women in IT with experienced mentors

  • ADPList – A global mentoring platform that allows you to book free 1:1 sessions with experienced UX designers, researchers, and product strategists

  • Slack & LinkedIn groups – Active communities like "Women in UX," "Design Mentorship," "UX Design Polska," and "SheDesigns" regularly share job leads, portfolio feedback, and professional advice.

And remember—mentorship goes both ways. If you’ve gained experience, consider becoming a mentor yourself. It’s not only rewarding, but also a great way to build leadership skills and give back to the community.

Collaboration Among Women: Projects, Trust, and Shared Opportunities

Networking isn’t just about chatting or exchanging business cards. It’s about building real relationships that can lead to joint ventures, shared clients, and long-term partnerships.

Among women in UX, these types of collaboration are gaining popularity:

  • Online coworking sessions, where freelancers and remote workers support each other while working on personal or client projects.

  • Mastermind groups, where a small group of peers meets regularly to set goals, share insights, and offer accountability.

  • Feedback workshops, where participants present their UX case studies and get constructive, real-time input.

If you’re just starting out and don’t have a large contact base-don’t worry. You can begin with one LinkedIn message, one industry event, or one short online chat with someone you admire. It’s all about taking the first step.

How Companies and Agencies Can Empower Women in UX/UI

While grassroots communities are powerful, employers and agencies also play a vital role in creating supportive ecosystems. Organizations that build internal mentorship programs, fund conference participation, and create open knowledge-sharing spaces contribute directly to stronger, more confident teams.

At UX GIRL, we recognize how crucial representation and inclusion are in the design process. That’s why we actively support women at every stage of their UX careers-by sharing knowledge, promoting female experts, and collaborating across our partner network. We believe women in UX shouldn’t just have a seat at the table-  they should help shape the entire strategy.

What You Can Do This Week

Don’t wait for your network to build itself. Here are three simple steps you can take right now:

  1. Join one of the communities mentioned above (e.g., Ladies that UX or Dare IT).

  2. Sign up for a mentorship program-as a mentee or a mentor.

  3. Reach out to one inspiring woman in your field and ask for a short coffee chat online.

Building a network of women in UX/UI is an investment that pays off-with better projects, more confidence, and a stronger, more inclusive design industry.

At UX GIRL, we actively support young women entering the field of UX.
We believe that real change happens when women are not just present in the industry, but truly empowered to lead, create, and grow. That’s why we regularly share knowledge, promote women experts, and collaborate within our community.

And right now-we have an open call for our mentorship program.
If you’re just starting out in UX and looking for guidance, encouragement, and practical experience, we invite you to join us.
Let’s build the future of UX together-one strong connection at a time.

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5 min

AI Shifts Us From Monitoring Numbers to Understanding Situations

For years, product teams have relied on metrics: KPIs, dashboards, charts. We’ve tracked conversion rates, NPS scores, session times, and click-throughs. But in today’s complex digital landscape-filled with nuanced user journeys and multi-touch interactions-numbers alone no longer tell the full story.

Artificial Intelligence is changing that. It’s not just processing data-it’s interpreting it. The shift is no longer from data to insights, but from measurements to meaning. AI enables us to move from simply monitoring activity to understanding the real-life situations behind the data.

The Problem: More Data, Less Clarity

Imagine a product team managing a mobile app. They notice a drop in daily active users. The dashboard makes the trend obvious—but not the cause.

Why are users dropping off? Is it a bug? New onboarding? Competitive noise?

This is the daily frustration for many teams. Analytics dashboards present signals, not narratives. Numbers show what is happening, but not why. As a result, decisions are often based on instinct instead of evidence.

The Power of Situational Awareness

Modern AI-powered by large language models and predictive algorithms-offers something beyond quantitative metrics. It enables situational awareness.

For example, instead of just reporting that “users bounce after visiting the product page,” AI might analyze multiple sources and suggest:
“Users are dropping off because the availability details are hidden behind a tab, causing friction in their decision-making.”

This is a leap-from interpreting events in isolation to connecting user behavior, interface patterns, and emotional friction.

AI can combine:

  • Support chat transcripts,
  • Voice-of-customer feedback,
  • Heatmaps and session recordings,
  • Usability testing outcomes,
  • Analytics patterns filtered by device, region, or time.

Together, these inputs form a rich narrative that answers:
What’s happening? Why is it happening? What should we do about it?

Redefining the Role of Product Teams

When AI handles the heavy lifting of data interpretation, product teams are free to do what they do best: make decisions, explore hypotheses, and run experiments.

AI doesn’t replace human intuition-it enhances it. Instead of endless reports, teams can respond to actionable, situation-based insights.

The Product Owner no longer has to guess why a user churned.
The UX researcher no longer has to manually synthesize 50+ interview transcripts.
The designer no longer operates in the dark.

With AI, the team sees the whole picture-faster.

But First, a Few Guardrails

AI-driven UX analysis is powerful-but not foolproof. To use it responsibly:

  1. Garbage in, garbage out. If your data is biased, incomplete, or misleading, your insights will be too.
  2. Context still matters. AI models lack cultural, emotional, and strategic context. Teams must interpret outputs critically.
  3. Transparency is key. Your team should know what data the AI is using and how it arrives at its recommendations.

How to Start Shifting From Metrics to Meaning

AI is not the future—-it’s the now. Here’s how to start the shift today:

  • Start with one source of qualitative data (like support tickets or survey responses) and use AI to identify common patterns or friction points.
  • Review AI-generated insights in weekly UX or product rituals to discuss, challenge, and prioritize actions.
  • Compare AI interpretation with your existing KPIs to create a more complete, situational view of your users.
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5 min

Design Debt: When to Redesign vs. When to Iterate

Abstract pastel illustration of interconnected UI elements, buttons, charts, and icons arranged across a soft pink background, resembling a playful, stylized interface made of 3D shapes and lines.

Over time, digital products accumulate design debt-incremental changes, quick fixes, and legacy decisions that gradually degrade the user experience. This often results in a fragmented, inconsistent interface that frustrates users and complicates workflows. Organizations face a critical dilemma: should they invest in a full redesign or make iterative improvements to refine the existing system?

A complete overhaul can be costly, risky, and disruptive. It requires significant resources, may alienate existing users, and can introduce new usability challenges. On the other hand, continuous iteration allows for gradual refinement but risks perpetuating flawed design foundations. The key to making the right decision lies in assessing the extent of design debt, understanding its impact, and weighing the costs and benefits of each approach.

Understanding Design Debt: The Silent UX Killer

Design debt accumulates in several ways:

  • Quick fixes and workarounds often address immediate needs but create long-term usability issues
  • Legacy design decisions may no longer align with user needs or technological advancements
  • Inconsistent UI patterns emerge when multiple teams contribute without a cohesive design system
  • Lack of user feedback loops results in decision-making based on assumptions rather than data

Ignoring design debt can lead to a frustrating user experience, increased support costs, and lost revenue. Indicators of high design debt include frequent user complaints, declining conversion rates, and significant usability issues that require extensive workarounds.

The Case for Iterative Improvements

When the core UX remains functional but users experience friction in specific areas, iteration is often the best approach. This method allows teams to make targeted enhancements without disrupting familiar workflows. Iteration works well under several conditions:

  • Users struggle with specific pain points that usability testing can pinpoint and address
  • Minor UI inconsistencies create confusion but do not fundamentally hinder functionality
  • Data-driven insights suggest small optimizations can improve engagement and conversions
  • The current system remains scalable and does not impose excessive technical constraints

Successful iteration requires a structured approach-identifying pain points, testing solutions, and continuously refining the design based on real-world feedback.

The Case for a Full Redesign

Sometimes, design debt reaches a point where incremental improvements can no longer salvage the user experience. When usability flaws are deeply embedded in the system, a redesign becomes the only viable option. This is particularly necessary when the product relies on outdated technology that restricts innovation, when maintaining the existing system incurs higher costs than rebuilding, or when competitors offer a far superior UX that threatens market relevance.

However, redesigns come with substantial risks. A poorly executed overhaul can alienate loyal users, disrupt workflows, and lead to significant financial setbacks.

One infamous example is Digg’s 2010 redesign. Digg, once a popular social news aggregator, launched a drastic redesign (Digg v4) that removed key features users loved, such as the ability to view upcoming stories before they became popular. The new version was seen as prioritizing publishers over its core community, leading to a massive user exodus. Within weeks, competitors like Reddit saw an influx of former Digg users, and Digg’s traffic plummeted. This serves as a cautionary tale of how failing to align a redesign with user needs can have catastrophic consequences.

Airbnb search results page showing a row of cabin-style listings with large thumbnail photos, including wooded cottages and modern tiny houses in the Czech Republic and Poland, along with prices, dates, ratings, and guest-favorite labels.

In contrast, Airbnb’s methodical redesign, informed by extensive user research, showcases how a well-planned revamp can drive engagement and growth. In 2014, Airbnb redesigned its search and booking experience to better accommodate user preferences and enhance visual storytelling. The redesign incorporated high-quality photography, improved filters, and a more intuitive booking flow. By leveraging A/B testing and gathering extensive feedback before the full rollout, Airbnb ensured a smooth transition, resulting in increased user satisfaction and higher conversion rates. Their data-driven approach demonstrates how a well-executed redesign can elevate a product without alienating its user base.

Making the Right Call: A Decision Framework

Deciding between iteration and redesign requires a structured evaluation process. Companies should begin with an in-depth usability audit, assessing the severity of design debt through usability scores, conversion rates, churn data, and direct user feedback. Identifying whether the primary issues are surface-level or deeply rooted in the system will clarify whether an iterative approach suffices or a full redesign is necessary.

If usability issues are isolated and correctable through focused adjustments, iteration is likely the better route. Teams should establish clear KPIs and user experience benchmarks to measure the success of iterative changes. Small-scale A/B testing can validate improvements before full implementation, reducing risks and allowing for incremental refinements.

For cases where fundamental usability issues persist, a redesign may be necessary. However, it should be approached methodically—by conducting thorough user research, prototyping potential solutions, and testing new designs before a full-scale launch. A phased rollout can mitigate risk, ensuring that users adapt smoothly and reducing potential backlash from drastic changes.

Beyond usability concerns, business strategy and technical feasibility should guide decision-making. If the current system lacks the flexibility to support long-term innovation, redesigning may be the only viable choice. However, if technical constraints are manageable and the UX can be improved without significant disruption, iteration offers a lower-risk alternative.

Conclusion: Strategic UX Decision-Making

Ultimately, the decision to iterate or redesign depends on the severity of design debt and its impact on users. While iteration allows for gradual enhancements, a full redesign is sometimes the only way to break free from foundational issues. Businesses must take a data-driven approach, leveraging usability testing and user feedback to guide their choices. Regularly auditing design debt ensures that user experience remains a priority and prevents the need for drastic interventions. By making strategic UX decisions, organizations can sustain product growth while maintaining an intuitive, user-friendly interface.

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