<![CDATA[Cristian's Product Workshop]]>https://www.uxsidequest.comhttps://substackcdn.com/image/fetch/$s_!oEgk!,w_256,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6f7b5f0c-bcf7-462f-a1a7-22aa39915ec6_1280x1280.pngCristian's Product Workshophttps://www.uxsidequest.comSubstackThu, 02 Jul 2026 19:16:44 GMT<![CDATA[50 Essential UX and Product Design Resources to Level Up Your Skills]]>https://www.uxsidequest.com/p/50-essential-ux-and-product-designhttps://www.uxsidequest.com/p/50-essential-ux-and-product-designTue, 24 Dec 2024 12:02:52 GMTWelcome to Issue #020 of Cristian Talks Product Design—and happy holidays! As 2024 wraps up, I’m thrilled to share a curated list of resources that have shaped my growth this year. This isn’t just a collection of links—it’s an intentional repository reflecting my commitment to continuous improvement.

These tools, guides, and platforms have either transformed my work or sparked new ideas. Some are part of my weekly workflow, while others are stable references I keep handy for just the right moment. I see them as essential resources for designers heading into 2025, whether you’re revisiting fundamentals or exploring new frontiers.

You’ll notice some personal touches throughout:

  • ⭐ Highlights my favorites.

  • 🚀 Marks the ones I’m most excited about for 2025.

Here’s to growth and intentional progress. Let’s dive into the resources to level up in the new year!

Table of Contents

  • Foundational UX Knowledge

  • User Research & Discovery

  • Design Systems

  • UI Inspiration & Design Tools

  • Accessibility Tools

  • Typography & Visual Design

  • Interaction Design & Story Mapping

  • AI and UX Design Tools

  • UX Podcasts and YouTube Channels

Foundational UX Knowledge

Deepen your expertise and grow your knowledge with these comprehensive platforms. They include courses, articles, and practical guides for improving your skills.

User Research & Discovery

Learn how to gather insights about your users and uncover their needs. These tools and guides will help you plan, conduct, and analyze research to inform your design decisions.

Design Systems

Learn how to create and implement design systems to ensure consistency and scalability in your projects. These resources cover guidelines, tools, and frameworks for building effective design systems.

UI Inspiration & Design Tools

Find inspiration for your designs or discover new tools to speed up your creative process. These resources include curated design galleries and platforms for visual exploration.

Accessibility Tools

Ensure your designs are inclusive and accessible to all users. These tools help you evaluate and improve accessibility throughout the design process.

Typography & Visual Design

Perfect your typography, color schemes, and visual hierarchy while enhancing the overall aesthetics of your designs. These resources are perfect for elevating your design’s presentation.

Interaction Design & Story Mapping

Design more engaging and functional interactions for your users. These resources also include frameworks for organizing product backlogs and planning features visually.

AI and UX Design Tools

Explore tools and platforms that leverage AI to assist with prototyping, ideation, and user insights. This bucket includes resources at the intersection of UX and AI.

UX Podcasts and YouTube Channels

Learn from experts and stay inspired with podcasts and video content on UX and design. These channels offer valuable discussions and deep dives into UX, design, and creativity.

I hope this resource repository inspires you to keep learning, growing, and creating impactful designs. Whether you’re exploring new tools, revisiting foundational principles, or diving into emerging technologies, these resources are here to support you at every stage of your journey.

Growth doesn’t happen by accident—it’s the result of intentional effort and curiosity. My hope is that this list becomes a go-to reference for you, just as it has been for me. Thank you for being part of this journey with me. Wishing you a wonderful holiday season and an inspiring start to 2025. Let’s keep leveling up together! 🚀

Lastly if you have thought or comments or additional resources that you'd like to share please leave a comment below.

Cheers!

Cristian Pineda

]]><![CDATA[Design Insights & Updates: Podcasts, Books, and Templates for UX Designers]]>https://www.uxsidequest.com/p/design-insights-and-updates-podcastshttps://www.uxsidequest.com/p/design-insights-and-updates-podcastsTue, 29 Oct 2024 11:01:18 GMTWelcome to this week's Cristian Talks Product Design newsletter! Today officially marks my 12th newsletter post. That's right, what started as a curious hobby has grown into something truly rewarding. I know we're still at the beginning of this journey, but I feel incredibly grateful for how it has evolved so far, and that’s all thanks to you. Before diving in, I want to give a big shoutout to everyone who reached out about the brand redesign—even as an experiment, I’m thrilled it’s resonating with you!

What we'll cover today

Podcast guest incoming

I recently had the opportunity to chat with Aswin Ranganathan on my incoming podcast, he is the founder of Designing with Prompts, where he shares tutorials to help designers bring their ideas to life using AI. Aswin’s also educator behind Modern Designer, a resource hub for emerging design practices. Stay tuned—the podcast should be live later this week! (see preview below)

On a side note, I want to mention that this is something I want to continue doing with the channel—bringing on designers who are passionate about AI. I plan to dive into what shaped them into the designers they are today and explore the ways AI tools can enhance our rapidly evolving workflows.

Get access to our community library

CTPD Community Library 🔗

Two weeks ago, I shared my thoughts on Unreasonable Hospitality and how it resonated with me, which led to some great offline conversations with some of you on the books that have impacted your careers. This inspired me to create a community library—a curated collection of books that have profoundly influenced my product design and UX journey. Check it our here: The Cristian Talks Product Design Community Library

These titles delve into creativity, user experience, innovation, and personal growth, each selected for their unique insights into design challenges. The library is a growing resource meant to support and inspire your design journey, and I’d love to hear any must-read suggestions you have. Don't forget to book mark it to your reading list! 

Lean UX & Value Proposition Canvases: Tools for Designers

I recently received an exciting update from the Figma community—my FigJam templates are being downloaded and making an impact! I'm stoked to see that they're adding value, and I want to let you know that there are even more templates and Figma resources on the way.

That said, there are already plenty of great assets out there, and today I want to share two that provide incredible value and that every product design/UX designer should have in their toolkit. Let’s dive into the details:

1. Value Proposition Canvas

The Value Proposition Canvas by Strategyzer 🔗

The Value Proposition Canvas helps ensure a product-market fit by focusing on customer segments and how a company’s products meet their needs. It breaks down into two core sections:

  • Customer Profile: Understand your target customers by mapping out their jobs, pains, and gains.

  • Value Map: Clarify how your product creates value by identifying products/services, pain relievers, and gain creators.

When should you use it?

When you want to create a compelling value proposition that resonates with customers. This tool helps prioritize user needs and ensures alignment between what users need and what you offer.

Tips for Success:

  • Invest in user research: Your canvas is only as strong as your understanding of your customer.

  • Prioritize customer needs: Not all jobs, pains, or gains are equal—focus on the most impactful ones.

  • Think beyond function: Emotional and social reasons often drive customer decisions, not just functional benefits.

Resource:

2. Lean UX Canvas

Lean UX Canvas V2
The Lean UX Canvas by Jeff Gothelf 🔗

The Lean UX Canvas helps teams quickly capture and validate ideas, focusing on user experience and iterative development. It’s particularly effective in environments where speed and collaboration are key.

When should you use it?

Use the Lean UX Canvas when your team needs to align on a problem quickly, validate ideas efficiently, and ensure that you are solving the right problem for users. It is especially helpful in startup environments or projects that prioritize rapid iteration and learning.

Key components include:

  • Business Problem & Outcomes: Define what you’re trying to solve and how success will be measured.

  • User Outcomes: Identify how users will benefit from your solution and what value they’ll derive.

  • Hypotheses & Minimal Work: Frame ideas as hypotheses and determine the least amount of work needed to validate them.

Tips for Success:

  • Start with the problem, not the solution.

  • Identify assumptions and validate quickly.

  • Frame ideas as hypotheses rather than features.

Resource:

I hope these canvases offer practical ways to support your design thinking journey. Feel free to reach out if you’re using them or if you have questions—I’d love to hear your experiences.

Until next time, Cristian.





]]><![CDATA[How to Apply Voice and Tone to Your AI Chatbot]]>https://www.uxsidequest.com/p/how-to-apply-voice-and-tone-to-yourhttps://www.uxsidequest.com/p/how-to-apply-voice-and-tone-to-yourTue, 22 Oct 2024 10:50:32 GMTHi Friends,

Happy Tuesday! Before diving into today’s article, I want to quickly thank each and every one of you for supporting my writing. As of this post, we’ve grown to a community of 75 strong, and I couldn’t be more grateful! A huge thank you for all your support! I figured this would be a great time to mention that I’m planning something big for when we reach our 100-subscriber milestone—maybe a giveaway of sorts! 😉 So stay tuned.

Now, let’s dive into an important topic that often gets overlooked when building AI-powered chatbots, applying a voice and tone to your organization’s chatbot.

There’s a common assumption that because GPT, Gemini, and other AI models are so advanced, there’s no need to worry about defining voice and tone. But this is a big misconception. In reality, it’s something organizations should account for to avoid delivering a generic, impersonal user experience that doesn’t align with their brand. As AI product designers, we’re perfectly positioned to add value in this area.

After all, it’s crucial for us to ensure these AI tools align with our organization’s unique personality. We’re not just creating a tool—we’re crafting an extension of our brand or product. While models like GPT can generate human-like text, it’s up to us to guide how that text sounds. A chatbot with a well-defined voice and tone can enhance user engagement, ensure consistency across platforms, and strengthen your brand’s identity.

With that in mind, today’s post will share three techniques you can use as a designer to apply voice and tone to your AI chatbot, along with some resources to inspire you.

Three Approaches to Applying Voice and Tone to Your AI Chatbot

1. Define Your Chatbot’s Personality

Begin by determining the tone and character traits your chatbot should exhibit. Consider how your brand would communicate if it were a person—would it be professional, playful, empathetic, or witty? Document these attributes in a comprehensive style guide to ensure consistency across all interactions. This guide should detail personality traits, preferred vocabulary, and provide sample conversations for AI engineers to follow.

2. Collaborate with AI Engineers

Engage closely with AI engineers to align the chatbot's technical capabilities with your envisioned personality. Share detailed scenarios and dialogue samples that demonstrate how the chatbot should respond in various contexts, whether addressing customer inquiries or technical requests. This collaboration ensures the chatbot’s tone adapts appropriately to different user needs, keeping interactions consistent and on-brand.

3. Leverage Prompt Engineering and Fine-Tuning

Utilize prompt engineering techniques to guide the AI model’s responses, ensuring they reflect your brand’s voice. By fine-tuning the model with specific prompts, you can maintain a consistent tone and prevent deviations into unintended styles. For example, you might instruct the AI to “respond in a playful yet helpful tone” or “keep responses empathetic and understanding.”

Recommended Readings:

  1. How to Design a Chatbot Personality:

    This article offers insights into creating a chatbot persona that aligns with your brand, enhancing user engagement through consistent tone and style.

  2. Chatbot Persona: What It Is and How to Create One:
    Learn about the benefits of establishing a chatbot persona and the steps to develop one that resonates with your audience.

  3. Tone of Voice Dimensions:
    This resource explores the four dimensions of tone of voice, aiding in defining your brand's communication style.

  4. Tone and Voice: What’s the Difference?:

    This article clarifies the distinction between tone and voice, essential for understanding how to communicate effectively through your chatbot.

  5. Brand Voice and Tone Building with Prompt Engineering:
    Discover how prompt engineering can help develop and maintain your brand's voice across AI-driven communications.

By thoughtfully defining your chatbot's personality and collaborating with AI engineers, you can create a conversational agent that authentically represents your brand, fostering meaningful connections with users.

Resources to Draw Inspiration From

To help you refine your approach, here are five excellent content style guides that provide examples of voice and tone across various industries. These can serve as inspiration for developing your own brand’s chatbot voice:

  1. Duolingo’s Brand Voice Guidelines
    Duolingo is known for its quirky, friendly tone, which makes language learning feel fun and approachable.

  2. MetLife’s Tone of Voice Guide
    MetLife’s tone is clear, empathetic, and helpful—qualities that resonate well with users in financial services.

  3. NASA’s Content Guide
    NASA’s guide demonstrates how to balance technical accuracy with approachable language, making complex concepts easier to digest.

  4. Slack’s Brand Guidelines
    Slack’s tone is conversational and casual, creating a relaxed atmosphere even in a professional setting.

  5. Atlassian’s Voice and Tone Principles
    Atlassian focuses on being open, accessible, and helpful—a great resource if you’re designing a product with a collaborative nature.

Voice and tone matter more than ever in AI-powered products. By defining your chatbot’s personality, working closely with AI engineers, and leveraging tools like prompt engineering, you can ensure your chatbot reflects your brand’s voice consistently. It’s not just about how your chatbot answers a question—it’s about how users feel when interacting with it.

I encourage you to experiment with these techniques. Reflect on your brand’s voice, and don’t hesitate to collaborate with your team to bring it to life in your chatbot. And as always, I’d love to hear how you’re applying these ideas in your projects—feel free to share your thoughts!

Until next time, stay creative and keep designing.

Best,
Cristian

]]><![CDATA[Do KPIs Limit Innovation for Product Designers?]]>https://www.uxsidequest.com/p/do-kpis-limit-innovation-for-producthttps://www.uxsidequest.com/p/do-kpis-limit-innovation-for-productTue, 15 Oct 2024 10:50:11 GMTHi friends!

Over the past week, I’ve been reflecting on how we, as product designers, balance creativity with the need to demonstrate the value and impact of UX within organizations. This got me thinking—does the way you approach metrics like KPIs and OKRs say something about your maturity as a designer? After considering it, I believe it does. And here’s why:

As a junior designer, you’re often tasked with completing immediate assignments, typically with much of the context already defined by others. Naturally, this focuses your perspective on the 'what' of your work. For example: What are you designing? What’s the deliverable? From this point of view, it might not seem necessary to think about KPIs or OKRs—or so you’d think, right? But I believe it’s important to consider these metrics, even as a junior designer, especially if you want to grow in your career. Here’s why:

As you grow into more senior or principal roles, your perspective shifts. Instead of just asking what, you start asking why and how. Why are you building this? How will it impact the end-to-end experience? And because of this shift, your relationship with KPIs evolves. You begin to see them as more than just measurements—they become strategic tools. They help you move beyond the 'what' and dive deeper into the 'why,' allowing you to connect your design decisions to long-term outcomes and organizational success.

This brings us to the question: Do KPIs limit innovation for product designers?

No, I don’t think so. In fact, I believe that understanding and integrating KPIs into your work can actually help you grow as a designer. When you know how to measure your impact, you don’t stifle creativity—you enhance it. You gain the ability to solve more complex problems, justify your design decisions, and communicate the value of UX in a way that resonates with stakeholders across the organization. Senior designers, for example, don’t just track metrics; they use them to guide long-term vision and ensure their designs have a lasting impact.

With all of this in mind, today I’d like to share 10 KPIs that every product designer should care about. I’ve broken them down into three key categories—User Experience and Usability, Conversion and Engagement, and User Feedback and Satisfaction—to help you focus on how each group impacts different aspects of your work. Let’s break each one down, explore why they matter, and how you can measure them effectively.

User Experience and Usability

User experience (UX) and usability metrics help you understand how effectively users can interact with your design. These KPIs focus on efficiency, ease of use, and error reduction, all of which are crucial for creating a seamless product experience. Let’s explore a few key KPIs in this category.

Task Success Rate (TSR)

  • What it is: Task Success Rate measures how effectively users can complete tasks while interacting with your product.

  • Why it’s important: TSR is a critical indicator of how intuitive and user-friendly your design is, directly reflecting how well your design helps users achieve their goals.

  • How to measure:

    1. Track the number of users who attempt a task.

    2. Categorize their success into tiers: complete success, success with minor issues, success with major issues, or failure.

    3. Calculate the percentage of users in each category to get a clear picture of usability.

For more detailed guidance, I recently wrote this article and created a free to access spreadsheet that you can use to guide your next usability test. check it out here!

Cristian’s Task Completion Rate Spreadsheet (link)

Time on Task

  • What it is: Time on Task measures how long users take to complete specific tasks within your product.

  • Why it’s important: It helps pinpoint where users may face delays or friction, giving insights into how efficient and smooth your design is.

  • How to measure:

    1. Define the task: Clearly outline the task you want users to complete.

    2. Set start and end points: Identify what actions mark the beginning and end of the task.

    3. Use tracking tools: Screen recorders or analytics software like UXtweak can capture task completion times.

    4. Analyze the data: Look for patterns, and consider excluding outliers such as pauses or interruptions.

    5. Refine based on findings: Use these insights to adjust the task flow or design to optimize completion times.

For more detailed guidance, check out this article “Task completion time” by UXtweak.

UXtweak task completion time article (link)

User Error Rate

  • What it is: The User Error Rate tracks how often users make mistakes while completing tasks.

  • Why it’s important: A high error rate signals usability issues, making it easy to spot areas that need improvement.

  • How to measure:

    1. Break down errors into categories, such as:

      • Slips: Unintentional actions (e.g., typos).

      • Mistakes: Wrong goals (e.g., entering incorrect data).

      • UI Problems: Errors caused by poor design.

      • Scenario Errors: Mistakes due to artificial test conditions.

    2. Count the total number of errors users make during the task.

    3. Divide that by the total number of task attempts.

    4. Multiply by 100 to get the error rate percentage.

For more detailed guidance, check out this article “Measuring Errors in the User Experience” by Jeff Sauro’s

Measuring Errors in the User Experience by Jeff Sauro, PhD 🔗

Navigation vs. Search

  • What it is: This KPI compares user preferences for using navigation menus versus search functionality to find content or complete tasks.

  • Why it’s important: It shows how users prefer to interact with your product, helping you identify whether navigation or search needs improvement.

  • How to measure:

    1. Use usability testing tools like UsabilityHub, Hotjar, or Mouseflow to track user clicks and interactions.

    2. Measure task completion rates for both navigation and search.

    3. Divide successful completions by the total number of tasks to identify trends.

    4. Analyze whether users rely more on search or navigation, offering insights into areas that may need improvement.

For more detailed guidance, check out this article “The 7 Most Important UX KPIs (and How to Measure Them)” by Emily Stevens.

The 7 Most Important UX KPIs (and How to Measure Them) by Emily Stevens 🔗

User Feedback and Satisfaction

User feedback and satisfaction metrics provide direct insights into how users feel about your design. These KPIs are crucial for improving the overall user experience and building customer loyalty.

System Usability Scale (SUS)

What it is: SUS is a standardized questionnaire of 10 items rated on a 5-point scale, designed to assess the overall usability of your product.

Why it’s important: SUS provides a reliable benchmark for understanding how users perceive ease of use. It’s widely used across industries, making it great for comparison and tracking improvements over time.

How to measure:

  • Distribute a SUS survey with 10 statements rated from "Strongly Disagree" to "Strongly Agree."

  • Convert scores: subtract 1 from odd-numbered items and subtract even-numbered responses from 5.

  • Add up the scores and multiply by 2.5 for a final score out of 100.

  • A score above 68 indicates above-average usability, while anything over 85 shows excellent usability.

For more detailed guidance, check out this article “System Usability Scale for Data-Driven UX” by Mads Soegaard.

System Usability Scale for Data-Driven UX by Mads Soegaard

Customer Satisfaction Score (CSAT)

What it is: A survey-based metric that measures user satisfaction with your product.

Why it’s important: It provides direct feedback on the user experience and highlights areas that may need improvement.

How to measure: Ask users to rate their satisfaction on a scale (typically 1 to 5 or 1 to 7). Calculate the percentage of users who provide positive ratings (4 or 5) out of the total responses to determine your CSAT.

For more detailed guidance, check out this article “What is CSAT and how do you measure it?” by Qualtrics.

What is CSAT and how do you measure it? by Qualtrics

Net Promoter Score (NPS)

What it is: NPS is a metric that measures user loyalty by asking how likely they are to recommend your product to others.

Why it’s important: A high NPS reflects strong user satisfaction and loyalty, which can drive organic growth through word-of-mouth.

How to measure: Ask users to rate their likelihood of recommending your product on a scale from 0 to 10. Subtract the percentage of Detractors (those who rate 0-6) from the percentage of Promoters (those who rate 9-10) to calculate your NPS score.

For more detailed guidance, check out this article “The One Number You Need to Grow” by Frederick F. Reichheld, published on HBR.

The One Number You Need to Grow by Frederick F. Reichheld on HBR

Conversion and Engagement

This category focuses on how effectively your design drives user engagement and conversion actions, like purchases or sign-ups. These KPIs provide insights into how well your design supports business goals and user retention.

Conversion Rate

What it is: Conversion Rate measures the percentage of users who complete a desired action, such as making a purchase or signing up for a service.

Why it’s important: It’s a key indicator of how well your design turns visitors into active users or customers, helping you gauge the effectiveness of your product’s engagement and sales funnel.

How to measure: First, identify the specific conversion events you want to track (e.g., signing up, completing a purchase). Then, divide the number of users who complete the desired action by the total number of visitors, and multiply by 100 to get the conversion rate. You can also use A/B testing to compare conversion rates across different designs and see which version performs best.

For more detailed guidance, check out this article “What are Conversion Rates?” by the Interaction Design Foundation.

What are Conversion Rates? by the Interaction Design Foundation.

Bounce Rate

What it is: Bounce Rate measures the percentage of visitors who leave after viewing only one page.

Why it’s important: A high bounce rate can signal that users aren’t finding the content or experience engaging, which may need further investigation.

How to measure: Use analytics tools to track the percentage of visitors who leave after a single interaction. Compare bounce rates across different pages or user segments to identify problem areas and opportunities for improvement.

For more detailed guidance, check out this article “Bounce rate: what it is and how to improve it” by Hotjar.

Bounce rate: what it is and how to improve it by the Hotjar team

Page Views

What it is: Page Views measure the total number of times a page is viewed or reloaded by users.

Why it’s important: High page views, combined with other engagement metrics, can indicate strong interest in your content or design.

How to measure: Use analytics tools to track views. Pair this data with metrics like scroll depth, time on page, and user interactions to understand overall engagement.

For more detailed guidance, check out this article “ What are Page Views?” by Agency Analytics.

Page Views Documentation by Agency Analytics 🔗

Wrapping It All Up

As we’ve explored, KPIs are not just metrics to track—they’re strategic tools that can help you grow as a designer and elevate the impact of your work. By integrating KPIs into your process, you don’t limit creativity, you empower it. Understanding the relationship between design and measurable outcomes allows you to justify your decisions, solve more complex problems, and align your designs with long-term business goals.

Now, you might be wondering if these KPIs are UX-specific—and the truth is, they’re not. Part of your growth as a designer involves realizing that marketing teams, product managers, and other stakeholders might also be using these same metrics to guide their decisions. This highlights an important point: none of these KPIs or metrics should be viewed in isolation. Instead, think of them as adjustable levers—like the knobs on a telescope—that help you sharpen your focus and get a clearer picture of the overall product landscape. The key is learning how to balance and interpret these metrics together to make informed, strategic decisions.

Whether you’re focusing on usability, engagement, or user satisfaction, each of the KPIs we’ve discussed offers a window into how your design is performing and where it can improve. As you continue to refine your approach, remember that embracing these metrics—especially as you transition into more senior roles—can be a game-changer in driving success for both your team and your users.

What do you think about the role of KPIs in product design? Do they help or hinder creativity in your experience? I’d love to hear your thoughts or any experiences you've had—feel free to share in the comments!

]]><![CDATA[Should Product Designers Read Unreasonable Hospitality?]]>https://www.uxsidequest.com/p/should-product-designers-read-unreasonablehttps://www.uxsidequest.com/p/should-product-designers-read-unreasonableTue, 08 Oct 2024 10:50:09 GMTHi Friends,

Today, I’d like to share five valuable insights I gained from reading "Unreasonable Hospitality" by Will Guidara. A friend recommended this book while we were chatting about our backgrounds in the hospitality industry, and yes if your wondering many years ago I had the opportunity to work at various restaurants and cafe’s, where surprisingly enough I learned a-lot about what it takes to deliver a pleasant and even memorable experience.

It's funny because this 'fun fact' about me often surprises those I meet, though I'm not really sure why. After all, there are many similarities between the general objectives of these industries. With this in mind I decided give Unreasonable hospitality a try to see if there were any bits of gold that incorporate into my professional growth.

Now if your still wondering whether you should read the book, the answer is yes, although "Unreasonable Hospitality" may not be explicitly aimed at product designers, its principles deeply resonate and offer valuable guidance for those of us creating digital experiences. Much of Guidara’s insight apply not only to the design process but also to team collaboration and leadership skills that I think are valuable. With that in mind, here are some carefully curated takeaways from the book that I think will add value to product designers tool set of skills.

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Being Intentional

Being intentional in design is all about embedding thoughtfulness and clarity into every aspect of your work. As Will Guidara puts it, "To do something with intentionality means to do it thoughtfully with a clear purpose in mind."

As designers, it’s crucial that we avoid superficial decisions, like relying solely on spontaneous inspiration. While these moments have their place, true intention must underpin every design choice, no matter its size. The sum of these intentional micro-interactions ultimately sculpts the entire user experience, going beyond the core product itself. By being deliberate in every choice, you contribute to crafting more meaningful and impactful experiences.

Fostering Collaboration

Designing collaboratively means cultivating an environment where open communication and mutual respect thrive. Will Guidara highlights the importance of acknowledging and appreciating each team member’s unique talents. Collaboration goes beyond merely working in proximity; it involves integrating diverse viewpoints to fuel innovation.

The way you respond to new ideas can set the tone for future contributions, as Guidara notes, "The first time someone comes to you with an idea, listen closely, because how you handle it will dictate how they choose to contribute in the future." Every interaction sets the stage for future collaborations, emphasizing the need for thoughtfulness and openness. By listening actively and providing a supportive atmosphere, you empower your team and unlock their potential, which leads to more innovative and successful outcomes.

Striving for Excellence

Amid today's competitive landscape, it's tempting to rush to launch and promise enhancements later—we've all been there. However, while iterative improvements are important, designers should advocate for creating exceptional experiences right from the beginning. Guidara wisely says, "It may not be possible to do everything perfectly, but it is possible to do many things perfectly."

I appreciated this because it points to the idea that there needs to be a middle ground rather than chasing perfectionism endlessly, focus on deliberate actions to guarantee high-quality outcomes. In other words delivering excellence doesn't equate to flawlessness in every detail; it's about intentionally honing in on core user interactions that define the product's value. By maintaining high standards and striving for excellence, you craft memorable and impactful user experiences.

Embracing a Creative Process

The creative process might seem like an unrestricted flow where ideas come and go, and to some extent, it is. However, Guidara's perspective adds depth: creativity demands initiative and active engagement. This struck a chord with me, affirming that, as designers, we mustn't wait for inspiration but should actively chase new ideas and perspectives. "Creativity is an active process, not a passive one," says Guidara, underscoring the need for action and continuous discipline. By creating safe environments that foster creativity through structured meetings, teamwork, and intentional open thinking, we nurture a curious mindset that propels innovative solutions. Viewing creativity as an ongoing journey equips us to deliver fresh, dynamic experiences.

Don't Ruin a Story with Facts

While crafting feasible designs that engineers can build is essential, over-focusing on technical constraints early on can stifle creativity. I've been in that situation, yet Guidara's advice is enlightening: "Start with what you want to achieve, instead of limiting yourself to what's realistic or sustainable." Allowing creativity to lead the process from the outset can unveil innovative opportunities and redefine perceived boundaries. By prioritizing exploration of what's possible, designers can transcend limitations and create groundbreaking designs. Embracing this approach fosters creativity and lets us craft meaningful experiences that inspire and elevate our work.

The Power of Hospitality Principles in Product Design

At its core, designing exceptional user experiences requires more than just technical expertise—it demands empathy, creativity, and a relentless pursuit of excellence. Just as hospitality revolves around making people feel valued and understood, these same principles can guide us in creating thoughtful, user-centered digital experiences. By being intentional, fostering collaboration, and embracing creativity, we can craft products that not only solve problems but resonate deeply with the people who use them.

What do you think about applying hospitality principles to design? I’d love to hear your thoughts or any experiences you've had—feel free to share in the comments!

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

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]]><![CDATA[Designing for AI Errors: Turning Mistakes into User-Friendly Solutions]]>https://www.uxsidequest.com/p/designing-for-ai-errors-turning-mistakeshttps://www.uxsidequest.com/p/designing-for-ai-errors-turning-mistakesTue, 01 Oct 2024 11:05:58 GMTHi friends!

Is anyone else still thinking about last week’s Meta announcements?! The progress on Meta AI and those Orion glasses—cool, right? You’ve got to love the innovation.

One moment that really stood out to me was when Zuck introduced Meta AI’s new conversational features. He asked the AI assistant how risky it is to do live demos, and the system responded:

“Live demos can be risky, yes. They can be unpredictable, prone to technical issues, and potentially embarrassing. However, they can also be engaging, memorable, and effective in showcasing products or skills. Preparation is key to managing those risks.”

This got me thinking about UX. A key responsibility of UX designers is to anticipate the edge cases that users might encounter. But with AI being such a unique type of product, how do we handle these edge cases, especially when mistakes are inevitable? Whether with machine learning or traditional systems, errors are part of the learning process. But how we design for those errors is what sets user-friendly systems apart.

With this in mind, I created a FREE Figjam workshop for you and your team. It’s designed to guide you through identifying AI errors, understanding their root causes, and brainstorming actionable solutions. You’ll move from strategy to wireframing, and by the end, you’ll have concrete insights you can turn into product improvements. Dropping the link below—check it out Let me know what you think!

FigJam Workshop Template Cover

➡️ Designing for AI System Errors: A Whiteboarding Workshop Template

If Figjam isn’t your thing, don’t worry! I’ll be covering much of the same content in today’s post, though at a higher level. So, let’s dive into these techniques and learn how to turn errors into moments that strengthen your AI product’s user experience.

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Defining Errors & Failure

Before you can design for errors, it’s important to clarify what counts as an "error" or "failure" in your system. Consider that In probabilistic AI systems, users might see failure in places where the AI is actually functioning as intended and this misalignment can create a significant opportunity for user pain points.

What you can do: Set up a time with as many cross functional stakeholders as you can and dedicate this time to collecting canonical error examples. This will set the stage for you to and your team to have a share understanding of potential errors to work toward solutions.

A picture of a whiteboard workspace where stakeholders can be documented

Identifying the Source of Errors

AI systems are complex, and identifying the root cause of an error can be challenging. As a designer, it’s essential to collaborate with your team to establish a process for recognizing and understanding errors. This approach helps you address issues more effectively and improve error-handling experiences.

What you can do: Define error types like system limitations, context misalignment, or input errors using canonical examples. Once sources are identified, collaborate on a plan to resolve them, focusing on feedback loops and improving user control.

Consider these questions to pinpoint root causes:

  • Did the system misinterpret the user’s input or fail to auto-correct?

  • Was the user’s habitual action interrupted, causing confusion?

  • Is the model working with incomplete or unstable data?

  • Is there confusion over which system is in control, especially during integrations?

  • Did multiple errors cascade, rendering features unusable?

By addressing these, your team can systematically diagnose errors, create targeted solutions, and improve user control and feedback loops.

A screenshot image of a figjam workspace with multiple activities that guide its users in identifying errors and finding out the errors root cause

Designing a Path Forward

No matter how well-planned, AI systems will experience failure. The goal isn’t to avoid errors but to detect them early and design thoughtful recovery options that improve the system over time.

What you can do: Set up feedback loops that capture and route errors back to your team for refinement. Use multiple sources to track and analyze issues:

  • In-product feedback tools to capture real-time issues.

  • Customer service reports that describe problems in detail.

  • Social media comments highlighting frustrations.

  • In-product surveys that prompt users for input after errors.

  • User research like interviews and diary studies to uncover patterns.

Decide which feedback channels suit your team’s resources. Not every channel is feasible, but the right ones will provide valuable insights. Ensure the user experience feels supportive, and that feedback continuously improves the system.

A screenshot of a whiteboarding workspace that guides its users toward finding a solution to the identified problem

Humanizing the Error Experience

Errors aren’t just technical issues—they’re opportunities to humanize your product. Error messages should reflect humanity, not just machine logic. Be transparent about the system’s limitations and encourage users to continue their journey. Explain how the AI learns from mistakes and how users can help improve it.

When users encounter errors, offer recovery options like retrying, adjusting input, or seeking assistance. Every error message should guide users forward, not leave them stuck.

What you can do:

  • Return control to the user: Give users intuitive options to regain control and move forward.

  • Assume subversive behavior: Design failures that are safe and avoid revealing system vulnerabilities.

  • Ensure suggestions are relevant: Make sure error suggestions help users progress, not just respond to the issue.

  • Always provide a path forward: Guide users to recovery options without dead ends.

  • Be transparent: Explain what went wrong and how the system is improving.

  • Take accountability: Use sincere messaging that acknowledges faults and maintains user trust.

By considering these elements, you can turn error states into moments of connection and trust-building.

The Heart of Learning is built from failure

Learning can't happen without making mistakes, and this is a critical concept for designers working with AI systems. When users encounter errors, it’s an opportunity for dialogue, not frustration. By designing your system with errors in mind, you allow users to see that the AI is a work-in-progress, and this transparency helps keep them engaged.

Designing user-centered error experiences for AI products goes beyond just fixing technical issues. It’s about showing users that you’re listening, that the system is learning, and that their feedback matters. By being transparent, human, and thoughtful in how you manage errors, you can turn mistakes into moments that build trust and improve your product.

What do you think about designing for errors in AI systems? Let me know your thoughts or questions in the comments—I’d love to hear your perspective.

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

Start Reader Feedback Survey

]]><![CDATA[Three AI-Powered Techniques for Building Design Systems]]>https://www.uxsidequest.com/p/three-ai-powered-techniques-for-buildinghttps://www.uxsidequest.com/p/three-ai-powered-techniques-for-buildingTue, 24 Sep 2024 11:02:49 GMTGood morning designers! This past week, I came across some fascinating discussions about how AI could revolutionize the way we build and contribute to design systems. While many of the ideas were thought-provoking, I found myself frustrated by how disconnected some of these use cases were from real-world design environments. Often, it felt overly focused on the potential applications of AI assistants rather than how we can apply AI right here, right now.

With this in mind, I decided to speak to some of you and also looked inward to reflect on how I’m using AI to enhance the way I contribute and build design systems and today I’m excited to share with you some applicable techniques you can incorporate into your design process right now!

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

3 Practical ways to use AI to build Design Systems

Before diving in, I’d like to mention that I’ve created these techniques for designers of all levels; whether you’re just starting out, an experienced pro, building from scratch or refining an existing system. I’ve crafted these examples to not only show how AI can expand your knowledge, speed up your workflow, and improve the quality of your work but also to spark your imagination on other ways you could leverage these tools; so with that lets dive into it!

Creating An Atomic Elements Checklist

If you're not already familiar with atomic design systems, they’re a method for creating scalable and flexible design systems, originally developed by Brad Frost. This approach breaks down UI components into five distinct levels: atoms, molecules, organisms, templates, and pages. It's a widely adopted technique that can grow with your project's needs. If you're interested in learning more, I'll share a link to Frost's work for further exploration.

Now, imagine you're tasked with building the foundational design system for a cool new startup's iOS application. Whether you're just getting familiar with atomic design or simply looking for a way to structure your work, leveraging an AI assistant can a gamechanger. By providing the AI with project context, you can create a file structure or checklist of atomic elements to start building your design system. This not only streamlines your process but also ensures that no essential components are overlooked. It's a great way to organize your thoughts and tackle your workflow with clarity and efficiency.

Prompt suggestion:

“Hi Chat, I need help creating an atomic design system as the foundation for an app. Could you provide an outline that focuses on atoms and molecules? This should include a checklist of key items to consider when building these elements. Additionally, I’d like suggestions on how to organize the pages of the design system file in Figma for ease of use, scalability, and team collaboration.”

Next Steps

Now that you have an outline of how to create a checklist for your atomic design system, start by customizing the checklist based on your project’s unique needs. Begin with atoms and molecules, and gradually build up to more complex components. Organize your Figma file according to the suggestions provided, ensuring scalability and ease of collaboration for your team. As you work through the checklist, remember that this is just the foundation—adapt and refine it based on feedback and project requirements to create a design system that truly supports your product’s growth.

Takeaway:

This approach allows you to jumpstart your process with a clear and organized checklist that sets the foundation for a well-structured, scalable design system. However, these answers should not be seen as final. Depending on where you are in the process, things are bound to be different. It’s imperative as a designer to keep ownership of defining what makes sense for your specific project.

Accessibility and Usage Documentation

When building or contributing to a design system, accessibility and usage documentation can be a time-consuming but critical aspect of the process. It’s not just about designing and integrating patterns that flow well together; it’s also about ensuring that your team uses these patterns correctly.

This is where documentation becomes essential. Often, this effort can take significant time, and in larger organizations, entire teams may be dedicated to creating it. However, for smaller teams, this is where leveraging AI tools like Perplexity can be a game changer, as they allow you to quickly gather cited details about the accessibility requirements for specific components, potentially saving hundreds of collective hours.

Let’s consider an example. Say you’re tasked with integrating radio buttons into your design system. You’ve already done the work of creating different states (default, hover, focused, disabled, etc.), but now you need to create documentation that will guide other designers in your organization. This documentation should highlight best practices and key accessibility considerations to ensure that the component is integrated correctly. Here’s what this might look like using the share prompt suggestion below:

Prompt Suggestion

“Create concise accessibility documentation for a Radio Component following this structure:

  • Purpose of the component: Describe when and why the component should be used.

  • When Not to Use: Provide guidance on inappropriate use cases for the component.

  • Visual and Interaction Considerations: Outline important visual and interaction requirements for accessibility (e.g., size, spacing, color contrast, labels).

  • ARIA Roles and Attributes: List any relevant ARIA roles, states, and attributes that should be applied to the component for screen readers and assistive technologies.

  • Testing Considerations: Provide recommendations for testing the component's accessibility, including screen reader behavior, keyboard navigation, and cross-device support.

Please tailor the documentation to mobile web and desktop.”

Next Steps

Now that you have a solid framework for creating accessibility documentation, the next step is to customize the output for your specific project. Start by reviewing the AI-generated content and tailoring it to ensure that it aligns with your team’s design standards and workflows. Make sure the accessibility guidelines are consistent with how your team operates, and confirm that all details are accurate and actionable.

Takeaway

While AI tools can provide a quick and structured draft, it’s important to remember that accessibility documentation should be tailored to the specific needs of your project. I encourage you to not only modify the prompt but also play around with it to see how AI can best support your workflow and make the documentation process even more efficient.

Component Variants and Design Tokens Automation

Design tokens are the building blocks that keep your design system consistent, enabling us to manage attributes like colors, typography, spacing, and motion across components and platforms. However, setting up tokens can be tedious and time-consuming. With the help of AI, this process becomes much quicker, allowing us to shift focus away from repetitive tasks like naming conventions and toward more creative work.

Imagine you're tasked with developing standardized tokens for an iOS app’s design system. These tokens will need to support a variety of components and might even require robustness for both dark and light modes. Below, I’ll share how we might approach this conversation with my AI assistant to get things moving.

Prompt Suggestion

"Hi chat, I need help generating design tokens for our iOS app's design system. Could you create a list of color tokens (for both light and dark mode), typography tokens, and spacing tokens?

Some more details: we have three core colors, our company font is Brisbane, and we use geometric progression starting with 4px for our spacing values. Also, please use hyphens for naming conventions.

I’d also like recommendations on how to organize these tokens in a Figma file for better scalability and team collaboration.”

Next Steps

Once the tokens are generated, implement them in Figma’s token management feature for easy scalability and collaboration. Schedule time with the engineering team to ensure the tokens align with the development workflow and can be integrated into the code stack. Finally, iterate and refine the tokens based on brand guidelines and feedback to enhance their scalability as your design system evolves.

Takeaway

By using AI to automate the generation of design tokens, you can quickly set up a scalable foundation for your design system. However, it’s crucial to refine the AI-generated tokens to ensure they align with the brand’s identity and meet project-specific needs. AI can help create structure and consistency, but designers should always review and adjust for a perfect fit.

Empowering Your Design Workflow with AI

I hope these examples sparked some ideas. Incorporating AI into your design system workflow is not just about automating tedious tasks—it’s about unlocking new levels of efficiency, creativity, and scalability. Whether you're laying the foundation with atomic elements, streamlining accessibility documentation, or automating the creation of design tokens, these AI-driven techniques empower you to focus on what matters most: designing thoughtful, high-quality user experiences.

As we continue to evolve our design practices, leveraging AI can help us navigate complex challenges with greater ease and precision. Remember, these tools are meant to enhance your process, but the real value comes from how you apply them to meet the unique needs of your projects.

So, as you integrate AI into your workflow, stay flexible, keep refining, and don’t be afraid to experiment. The future of design is collaborative—and AI is just another tool in our kit to help us create more impactful, human-centered products.

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

Start Reader Feedback Survey

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

]]><![CDATA[Five UX Principles for Designing AI Models.]]>https://www.uxsidequest.com/p/five-ux-principles-for-designinghttps://www.uxsidequest.com/p/five-ux-principles-for-designingTue, 17 Sep 2024 11:01:24 GMTGood morning designers! This past week brought some exciting tech updates, from Apple's latest product announcements to OpenAI’s big GPT-01 reveal. Amid all the buzz, I came across one of Jakob Nielsen’s latest post on Gestalt Principles for Visual UI Design, which got me thinking… With AI being at the forefront of today’s product landscape, what key UX principles should we be considering to craft truly user-centric AI experiences?

That question led me down a research rabbit hole, and today I’m excited to share what I believe are five essential UX principles that every UX designer should have in their toolbelt when designing AI powered experiences. So let’s dive in to it and explore how these principles can help you create products and services that are intuitive, user-friendly, and—most importantly—enjoyable to use.

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Our Five UX Principles for Better AI Design

Keep It Simple (Occam’s Razor Law)

What It Is:

Occam’s Razor tells us that when multiple solutions achieve the same outcome, the one with the least assumptions is usually the best choice. In AI design, simplicity enhances user understanding and trust, as AI technology can often feel complex and abstract.

How to Apply It:

Consider how simplicity affects not just the user interface but also the AI's outputs. Design both elements to be straightforward and aligned with user expectations to ensure the system feels cohesive and easy to use.

Examples:

  • Smart defaults: Provide default settings that suit most users, reducing the need for complex configuration.

  • Clear language: Use plain language and avoid technical jargon. Offer concise instructions to guide users through tasks.

  • Essential information only: Request only the necessary information, minimizing cognitive load by keeping forms and inputs simple.

  • Simplified AI responses: Program AI to deliver clear and concise answers without unnecessary complexity.

Why It Matters:

By keeping things simple, we reduce cognitive load and make it easier for users to engage confidently with our AI products. Simplicity not only enhances usability but also builds trust, as users are more likely to rely on systems that are transparent and easy to understand. In a field where technology can seem overwhelming, a straightforward design can make the difference between user adoption and abandonment.

Learn More:

Leverage Familiarity (Jakob’s Law)

What It Is:

Jakob’s Law states that users spend most of their time on other websites and applications, so they expect your product to function similarly to those they already know. By leveraging familiar patterns and conventions, we reduce the learning curve, allowing users to focus on their goals rather than figuring out how to navigate a new system.

How to Apply It:

Incorporate design elements and interaction patterns that users are already comfortable with. When introducing new features, align them with familiar experiences to make them more intuitive. If you need to implement unique functionalities, provide clear guidance to help users understand how to interact with them.

Examples:

  • Consistent Icons and Symbols: Use universally recognized icons like the magnifying glass for search, a gear for settings, or a house icon for the homepage. This immediate recognition helps users navigate your AI product effortlessly.

  • Familiar Interface Layouts: If your AI uses a chat-like interface, design it to resemble popular messaging apps. Position the user's input on one side and the AI's responses on the other to create an intuitive experience.

  • Standard Interaction Patterns: Implement common gestures and actions, such as swiping or tapping, that users have learned from other apps. This familiarity makes your AI product feel more approachable.

  • Recognizable Feedback Mechanisms: Utilize standard cues like loading spinners, checkmarks, or notification sounds to confirm actions. These signals provide instant feedback, building user confidence in the system's responses.

Why It Matters:

By leveraging familiarity, we minimize the cognitive load on users, making it easier for them to adopt and engage with your AI product. This approach not only enhances usability but also increases user satisfaction and trust, as they can rely on their existing knowledge to navigate new experiences.

Learn More:

Simplify Choices (Hick’s Law)

What It Is:

Hick’s Law states that the time it takes for a person to make a decision increases with the number and complexity of choices presented. Essentially, the more options you offer, the longer it takes users to decide, which can lead to frustration or decision paralysis.

How to Apply It:

Simplify your AI product's interface by limiting the number of choices presented at any given time. Focus on presenting the most relevant options first, and provide additional choices progressively as needed. This approach helps users make quicker decisions without feeling overwhelmed.

Examples:

  • Data Analysis Tools: Instead of displaying all available data visualizations at once, start with a few key options. Allow users to delve deeper or access more advanced features as they become comfortable. This helps prevent overwhelm and keeps the focus on the most important information.

  • Recommendation Systems: Limit AI-generated recommendations to a curated list of top suggestions—typically 3 to 5 items. Presenting too many options can lead to choice overload, so a smaller selection makes it easier for users to decide quickly and confidently.

  • Simplified Navigation: Use clear and concise menus with a limited number of options. Group related actions together and employ dropdowns or expandable sections to keep the interface clean and intuitive.

Why It Matters:

By simplifying choices, we enhance the user experience by reducing cognitive load and making it easier for users to interact with our AI products. This not only speeds up decision-making but also increases user satisfaction and engagement.

Learn more:

Focus on the Essentials (Pareto Principle)

What It Is:

The Pareto Principle, also known as the 80/20 rule, states that roughly 80% of effects come from 20% of causes. In design, this means that a small set of features often delivers the majority of user satisfaction and value. By identifying and concentrating on these critical elements, we can optimize our AI products to meet the most significant user needs effectively.

How to Apply It:

Prioritize the features and functions that provide the most value to your users. Instead of trying to address every possible need or use case, focus your efforts on the key aspects that will make the biggest impact. This approach ensures that you allocate resources efficiently and enhance the overall user experience.

Examples:

  • Target Core Features: Identify the 20% of functionalities that 80% of your users engage with most frequently. For an AI-driven productivity app, this might mean focusing on seamless task automation and intuitive scheduling features rather than less-used advanced options.

  • Prioritize Critical Fixes: Concentrate on resolving the 20% of issues that cause 80% of user frustration or errors. For example, if users often encounter inaccuracies in an AI-powered translation tool for specific languages, prioritize improving the algorithm for those languages.

  • Optimize for Key User Segments: Focus on the user groups that represent the most significant portion of your audience or revenue. Tailor your AI system to meet their specific needs, enhancing satisfaction and fostering loyalty.

Why It Matters:

By focusing on the essentials, you ensure that your AI product delivers maximum value where it counts most. This not only boosts user satisfaction but also makes the best use of your development resources. Concentrating on high-impact areas leads to a more effective and user-centric design, ultimately contributing to the success of your product.

Learn More:

Maintain Flow (Doherty Threshold)

What It Is:

The Doherty Threshold is a design principle that states that productivity soars when a computer and its users interact at a pace (response time) below 400 milliseconds. When system responses occur within this timeframe, users remain focused and engaged, experiencing a seamless flow of interaction. Delays longer than this threshold can disrupt the user's thought process, leading to frustration and decreased efficiency.

How to Apply It:

Ensure that your AI product responds to user actions promptly, keeping response times under 400 milliseconds whenever possible. If certain AI processes require more time due to complex computations, provide immediate feedback to inform users that the system is processing their request. This helps maintain the perception of responsiveness and keeps users engaged.

Examples:

  • Loading Indicators: Implement progress bars, spinners, or subtle animations during longer AI processing times. These visual cues reassure users that their input has been received and the system is working on it, preventing frustration due to perceived unresponsiveness.

  • Optimized Performance: Streamline your AI algorithms and backend processes to reduce latency. Utilize efficient coding practices, caching, and content delivery networks to speed up response times.

  • Asynchronous Processing: For tasks that inherently take longer, consider processing them in the background. Allow users to continue interacting with other parts of the application and notify them once the task is complete.

  • Predictive Loading: Anticipate user actions based on common usage patterns and preload or cache content accordingly. For example, if an AI assistant frequently accesses calendar data after checking emails, preload the calendar information to reduce wait times.

Why It Matters:

Maintaining quick and consistent system responses is crucial for keeping users engaged with your AI product. By respecting the Doherty Threshold, you enhance the user experience, making interactions feel smooth and efficient. This not only boosts user satisfaction but also encourages continued use of your product, as users associate it with productivity and reliability.

Learn More:

Embracing Our Role as Designers in the AI Era

As AI becomes an integral part of our daily lives, the role we play as designers crafting intuitive, transparent, and enjoyable user experiences is more important than ever. By applying the principles of keeping it simple, leveraging familiarity, simplifying choices, focusing on the essentials, and maintaining flow, we can create AI-powered products that truly resonate with users.

I'm really happy that I went down this rabbit hole; it not only refreshed my understanding of these fundamental principles but also reminded me of their impact on our work. Designing with these concepts in mind doesn't just make our AI systems better; it makes them more human-centered and accessible.

Remember, these principles aren't exclusive to AI design. They're universal guidelines that enhance any project we undertake. As we continue to innovate and push the boundaries of technology, it's crucial that we keep our users at the forefront of our minds.

So, how will you apply these principles in your next design project?

Let's make a conscious effort to:

  • Explore new ways to simplify and clarify our designs.

  • Incorporate familiar elements to make users feel at home.

  • Streamline choices to enhance decision-making and satisfaction.

  • Prioritize features that deliver the most value to our users.

  • Ensure our systems are responsive to maintain user engagement.

By doing so, we’ll not only improve the products we create but also contribute to a more user-friendly and empathetic digital world. I'm excited to see how we all incorporate these principles into our work moving forward.

Happy designing!

Feel free to share your thoughts or experiences—I’d love to hear how you're bringing these principles to life in your own projects.

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

Start Reader Feedback Survey

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

]]><![CDATA[Designing for AI Agents: A New Frontier for Product Designers]]>https://www.uxsidequest.com/p/designing-for-ai-agents-a-new-frontierhttps://www.uxsidequest.com/p/designing-for-ai-agents-a-new-frontierTue, 10 Sep 2024 11:03:11 GMTHi there, happy Tuesday! Today’s post is designed to spark curiosity and ideas about how AI agents are reshaping user interactions and the product landscape. We’ll dive into how designers can create human-centered experiences that ensure transparency and build trust. We’ll also explore new technologies and how we can rethink the elements and tools we provide users to interact with these platforms. My goal with this post is to inspire you to think differently about product design as we continue to contribute to the building of AI products.

Before diving in Id like to encourage you to reach out or drop a comment! I’d love to hear your thoughts and questions!

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

As AI continues to evolve we need to rethink how users interact with these systems. It’s no longer enough to rely on text-based conversations alone. AI agents are becoming more autonomous, capable of handling more complex tasks, and as product designers, it’s on us to create interfaces and experiences that go beyond what we’re used to. In this post, I’ll dive into some key questions we should be asking as we integrate AI agents into our products and how we can make user experiences more intuitive and engaging.

What Are AI Agents?

A flowchart titled 'AI Agents #101' visually explaining the steps an AI agent follows to answer a user's question. The flow begins with 'The user asks a question,' followed by 'The AI thinks about the steps it needs to take to find the answer.' Next, 'The AI takes action by following the plan to get the answer.' If needed, the AI pulls information from tools or databases. The AI then checks whether the answer is good enough to respond to the user's question. If yes, the agent provides the final answer; if no, the AI makes a new plan and tries again.
caption...

Before we dive into the design aspects, let’s talk about what AI agents actually are. You’re probably already familiar with advanced language models (LLMs) like ChatGPT, which respond to user inputs and can handle a wide range of conversational tasks. However, AI agents take this a step further. While LLMs primarily rely on users to prompt them, AI agents operate with greater autonomy. They not only answer questions but also gather data, take actions, and make decisions based on predefined goals or real-time user behavior. In essence, AI agents can manage multi-step processes and carry out tasks with minimal ongoing input from the user, allowing for a more seamless and proactive interaction.

This ability to act independently is what sets AI agents apart. They’re not just passively waiting for instructions but are actively working towards completing tasks or anticipating what the user might need next. For product designers, this shift challenges us to rethink how users will interact with these agents, ensuring the experience remains intuitive, transparent, and engaging as AI agents take on more proactive roles.

If you’re interested in learning more about what AI agents are and how they differ from traditional LLMs, I highly recommend checking out these videos: AI Alfie and IBM’s overview. They provide some of the best visual explanations of these systems and really opened my eyes to the possibilities.

AI Processes and Decisions: Building Trust Through Transparency

A Venn diagram with three overlapping sections labeled 'Controls,' 'Trust,' and 'Transparency.' The left circle, labeled 'Controls,' includes the note: 'Control: Highlighting interaction points where the user can intervene, adjust, or stop the AI process.' The right circle, labeled 'Transparency,' includes the note: 'Transparency: Represented through clear communication between the AI agent's processes and the user.' The overlapping section in the center is labeled 'Trust' with the note: 'Trust: Feedback loops to visualize the user's ability to refine or tweak the AI output.' The diagram visually represents the relationship between controls, trust, and transparency in the design of AI systems.

As we integrate AI agents into more complex systems, one of the most important things we need to address is how users will understand and trust the AI’s decision-making.

Ask yourself: How do we present the AI’s processes in a way that feels transparent and trustworthy?

Transparency is crucial for building user confidence in AI-driven processes. This goes beyond simply showing users what the AI is doing—it’s about helping them understand what the AI agent can do, how it works, and why decisions are made. Applications that meet these expectations not only ensure users feel in control but also drive greater adoption and retention.

Example scenario: Imagine a banking app that uses an AI agent, acting as a personal accountant, to help users budget, it might optimize their spending budget, and manage investments and retirement planning. To do this the agent would need to take data from various accounts and possibly even look at the users age, income, historical spending patterns etc. in order to auto allocate funds as needed. As designers, the high level challenge is: How do we create an experience that is clear and builds trust in the AI’s decision-making process? Else why would anyone use this product right?

Designer Considerations:

Thinking about this example scenario, it might all start with the user’s first interaction—onboarding and setup. How do we guide users through linking their accounts and providing the necessary information? How might the system clearly explain how each piece of data will be used to meet their financial goals. At every step, communication should be simple and clear—whether through visual cues, onboarding flows, or conversational prompts—so users always know what the agent is doing with their data and the decisions it’s making on their behalf.

We might also consider how much control users have. Can they adjust what the AI manages or step in when needed? Transparency here means not only showing how the AI uses data but also how it arrives at decisions. Visual elements like progress bars, action logs, or decision trees can help make the AI's reasoning clearer, which in turn will give users more confidence and control.

We must also be clear about what the agent will do and how it will do it over its lifecycle. For example, if the AI suggests reallocating investments, it should explain why this action is recommended and how it aligns with the user’s goals, maybe even providing references and links along the way. This way, users understand both the strategy and the data driving the decision.

Takeaway: As designers, it’s our responsibility to make AI decision-making as transparent as possible. From the setup process to ongoing usage, we need to provide clear communication about what the agent is doing and offer users meaningful control. By ensuring transparency at every stage, we can foster trust and create user-friendly systems that feel intuitive and reliable. A big point to think about here is how this all looks—it's likely to depend on the application and context, right?

If you’re interested in diving deeper into this topic, the team at Microsoft has done an amazing job creating guidelines that empower designers and product teams to deliver human-centered AI experiences. You can explore their guidelines here: Microsoft AI Guidelines.

Redefining Interaction Channels: Moving Beyond Text

A mind map titled 'Brainstorming AI Agent & Human Interactive Elements' shows different ways AI agents can interact with humans. On the left, ideas include gesture commands (hand, eye, touch), voice commands (natural language, voice recognition), written commands, and data visualization (charts, graphs, heatmaps). On the right, ideas include smart notifications (real-time updates, touch point reports), smart information cards, conversational elements (emotion recognition, personalization, adaptive explanations), and decision logs (expandable logs, timelines, drill-down tables). A lightbulb icon in the center represents idea examples.

Conversational or chat-based interfaces are powerful, but they shouldn’t be the only option. To fully leverage the potential of AI agents, we should explore alternative channels like gestures, buttons, smart elements, or voice commands. These options can simplify interactions while making the experience feel more intuitive and engaging.

Example scenario: Imagine an AI agent that sets up follow-up meetings with agendas based on ongoing conversations. While a chat-based summary could be provided, visual timelines, an interactive smart calendar UI, or voice assistants could allow users to adjust meeting details more naturally. These are not one-size-fits-all solutions, and there’s potential for these elements to overlap, creating a richer, more layered design. We should consider how these elements fit together seamlessly and what the right combination is to create the best user experience.

Designer Considerations:

When thinking about communication channels, it’s important to also consider how UI elements evolve based on user needs and the context of the interaction. For example, smart information cards that adapt to user input or task progress can be a powerful tool for providing users with up-to-date, relevant details. These cards might display meeting agendas, recent adjustments, or notifications about key changes, all in a way that’s easily digestible and actionable.

As time passes and schedules become busier, the AI agent might detect new information, such as participants answering follow-up questions elsewhere. How should the agent respond to evolving information? Should it notify users, adjust the agenda automatically, or suggest changes based on this context? Notifications and touch point reports—which highlight key updates or actions—could inform users in real time without overwhelming them. These touch points serve as ongoing, dynamic interactions between users and the system, ensuring transparency and user control.

Another consideration is how evolving UI elements, like smart notifications, can make the interaction feel more fluid. These notifications could appear as layered visuals, providing context-sensitive actions—such as approving changes or reviewing updates—without requiring users to switch to a different interface. This allows for a smoother flow, helping users manage complex tasks more efficiently.

What would this all look like? Thinking through how notifications, smart cards, and other interactive communication elements come together will be crucial to designing seamless, AI-agent-powered experiences.

Takeaway: As designers, we need to think beyond chat interactions and consider how evolving UI elements, smart information cards, and notifications work together to create user-friendly systems. Our goal is to ensure interacting with AI feels as natural and intuitive as possible, allowing communication channels and touch points to evolve alongside the user’s needs and the task at hand.

For those looking to explore this further, I highly recommend The Shape of AI, a resource published by Emily Campbell. It’s a fantastic guide for anyone thinking about the new frontier of AI and how we, as designers, should be leveraging key elements and principles. You can check it out here: The Shape of AI.

Expanding Our Role as Designers in AI Systems

As AI agents become more autonomous and integrated into everyday products, the role of design in shaping intuitive, transparent, and effective user experiences becomes even more critical. By understanding how AI agents differ from traditional models, emphasizing transparency in AI-driven decisions, and exploring alternative communication channels, we can create systems that empower users and foster trust.

Designers have a responsibility to go beyond the surface-level interactions and think deeply about how UI elements, smart information cards, and notifications can be used to deliver meaningful, engaging experiences. As we continue to explore the potential of AI, it's crucial that we stay ahead of the curve and remain thoughtful in how we approach the design of AI systems.

By leveraging the insights discussed here and utilizing resources like Microsoft's AI guidelines and Emily Campbell’s The Shape of AI, we can help define the future of human-centered AI design. The question now is: How will you apply these principles in your next AI-powered product?

Next Steps for Designers:

  • Explore multi-modal interactions with AI agents.

  • Focus on transparency, control, and collaboration in AI design.

  • Keep up with the latest AI advancements to continue improving user experiences.

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

Start Reader Feedback Survey

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

]]><![CDATA[Are You Asking the Right Questions? Discover the 5W1H Framework for Design Excellence]]>https://www.uxsidequest.com/p/are-you-asking-the-right-questionshttps://www.uxsidequest.com/p/are-you-asking-the-right-questionsTue, 03 Sep 2024 11:02:01 GMTGood morning, designers! I hope you had a relaxing Labor Day weekend! Believe it or not, it's not just the beginning of September—it’s also a milestone for our newsletter, marking four consecutive weeks of sharing content! Thank you all for joining me on this journey. Though it’s just getting started, I’m excited about our continued growth!

As I reflected on this milestone, I started thinking about the nuggets of wisdom I've gathered over the years that have helped me tackle various design challenges. And one key phrase kept coming back to me: What questions was I asking?

It might not sound like much at first, but think about it—knowing the right questions to ask and when to ask them can make all the difference. It’s a skill that can change the course of even the biggest projects. With this in mind, get ready, because today I'll be sharing with you the 5W1H framework that will help you solve any problem. But not only that I’ll also be providing you with a FREE Figjam template so that you will be able to integrate it into your next project. 

For some of you, this might be a refresher; for others, you may have just stumbled upon gold. These techniques will set you apart from designers who are simply winging it.

But before we dive into that... let’s start with this week’s trivia question 😉

Trivia Time!

trick question GIF

By now, we're all pretty familiar with mobile games and apps. There are probably millions to choose from, and it can be overwhelming to think about just how far we've come. But have you ever wondered where it all started? Which game set the stage for the mobile gaming revolution?

Well, with that, here comes this week’s trivia question!

Which of these puzzle games, released on July 10th, 2008, among the 552 initial App Store apps, is widely cited as one of the first breakout hits?

A) Bejeweled
B) Trism
C) Sudoku Master
D) Tetris
E) Enigmo

Find the answer at the bottom of today’s newsletter! 

Exploring the 5W1H Framework: From Origins to Product Design

The 5W1H framework is a time-tested tool originally developed for journalists, detectives, and even scientists to systematically approach and solve complex cases. By asking six fundamental questions—Who, What, When, Where, Why, and How—these professionals could quickly and effectively uncover the essential details of any situation. This structured approach ensures that no stone is left unturned, making it invaluable in fields where thoroughness and accuracy are paramount.

Though I had heard of this framework before, it wasn’t until I read Artiom Dashinsky’s book, Solving Product Design Exercises, that I truly grasped its power. Dashinsky took the traditional 5W1H framework and adapted it specifically for product design, revealing how these simple questions can lead to profound insights when designing products. Since then, I’ve frequently referenced this framework and discovered various other adaptations that enhance its utility in the design process. 

With this in mind today we’ll dive into each of the six key questions exploring how they can be applied to product design. For those who want to put this into practice immediately, I’ve created a FigJam template that you can access and use to guide your own projects. The framework is not only quick and effective but also versatile, making it a must-have tool in your design arsenal.

FigJam Template

Cover image for the 5W1H Discovery Template in FigJam, showcasing an overview of the process with key phases, interactive cards, and features like key considerations and example questions for each phase. Includes a photo of Cristian Pineda, who discusses UX, UI, and Gen AI.
🌐Click Image to access 5W1H FigJam Discovery Template by Cristian Pineda

The 5W1H Framework: A Deep Dive

Below, we’ll dive into each of the six questions—Why, Who, When & Where, What, and How. You might notice that the traditional order has been adjusted, and that’s intentional! I’ve rearranged the sequence to better align with the design thinking process, making it more intuitive and helping you gain a comprehensive understanding to deliver the most impactful solutions. Let’s dive into it, starting with our Why.

🔎 Why Are We Building This?

Clarify the purpose and rationale behind the project. Understanding the "why" is crucial to ensuring that the project's goals align with the needs of the stakeholders and end-users.

Key Considerations:

  • Why is this project important?

  • What problem are we trying to solve?

  • Why does this solution matter to the stakeholders and end-users?

  • Why is this the right time to address this issue?

  • Why does this project align with our broader goals or strategy?

Note: Remember, understanding the "why" not only drives purpose but also keeps the team aligned and motivated throughout the project.

🔎Who Needs to Be Involved and Who Are We Building This For?

Identify the end-users, key stakeholders, and relevant team members. Ensure that all voices are included to avoid building in silos, and remember to consider input from all necessary parties throughout the project lifecycle.

Key Considerations:

  • Who are we building this for, and what are their needs?

  • Who will use the final product, and how does that influence the design?

  • Who are the primary stakeholders?

  • Who needs to be involved at each stage of the project?

  • Who will provide input, feedback, or approval?

Note: Involve early, involve often—engagement and collaboration are key to avoiding misalignment and ensuring the project meets its objectives.

🔎When and Where Will It Be Used?

Determine the timeline and context for the project's use. Gain an understanding of when and where users will interact with the product, feature, or service to ensure it fits their needs and environment.

Key Considerations:

  • When does this project need to be completed?

  • When will the end-users interact with the product?

  • Where will the product be used (e.g., physical location, digital platform)?

  • When and where will key milestones occur?

  • Are there any timing or environmental factors that could impact the project?

Note: Consider the user’s environment and timing—context is key to delivering a solution that truly resonates with and supports the user.

🔎What Are We Building?

Define the scope, objectives, and deliverables of the project. Clearly understanding what you are building ensures that everyone is aligned and that the project stays on track.

Key Considerations:

  • What are the specific goals of this project?

  • What features or components need to be included?

  • What are the expected deliverables?

  • What constraints or limitations must be considered?

  • What are the success criteria for this project?

Note: Clarity in scope leads to clarity in execution—ensure that all team members understand exactly what is being built and why.

💡Bring the Idea to Life

Though this step isn't one of the original 5W1H questions, I’m including it to provide important context. By now, you’ve gathered all the necessary insights and considerations. You’ve defined what you’re building, who it’s for, when and where it will be used, and why it matters. With all this information in hand, you’re ready to bring your idea to life. This is the moment where planning meets action—take all that you’ve learned and start brainstorming and building the solution that will make an impact.

Note: Don’t forget to use tools like a Prioritization Matrix to identify which solution to move forward with! This can help you focus on the ideas that offer the most value and are the most feasible to implement.

⏱️How Can We Measure Success?

Once you have a solution in place, it’s crucial to track how you will measure its success. Establish the metrics and evaluation methods that will help you understand the impact and effectiveness of the solution, ensuring it meets the project’s goals and user needs.

Key Considerations:

  • How will we measure success?

  • How will we track progress throughout the project?

  • What key performance indicators (KPIs) are relevant?

  • How will we gather feedback from stakeholders and end-users?

  • How will the results be analyzed and reported?

Note: It’s not just about checking off boxes—consider the experience as a whole to truly gauge the impact and effectiveness of the project. Don’t forget to use tools like a prioritization matrix to identify the best possible solution.

This wraps up the core 5W1H framework for product design. Remember, this is a powerful tool for product designers, providing clarity, focus, and a structured approach to tackling design challenges. By applying this framework, you can ensure that your projects are grounded in solid reasoning, well-aligned with stakeholder needs, and ultimately successful in delivering impactful solutions.

I hope you found this content valuable and that it helps you in your design journey. If you’re interested in learning more, I encourage you to check out the references below.

References

Note: Today's post is not sponsored; I’m simply sharing resources that I found genuinely valuable in my work.

Cool Tech of the Week: Mixing It Up

today gon GIF

This week, I’m mixing it up a bit. While I normally share a single tech news highlight, this time I want to open things up and share a few cool tech developments and news stories that caught my eye. Let’s dive in!

  • Gantri Revolutionizes Lamp Design with Customizable Colors

    • Why It’s Cool: Gantri, a leader in 3D-printed lighting, has introduced a groundbreaking color customization system for their lamps, offering up to 4,000 unique combinations. This innovation not only highlights Gantri's commitment to personalized design but also underscores the potential of 3D printing in product design.

    • Read more: Gantri Customizable Lamps (Wired)

    Scientists Use DNA to Build Chess Playing Computer

    • Why It’s Cool: This breakthrough in bio-computing offers a glimpse into a future where biological processes could revolutionize computing power and efficiency. This could open new avenues for innovation, particularly in fields requiring complex data analysis and biomimicry.

    • Read more: DNA-Based Computing (Yahoo)

    Emotion AI Emerges in Business Software: Potential and Pitfalls

    • Why It’s Cool: Emotion AI in business software is revolutionizing how technology interacts with users by detecting and responding to human emotions. This trend offers exciting possibilities for personalized user experiences and enhanced customer engagement, though it also raises ethical concerns about privacy. For product designers, it emphasizes the importance of ethical AI development while showcasing the potential to create more empathetic and user-centered products that drive business value.

    • Read more: Emotion AI in Business Software (TechCrunch)

    Hyundai Confirms Production of Retro-Futuristic N Vision 74

    • Why It’s Cool: Hyundai’s N Vision 74, a hybrid sports car concept, is confirmed for production, blending retro-futuristic design with cutting-edge technology. For product designers, the N Vision 74 is a case study in balancing heritage and innovation, demonstrating how design can drive both form and function.

    • Read more: Hyundai N Vision 74 (Top Gear)

That’s a wrap on this week’s Cool Tech! I hope you enjoyed this broader look at some of the exciting developments happening in the tech world. Whether it’s sustainable design, groundbreaking scientific advancements, or the ethical implications of AI, there’s always something fascinating on the horizon. As always, I encourage you to stay curious and keep exploring!

Trivia Question Answer

confused wyatt cenac GIF by People of Earth TBS

Earlier in the newsletter, I asked: Which of these puzzle games, released on July 10th, 2008, among the 552 initial App Store apps, is widely cited as one of the first breakout hits?

A) Bejeweled
B) Trism ⬅️ Correct Answer
C) Sudoku Master
D) Tetris
E) Enigmo

That’s right Trism is the correct answers! Released on July 10th, 2008, as part of the 552 initial apps on the App Store, Trism quickly became one of the first breakout hits in the world of mobile gaming. This innovative puzzle game, designed and developed by Steve Demeter, introduced a unique twist to the match-three puzzle genre by incorporating diagonal and triangular sliding mechanics—a fresh take that caught the attention of users and developers alike.

But Trism didn’t just make waves for its gameplay. Steve Demeter's story is equally inspiring. Prior to the release of Trism, Steve was working a regular 9-to-5 job as a software engineer. Fueled by his passion for gaming and a desire to create something new, he spent his evenings and weekends developing Trism. His hard work paid off—Trism grossed $250,000 in just the first two months after its release.

After the success of Trism, Steve Demeter went on to further impact the gaming industry by inspiring a generation of indie developers. He became a symbol of what could be achieved with creativity, perseverance, and a willingness to take risks. His success with Trism encouraged countless others to try their hand at developing apps, showing that one person with a great idea could indeed make a significant impact in the tech world.

Inspiration for Designers:

As designers, there’s so much to learn from stories like Steve’s. The world of design and development is vast and full of opportunities. Don’t be afraid to explore your interests, experiment with new ideas, and push the boundaries of what’s possible. Whether you're working on a mobile game, a new app, or a product design project, remember that innovation often starts with a small idea and a lot of passion. Who knows? Your next side project could be the next big thing!

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

Start Reader Feedback Survey

]]><![CDATA[Tips for integrating AI into your design process]]>https://www.uxsidequest.com/p/tips-for-integrating-ai-into-yourhttps://www.uxsidequest.com/p/tips-for-integrating-ai-into-yourTue, 27 Aug 2024 11:00:56 GMTGood morning designers! Today, I want to start by expressing my sincere gratitude to all of you who reached out about the free template included in last week's post—your feedback and enthusiasm truly made my week!

As for today's post, it's one I've been particularly excited to share. Over the past few weeks, some of you might have noticed that I've been running a series of surveys on how designers are using AI to enhance their workflow. While the results are still pending, the insights I've gathered so far have already sparked a lot of inspiration.

As both an AI power user and designer, I've experienced firsthand the transformative impact AI can have on our work. I often find myself thinking, "I wish I had tools like this when I first started," and this sentiment has largely motivated me to write this post—it's all about helping you supercharge your design workflow with the power of Gen AI.

So, whether you're new to AI or already experimenting with it, I hope the tips I share today will provide you with some practical ways to integrate AI into your design thinking process.

Trivia Time! 

Rhett And Link GIF by First We Feast
GIF courtesy of Giphy via First We Feast.

It’s safe to say that we’re all pretty used to touchscreen devices—they’re a common part of our everyday lives now. But as you may know, this wasn’t always the case. Crazy, right? Seriously, could you imagine a world without touch screens? What would Candy Crush or Angry Birds look like? I guess we’ll just have to wonder! But with that in mind, here’s today’s trivia question: 

➡️ Do you know what the first product to introduce a touchscreen was?

Find the answer at the bottom of today’s post! 

Tips for integrating AI into your design process

The Importance of AI in Design

In today’s fast-paced design world, staying competitive requires more than just keeping up with trends—it’s about leveraging the right tools to get ahead. AI isn’t just a buzzword; it’s a powerful resource that helps you work smarter, create better user experiences, and maintain your edge in the industry. By streamlining repetitive tasks and providing data-driven insights, AI can be a game-changer in your design process.

To help you maximize the benefits of AI, I’m breaking down how you could use it within each phase of the design thinking process. I’ll be presenting you with a few scenarios and examples of prompts based on my real-life interactions with Gen AI models like GPT, Claude, and Co-pilot. To avoid overwhelming you with information, we’ll start with the discovery phase today, and in future posts, I’ll focus on each subsequent phase. So whether you’re new to AI or already experimenting, these tips will offer practical ways to integrate AI into your everyday work.

Scenario 1: Preparing for a Kick-Off Meeting

Scenario: I need to prepare for an upcoming kick-off meeting where we’ll discuss the project’s objectives and next steps. I want to ensure I’m prepared to ask the right questions and cover all critical areas so that I can confidently move forward in my workflow.

Thoughts: In situations like this, I like to treat my AI assistant as a sounding board and ask if I’m missing anything or if it suggests adding something to my questionnaire lineup. It’s an opportunity to provide details about the general problem space, maybe even share some questions I already have queued up. You might find that the very act of writing out your thoughts can go a long way. Below I’ll share an example of how this could be put into practice.

Prompt Example: “Hey chat, I’m going into a kick-off meeting to discuss next steps for the new checkout flow for our e-commerce store. My briefing says users are having a hard time moving forward after reviewing their cart, and we’ve heard loading times can get pretty messy during this step. Aside from timelines, what other questions should I be asking during this call? Consider that I’m a UX/UI designer at XYZ Ecommerce store.

Leveraging the response: As you review your AI assistants suggestions, keep in mind that your expertise as a designer is key. Use your understanding of the project to filter out what’s most relevant. Not everything will apply, but that’s okay—focus on what will truly drive the conversation forward with your team. I encourage you to also play around with the possibilities maybe you can even ask your AI assistant to help craft a meeting agenda that centers on the most important points. The goal here is to take these tools, adapt them to your needs, and make the process uniquely yours.

Scenario 2: Creating a Lean User Persona

Scenario: I might be resource-constrained, but I want to create a lean user persona that includes high-level attributes based on my understanding of the user or customer. This persona could be used to align with others on the team, creating a common language as we prepare for a user research testing plan.

Thoughts: I’ve found this to be a great way to save time. By leveraging my AI assistant to help organize my thoughts, I can quickly create and refine personas. Since personas often have multiple attributes, I like to explicitly ask for the ones I feel are most relevant and request the persona in a table format. This makes it easier to comb through the details and make adjustments as needed. See the prompt example and interaction below for how this might look.

Prompt Example: “Hey chat, I need to create a lean user persona for a quick alignment with my team. Here’s what I know: Our product is a fitness tracking app designed for users who are new to fitness routines and need guidance on forming healthy habits. I understand our users to be tech-savvy millennials who value convenience and personalized experiences. Can you help me draft a persona that includes the following key attributes: name: age range, goals, pain points, tech proficiency, and activity level. Please present the information in a table format for easy review.”

How to Leverage the Response: While the AI-generated persona is a great starting point, remember that it’s not exhaustive. Don’t hesitate to add or modify fields that you feel will be important when communicating with your stakeholders. The persona should be a flexible tool that evolves as you gather more information and insights. Customize it to fit your project’s needs and make sure it aligns with your team’s understanding of the user.

Scenario 3: Generating a Testing Plan Report

Scenario: I’ve identified that a user research study is required to better understand why users are not finding the onboarding experience of our [SaaS idea] satisfactory. To align our team and stakeholders on the objectives and scope of this study, I need to generate a comprehensive testing plan report. This report will clarify why the study is being conducted, what type of research will be used, and how the results will be tracked.

Thoughts: Using an AI assistant can save significant time by helping you draft a detailed report that includes all necessary information. Leveraging AI in this way allows you to gather your thoughts and ask clarifying questions to ensure the report is accurate and tailored to your needs. Below, I'll share how I might approach asking ChatGPT to aid in this process

Prompt Example: “Can you help me generate a testing plan report for our upcoming user research study? The report should include the purpose of the study, the research methodology we’ll use, a list of stakeholders, our expectations, and how we will track the results. Please ensure the final document is formatted as a Word doc. Before we begin, please ask me clarifying questions to ensure the report is accurate.”

How to Leverage the Response: The AI’s generated report will give you a solid foundation, but it’s important to review and customize it to fit the specific needs of your project. Make sure to answer any clarifying questions the AI might ask, as these will help tailor the report to your exact requirements. Once the initial draft is ready, use it as a springboard for further refinement, ensuring all details are aligned with your project goals. By taking the time to personalize the AI-generated content, you can ensure that your testing plan report not only meets but exceeds expectations, providing clear guidance for your team and stakeholders.

Scenario 4: Brainstorming and Drafting a Survey

Scenario: I want to identify areas where we can introduce new features or enhance existing ones. To do this, I consider drafting a survey that can be sent to both existing users and potential customers. The survey could explore both current user experiences and potential future needs, helping me gather insights that will drive user engagement and app improvements.

Thoughts: Starting with a template is often easier, but even then, finding the right words and potential answers can be time-consuming. This is where an AI assistant can really help. By assisting in brainstorming and drafting a survey, AI can streamline the process, ensuring that the questions are targeted and relevant. In the example below, I'll share how I might approach asking ChatGPT to help me brainstorm for the scenario described above.

Prompt Example: “Can you help me brainstorm and draft a survey for our photo-sharing application? The survey should aim to identify areas where we can introduce new features or enhance existing ones. It will be sent to both existing users and potential customers, so please include branched questions that explore both current experiences and potential future needs. For each question, please provide a brief explanation of why it’s important. The goal is to gather insights that will help us improve the app and drive user engagement. Before we proceed, please ask any clarifying questions to ensure the survey aligns with our objectives and effectively targets our audience.”

How to Leverage the Response:
The AI-generated survey draft will provide a solid starting point, but it's essential to review each question carefully. Make sure the branching logic accurately reflects the different perspectives of existing users and potential customers. Also, consider the rationale provided for each question—this will help ensure that every question has a clear purpose and contributes to your overall goals. If needed, adjust the questions or add new ones to better align with your specific objectives. By taking the time to personalize and refine the survey, you can ensure that it effectively gathers the insights needed to enhance your photo-sharing app and boost user engagement.

Scenario 5: Assisting with competitive analysis

Scenario: As part of the discovery process, we identified that examining how competitors handle similar workflows would greatly aid in our ability to design a solution. This typically involves searching for relevant companies and applications, reviewing their workflows and design patterns, and assessing user sentiment around the overall product. However, this process can be time-consuming—starting with finding companies that are strong candidates for comparison and then researching the specific patterns they use.

Thoughts: In my experience, asking an AI assistant to support competitive research can save hours and uncover insights that might have otherwise gone unnoticed. However, it’s important to fact-check and explore each app more closely. Using tools like Mobbin in conjunction with your AI assistant can be a game changer. Below, I’ll share an example prompt of how I might interact with an AI assistant to get started with a scenario like the one above.

Prompt Example: “Can you help me identify five companies that might be good candidates for a competitive analysis? I’m working on creating a sharing/inviting team members feature within our infinite canvas workspace. I’m interested in understanding how they are solving for this specific design workflow. Also, please provide a link to customer reviews that I can read through.”

How to Leverage the Response: The AI-generated list of companies provides a solid starting point, but it’s crucial to dig deeper. Use tools like Mobbin to explore visual design patterns and see how they align with your own design challenges. Don’t hesitate to ask clarifying questions to understand why the AI provided certain data, just as you would with a human. This approach allows you to gather insights and inspirations that you can refine and adapt to your product’s needs. By combining AI research with hands-on exploration, you can uncover innovative solutions and streamline your discovery phase.

Embrace AI as a Design Ally

As we’ve explored, AI can be a powerful ally in your design process, helping you work smarter and more efficiently. But remember, while AI can provide valuable insights and streamline tasks, it’s your creativity and insight that will ultimately drive successful outcomes. Embrace AI as a tool that enhances your abilities, not replaces them.

I encourage you to explore AI tools and experiment with integrating them into your workflow. Whether you’re just starting out or looking to deepen your use of AI, remember that this is just the beginning. The potential of AI in design is still expanding, and by staying curious and adaptable, you can continue to leverage AI to push the boundaries of what’s possible in your work.

Cool Tech of the Week

Self-Adjusting Brain Pacemaker for Parkinson’s Disease

An illustration of a human brain with a microchip embedded in the center, symbolizing the integration of technology with human cognition, against a blue background.
Image created by Cristian Pineda with Adobe Firefly

This week, the NIH highlighted a groundbreaking development in healthcare technology: a "brain pacemaker" using adaptive deep brain stimulation (aDBS) to help reduce Parkinson’s disease symptoms . This AI-powered device, was tested in a small NIH-funded trial, adjusts stimulation in real-time based on brain activity, offering a more personalized and potentially more effective treatment than conventional deep brain stimulation (DBS) methods .

Why It’s Cool: The aDBS system represents a significant leap forward in personalized medicine. Using machine learning algorithms, the device monitors brain signals and dynamically adjusts electrical stimulation to meet the patient’s immediate needs. This "closed-loop" technology creates a continuous feedback mechanism that can counteract symptoms as they arise, providing more precise management of Parkinson’s disease. Additionally, patients have the flexibility to switch out of the adaptive mode or turn off the treatment entirely with a handheld device, offering them greater control over their treatment.

Design Insights: This innovation is a powerful example of how AI can be leveraged to address complex, real-world challenges in healthcare. For designers, it opens up opportunities to ask critical questions: How do users interact with the device? What trends and data are most relevant for doctors? How is the data communicated, and how can it be made clearer to ensure continuous advancements? These are the types of considerations that can drive impactful design in specialized use cases like this, pushing the boundaries of what’s possible.

Read more about it:

  1. NIH News Release

  2. Perplexity AI Summary

  3. YouTube Video Overview

Survey question answer

fallontonight giphyupload game friends jimmy fallon GIF
GIF courtesy of Giphy via The Tonight Show Starring Jimmy Fallon.

🥇 The IBM Simon: The First Smartphone That Paved the Way for Future Innovations

In 1994, the IBM Simon Personal Communicator made history as the world's first smartphone, a device that was truly ahead of its time. Designed by Frank J. Canova, a visionary designer and engineer at IBM, the Simon was a groundbreaking product that combined the functionalities of a mobile phone and a Personal Digital Assistant (PDA). What set the Simon apart was its touchscreen interface—a feature that would later become a standard in smartphones.

Design and Development: Frank J. Canova led the project with the goal of integrating communication and computing into a single handheld device. The Simon allowed users to make calls, send emails, manage contacts, and even run rudimentary apps, all through a touchscreen that could be operated with a stylus or a finger. This was a revolutionary concept in the early 1990s, setting the stage for the smartphones we use today.

Market Introduction and Consumer Access: The IBM Simon was officially released to the public in 1994, available exclusively in the United States through BellSouth Cellular. Priced at around $899 with a service contract (equivalent to roughly $1,600 today), it was positioned as a high-end device for business professionals. However, its high cost, limited availability, and a battery life of just about an hour restricted its appeal and accessibility to the broader consumer market.

Legacy and Influence: While the Simon was not a commercial success, selling only around 50,000 units, it laid the crucial groundwork for future smartphones. It demonstrated the potential of combining telephony with computing and showed that a single device could handle multiple communication tasks.

However, it wasn't until over a decade later that these ideas reached their full potential. Enter Apple, which took the foundational concepts introduced by the IBM Simon and revolutionized them with the release of the iPhone in 2007. Apple's innovation lay not only in the technology but in making it accessible and intuitive for the average consumer. The iPhone’s sleek design, user-friendly interface, and robust ecosystem of apps transformed the smartphone into an essential tool for daily life, far surpassing what IBM's Simon had started.

The IBM Simon might not have achieved widespread success, but its influence is undeniable. It was the first step in a journey that would eventually lead to the iPhone, a device that would define the smartphone era and change the way we interact with technology.

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

Start Reader Feedback Survey

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]]><![CDATA[Using Task Success Rate for More Insightful Design Decisions]]>https://www.uxsidequest.com/p/using-task-success-rate-for-morehttps://www.uxsidequest.com/p/using-task-success-rate-for-moreTue, 20 Aug 2024 11:10:38 GMTWelcome!

This past week, I was thinking about the best approaches to tracking success in our design work. It got me reflecting on how often it can feel like these aspects of design can suck the creativity right out of the process. I’ve heard this sentiment from many designers, and I completely understand. The thought of reducing our innovative ideas to a set of numbers can seem stifling. But here’s the thing: it doesn’t have to be that way.

Let’s be honest—Key Performance Indicators (KPIs) can feel restrictive, sometimes even scary. What if we don’t end up meeting them? I get it—this feeling can be intimidating. But rather than seeing this as a failure, I encourage you to reframe it as an opportunity—an opportunity to learn, dig deeper, and understand why things didn’t go as planned.

This kind of insight is invaluable and can lead to actionable changes that help in many ways—from aiding in selling ideas, gaining a clearer understanding of users, to ultimately improving your creative problem-solving efforts.

With this in mind, in today’s post, we’re going to focus on one specific KPI that I believe is essential for any designer: Task Success Rate. I’ll share with you how this metric can be leveraged in UX/UI design-specific use cases to not only measure success but also boost your creativity. I’ve also decided to include two more pieces of content that I hope you’ll enjoy: a highlight of a cool tech product or feature that I came across this week, and a trivia question to spice things up! Hope you enjoy today’s read!

Enjoy!

Cristian Pineda

Trivia

North Carolina Livestream GIF by NC Museum of Natural Sciences
GIF courtesy of Natural Sciences via Giphy

As promised here’s this issues trivia question:

What was the first product to have a barcode?

I’ll reveal the answer at the end of the article!

Task Success Rate

Now, let's dive into it. You’re probably wondering what exactly Task Success Rate is, when it’s used, and how to apply it in your design process. Not to worry—I’ve laid it all out for you below.

What it is:

The Task Success Rate measures the level to which customers can successfully complete tasks while using a product. It’s a key indicator of how effectively your design enables users to achieve their goals.

When it’s used:

This metric is particularly useful during usability testing and after launching a product update. It helps assess whether design changes have made it easier for users to complete essential tasks.

How to use it:

mad GIF by South Park

To calculate and report the Task Success Rate, follow these steps:

  1. Define a goal, a task, and success tiers related to those tasks.

    For your convenience, here are four success tiers defined by the Nielsen Norman Group, that I use and have found to be extremely helpful

    1. Complete Success:
      Users complete the task successfully with no errors.

    2. Success with a Minor Issue:
      Users complete the task but encounter a minor issue.

    3. Success with a Major Issue:
      Users complete the task but with significant difficulty.

    4. Failure:
      Users are unable to complete the task.

  2. Through testing, categorize user outcomes into your success tiers:

  3. Report the percentage of users who fall into each category. For example:

    1. 20% of participants were able to complete the task successfully with no error.

    2. 50% of participants completed the task with a minor issue.

    3. 20% of participants completed the task with a major issue.

    4. 10% of participants were not able to complete the task.

When reporting these figures, it’s crucial to include a confidence interval, which provides an estimate of how these results would generalize to the broader user population.

Note: A confidence interval tells you that if you repeated the test with a different group of users, the percentage of successful completions would likely fall within a certain range. For example, you might say, "We expect that between 13% and 29% of our overall user population would be able to complete this task with no errors." This gives you a better sense of how the results from your sample might apply to all users.

Main Takeaway:

The Task Success Rate is a powerful tool in the designer's toolkit, offering deep insights into how effectively users can achieve their goals with your product. By focusing on this metric, you can identify areas of your design that may need refinement, ensuring a smoother and more intuitive user experience. Remember, it’s not just about whether users can complete tasks, but how easily they can do so. Incorporating Task Success Rate into your design process can help you make informed decisions, boost your creativity, and ultimately deliver a better product.

Try my template!

While working on the podcast for today’s post, I realized that setting up testing can sometimes be a headache. So, I created a template to help you get started on your next user testing journey! I hope you find it helpful.

References:

Cool Tech of the Week

Free Group of People Sitting on Concrete Bench Stock Photo
Photo courtesy of cottonbro studio | Pexels

This week, Google announced Add Me on the Pixel 9, an AI-powered feature designed to solve a common problem we all face: getting everyone into a group photo without the need for selfie sticks or asking a stranger for help. So we can finally say goodbye to awkwardly wide and angled selfies… well, at least for Pixel users, that is.

Why It’s Cool:

Add Me allows users to create a group photo that includes everyone, even the person who originally took the photo, by merging two images. The feature guides you through taking two separate shots and then uses AI to seamlessly combine them, ensuring that no one is left out. No more awkwardly tilted selfies or missing members in your group shots.

Design Insights:

This feature is a great example of how AI can enhance user experiences by addressing everyday challenges. For designers, it’s a reminder to think about how technology can be leveraged to solve similar problems in creative ways.

Trivia Answer

bart simpson gum GIF
GIF courtesy of The Simpsons | Giphy via Simpsons World

In case you’re still wondering, the first product to have a barcode was… Wrigley’s chewing gum. Talk about sticking to record-keeping, huh?

All jokes aside, it’s amazing how something as simple as what is essentially a stamp has dramatically changed how society keeps track of records and inventory. It’s saved probably millions of hours that previously spent on tedious tasks. This is a great example of how innovations that improve our day-to-day lives can come in all shapes and sizes.

Ps. Learn more about the history behind the invention by listening to the podcast!

Thank you for reading today’s post!

I hope you enjoyed this week’s issue of “Cristian Talks Product Design.” Your feedback is incredibly valuable and helps me improve and deliver content that matters to you. If you have a minute, it would mean a lot if you could complete this quick 3-question survey!

Reader Feedback

]]><![CDATA[What 9 years of Designing has taught me.]]>https://www.uxsidequest.com/p/what-9-years-of-designing-has-taughthttps://www.uxsidequest.com/p/what-9-years-of-designing-has-taughtTue, 13 Aug 2024 00:16:27 GMT👋 Hi, I'm Cristian! Welcome to the first edition of Cristian Talks Product Design, where I’ll be sharing insights each week on designing exceptional products, tackling design challenges, and driving innovation in tech.

Before diving in, I want to thank you for reading! If you enjoy these posts and want to support my work, please subscribe for free to receive new updates directly in your inbox. Your support means a lot!

Table of contents

  1. My Background & Professional Growth

  2. Key Lessons Learned

  3. Conclusion

My background and professional growth

In 2015, fresh out of high school, I started exploring graphic design and photography gigs. At the time, I didn't take design too seriously and saw it more as an enjoyable hobby that fit within my skillset. However, as time went by, I started to become increasingly fascinated by the world of software products, web design, and web development.

Driven by a desire to create my own e-commerce stores, blogs, and other SaaS products, I decided to start teaching myself the basic skills required to launch these types of project ideas. These ventures collectively garnered hundreds, if not thousands, of subscribers, leads, views, and purchases. During this journey of self-education and exploration, I found myself becoming increasingly passionate about creating effortless and effective digital experiences.

This newfound passion guided me through a Columbia Engineering UX/UI bootcamp, where I refined my skills as a UX/UI designer, graduating at the top of my cohort. I landed my first official internship at a pre-seed startup called Munch as a UX Researcher. Shortly after, I secured a contract role at Ernst & Young's Gignow, where I was exposed to the healthcare industry and this experience led to a full-time position at Kaiser Permanente, where I worked on their flagship mobile application, allowing me to further hone my skills on impactful Product design projects. My work contributed to Kaiser Permanente being recognized as the 2022 Design Company of the Year by Fast Company for its user-focused app redesign. To this day it’s something that I’m very proud about.

Today, I work as a UX/UI designer at Operative Media, leading design efforts on their flagship AI assistant, Adeline, which aims to empower workflows across their AdTech ecosystem. This transition has been both challenging and rewarding, allowing me to grow in a new context, which I continue to be really excited about. To this day this is something that I am very proud about.

Reflecting on my career, which has been far from a traditional journey, I feel very accomplished. Although I feel that I have much more room to grow, I'd like to start sharing with the design community to encourage those thinking about a career in UX/UI design, those just getting started, and those who, like me, want to continue growing their skills.

With this in mind, I’ve distilled a five key lessons that have been instrumental in shaping my journey as a designer. These insights have not only been foundational to my growth as a designer but also valuable to anyone striving to excel in this field and while they may not apply to every situation, they have certainly been core to my success and can offer guidance to others on a similar path.

Key Lessons Learned

The value of self-learning and adaptability

Adaptability has been essential to my growth as a designer. I've found that exploring new interests, even those unrelated to my current work, have opened up many new possibilities in how I approach problem-solving and various aspects of my day-to-day workflow, from understanding problems to generating ideas.

Moreover, in my short professional career, I’ve witnessed design techniques, tools, and styles evolve rapidly, while new technologies have continually reshaped the product landscape. To navigate this fast-paced environment, staying adaptable has been crucial. I’d like to share a few tips that have helped me embrace self-learning and adaptability.

Tips on embracing self-learning and adaptability:

  • Stay curious: Always be on the lookout for new skills and technologies to learn, even if they don’t fully align with your day-to-day work. Follow your interests and explore the rabbit holes they lead you down—you never know what valuable insights you might discover.

  • Be proactive: Take charge of your own education through online courses, books, and hands-on practice. Almost everything you need to learn is available for free—just check Google or ask your favorite AI assistant. Who knows what you might learn.

  • Adapt to change: Be flexible and willing to shift your focus as needed to stay relevant. Don’t get discouraged if things don’t turn out as expected; remember, there are no limits to what you can achieve.

Main takeaway: Continuously learning and adapting is essential to staying relevant and thriving in any field.

Balancing creativity and technical Skills

No matter where you work, design will always involve a level of politics and subjectivity. You’ll often need to sell your ideas and reasoning, and being able to speak not only to the experience and design but also to the technical side is a game changer in these conversations. I’ve lost count of the times I’ve been told, “This can’t be done,” or “That’s a technical constraint,” only to suggest an alternative approach and hear, “Oh, right, we could probably do that.”

I’ve noticed that for myself and other designers who understand the basics of coding and the infrastructure behind software, it’s been hugely beneficial. Having this technical knowledge has not only allowed me to engage in more meaningful conversations with engineers, architects, and product managers but also empowered me to challenge constraints and push boundaries to create more innovative solutions.

Tips on Balancing Creativity and Technical Skills:

  • Leverage your strengths: Use your creative skills to enhance your technical work and vice versa.

  • Collaborate with others: Work with teammates who complement your skills to produce the best results.

  • Practice both: Regularly engage in both creative and technical activities to keep your skills sharp.

Main takeaway: Strive to balance creativity with technical proficiency to create innovative and functional designs.

Working without direction & sharing solutions

Early in your career, it’s essential to take the time to observe how others approach discovery, design, and communication. But beyond observation, I encourage you to take initiative—don't just wait to be told what to do. The real mark of a seasoned designer is not just in identifying areas of opportunity but also in proposing solutions.

This ability to both recognize issues and offer actionable ideas is something I’ve found to be the most valuable lesson in my career. By being proactive and solution-oriented, you’ll not only contribute more effectively but also grow significantly as a designer.

Tips on working without direction & sharing solutions:

  • Observe and learn: Regularly take time to watch how others approach design challenges, from ideation to execution. Absorb their methods and insights, then apply what resonates with you.

  • Take initiative: Don’t wait for tasks to be assigned—explore areas where you can contribute and take action. Proactively addressing issues or opportunities shows leadership and drive.

  • Propose solutions: When you identify a problem, don’t stop there. Go the extra mile to think through possible solutions and present them. This problem-solving mindset is key to growing as a designer.

Main takeaway: The ability to explore independently and offer concrete solutions is what sets seasoned designers apart. Embrace this proactive approach to truly excel and innovate in your design career.

Following and understand-focused process

We’ve all been there—tight deadlines can easily push you into reactive designing. But I strongly encourage following a repeatable, adaptable process that prioritizes clearly understanding the problem space. Doing so consistently leads to higher-quality work compared to rushing out the first idea that comes to mind.

A common misconception, especially early in UX/UI design careers, is the belief that every task—like user interviews, competitive analysis, or user testing—must be completed before delivering a final product. This often results in designers bypassing the discovery phase altogether. And I want to highlight that while these tools are valuable, they aren’t always necessary, particularly when resources or time are limited.

The key is to start by understanding the problem space, which will naturally guide you in selecting the right tools and steps. And never underestimate the power of collaboration; as one of my first design directors often reminded me, "I’ve never designed anything that I couldn’t improve after showing it to a few teammates." You never know what insights others might bring that could help you solve a problem.

Tips on following an understanding-focused process:

  • Ask "Why" often: Continuously question the reasoning behind design decisions to ensure you’re addressing the core problem and not just symptoms.

  • Prioritize understanding: Begin by deeply understanding the problem space before jumping into solutions. This will guide your process and keep your work focused on the right challenges.

  • Use targeted research: Conduct quick, relevant research to test your ideas and collaborate with your team to refine your approach.

Main takeaway: An understanding-focused process prevents rework and enhances the quality of design outcomes.

The Importance of effective presentations

Over time, I’ve found that adapting your presentations to fit the audience is crucial. While there are exceptions, a general guideline is to avoid sharing raw working files with higher-level stakeholders. Instead, focus on creating a narrative through slides or decks that clearly demonstrate your design journey and decision-making process. This helps keep the conversation focused and eliminates potential distractions.

On the other hand, when collaborating closely with designers or team members, sharing a Figma file or Miro board can foster more in-depth, interactive discussions. The key is to choose the right format for the right audience, ensuring your ideas are communicated effectively and your work is polished.

How to make effective presentations:

  • Adapt your presentation: Customize your approach based on who you’re presenting to — narrative-driven decks for stakeholders, detailed files for designers.

  • Create a presentation template: Develop a go-to template that helps you quickly put together presentations without starting from scratch, saving time and ensuring consistency.

  • Check for spelling errors: Always review your work for spelling and grammatical mistakes to maintain professionalism and avoid unnecessary distractions.

  • Avoid using Lorem Ipsum: Instead, use realistic content to ensure your walkthroughs stay focused and on track.

Main takeaway: Tailoring your presentation to the audience not only improves communication but also enhances decision-making and collaboration.

Conclusion

Reflecting on these five key lessons from my career, I hope these insights not only inspire you but also equip you with practical strategies to navigate and excel in your own design journey. Embrace self-learning, balance creativity with technical skills, explore without fear, follow a structured process, and communicate effectively to achieve success in your field.

I understand that it’s easier said than done, but I encourage you to give them a try—nobody is perfect so remember the key is to continuously and intentionally try to improve. If all else fails this alone will set you up for success.

I hope you found the content in this week’s post valuable. Please feel free to reach out if you have any questions or comments.

Till Next time,

Cristian Pineda

Cristian Talks Product Design is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

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