UX Mistakes That Drive Customers Away (and How to Fix Them)

Some time ago, UX GIRL had the pleasure of contributing to this shift by leading a hands-on workshop for the UX and UI design team at Silky Coders. The session was facilitated by our CEO, Magdalena Ostoja-Chyżyńska, and focused on practical, responsible, and creative applications of AI in the user experience design process - from early discovery to daily execution.

The energy in the room was undeniable. Silky Coders’ team brought openness, curiosity, and a hunger for meaningful innovation. Together, we dove deep into the new frontier of UX work - where human-centered design meets AI-supported workflows.

AI in UX: Not a Threat, but a Tool

One of the key messages of the workshop was clear: AI is not here to replace designers - it’s here to support them. Rather than automating creativity, AI can serve as a strategic partner that:

• Accelerates research in the discovery phase by summarizing large data sets, extracting patterns from user feedback, and supporting persona creation.
• Supports ideation with concept generation tools, enabling faster brainstorming and prototyping.
• Optimizes repetitive tasks such as UI variant testing, accessibility checks, and design documentation - giving designers more space for meaningful work.

According to McKinsey, teams that effectively integrate AI into their workflows can improve design delivery times by up to 30% and significantly reduce cognitive load during early research phases.

Balancing Innovation with Responsibility

An equally important topic explored during the session was responsible AI adoption. As powerful as these tools are, they come with ethical considerations: biased outputs, transparency concerns, and the risk of over-automation. The group discussed how to stay grounded in human-centered principles even as workflows evolve.

That means:

• always validating AI-generated insights with real user data,
• being transparent with stakeholders about AI’s role in the process,
• ensuring diversity in training data and critically assessing the risks of bias in the tools used.

This human-first mindset is key to ensuring AI enhances - rather than dilutes - the quality of user experiences.

Key Takeaways for UX Teams Exploring AI

For those who couldn’t attend, here are three actionable ideas from the workshop that any design team can start applying:

1. Start small, but start now. Test AI tools in low-risk areas like copy generation, image variations, or documentation support. Gradually integrate them into your design sprints.
2. Create internal AI guidelines. Align your team on when, why, and how AI should be used. Define quality standards, review processes, and ethical boundaries.
3. Treat AI as a design collaborator. Just like you might whiteboard with a teammate, you can brainstorm with AI. Use it not only to move faster, but also to explore what’s possible.

Looking Ahead

These workshops reminded us that the future of UX is not about man versus machine - it’s about collaboration between designers and technology. AI will continue to evolve, but the heart of UX will always be human insight, empathy, and creativity.

At UX GIRL, we’re proud to guide teams through this transition - not just by teaching tools, but by cultivating the mindset needed to design smarter, faster, and more ethically.

A big thank you to Silky Coders for your openness, energy, and curiosity. We can’t wait to see how your team transforms the knowledge from this session into even more impactful user experiences.

Until next time - let’s keep designing the future together.

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Is AI becoming the new operating system for digital products? After OpenAI DevDay 2025, many tech leaders would say yes. This year’s announcements go far beyond model upgrades - they offer tools that could fundamentally change how companies design, build, and monetize experiences.

At UX GIRL, we’ve analyzed the most important updates and their real impact on product teams, UX designers, and business owners.

Key Announcements You Should Know

1. ChatGPT Apps (SDK preview)
Developers can now build and distribute apps directly inside ChatGPT, using a new SDK that enables more interactive and personalized experiences. This opens up a new layer of lightweight front-end experiences without building a full UI.

2. AgentKit - AI Production Agents
AgentKit helps teams build autonomous AI agents capable of completing tasks end-to-end. Think onboarding assistants, support bots, or even product recommendation engines.

3. GPT‑5 Pro and mini models
The new GPT‑5 Pro brings higher accuracy in complex scenarios. Meanwhile, lightweight versions of image and voice models (e.g., gpt-realtime-mini) reduce operational costs by up to 80%.

4. Sora 2 via API
Sora 2 introduces text-to-video generation capabilities via API, a game-changer for education, content creation, and personalized storytelling.

5. Codex - Expanded Integrations
Slack, SDK, and enterprise-grade governance tools make Codex even more practical for building collaborative, AI-powered productivity tools.

What It Means for Product, UX, and Tech Leaders

OpenAI’s DevDay updates are more than just developer features - they’re designed for real product impact. Here's why it matters:

• ChatGPT Apps could act as alternative user interfaces for your product - fast to deploy, low maintenance.
• AI agents allow teams to automate high-touch tasks with natural language interfaces.
• Mini models lower the barrier to experimenting with AI at scale, without unpredictable infrastructure costs.

For UX teams, this means designing interactions between people and autonomous systems - where clarity, trust, and fallback mechanisms are critical.

Two Lists That Matter: Watchouts and Quick Wins

Top 5 Risks to Consider:

1. Cost management - poorly scoped AI use can lead to soaring API bills.
2. Compliance & safety - you’ll need moderation systems for AI-generated content.
3. Unpredictable UX - AI outputs must feel consistent and transparent to users.
4. AI skill gaps - many teams lack the cross-functional know-how to build responsibly.
5. No validation pipelines - AI decisions still need testing like any other feature.

Quick Wins You Can Act On Today:

• Audit product areas that could benefit from AI-powered assistance or automation.
• Launch a small experiment using AgentKit - for example, a product suggestion agent.
• Run usability tests for AI-based flows to ensure user comprehension and trust.
• Bring UX, product, and AI engineers together into AI-focused sprints.

Final Thoughts: AI Is No Longer Just an Add-On

OpenAI DevDay 2025 marks a shift - we’re moving from playful experiments to strategic deployments. Businesses that treat AI as a core product function, not a gimmick, will lead the next wave of user experience innovation.

At UX GIRL, we help clients identify high-impact AI use cases, prototype responsibly, and test with real users. Whether you're in fintech, education, health, or e-commerce - this is the moment to think AI-first, user-always.

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Conversational AI has changed the rules of user experience. With OpenAI Apps SDK, teams can now create embedded applications that live directly inside ChatGPT - offering users seamless, intelligent, and contextual support.

But building these apps isn't just about writing smart code. It's about designing meaningful, intuitive interactions. That’s why OpenAI published official design guidelines - and why UX GIRL is here to help you translate them into real results.

What Are ChatGPT Apps and the Apps SDK?

ChatGPT apps are mini-tools that users can access directly in the ChatGPT interface. They allow users to perform tasks, analyze data, create documents, fetch information from external sources, and more - all within the flow of conversation.

The Apps SDK lets developers define these app interactions using JavaScript while maintaining full compatibility with the ChatGPT interface. But to deliver real value, apps need to feel intuitive - and that’s where UX comes in.

The Core Design Principles from OpenAI

OpenAI’s UX guidelines are built on six core principles. Here’s what they mean in practice, with insights from the UX GIRL team:

Clarity is key

Your app’s interface must clearly communicate what it does, how it works, and what users can expect. Avoid vague labels or overloaded screens. Guide users with simple language and clean layout.

Respect the user’s intent

Let users take the lead. Your app should support user goals, not hijack the conversation. Avoid aggressive prompts or forced flows.

Make progress visible

Users need feedback. Loading indicators, success confirmations, and microinteractions help users trust the process - especially in a conversational UI.

Minimize user effort

Reduce friction wherever possible. Use smart defaults, context-aware suggestions, and auto-filled values to streamline user input.

Be consistent

ChatGPT has a defined look and tone - follow it. Use system UI components and maintain consistency in voice, spacing, and layout.

Fail gracefully

Errors are inevitable. Design them to be informative and friendly. Offer users clear explanations and next steps without making them feel lost.

How Product Teams Can Apply These Guidelines

Following these principles doesn’t require a full UX overhaul - but it does require strategic thinking. Here are two practical ways your team can implement them:

1. UX-aligned development workflow:

• Define realistic user conversations and app responses early.
• Prototype conversations using mock UIs or prompt flows.
• Test early and often - even with basic, Wizard-of-Oz style setups.
• Build in real-time feedback elements (confirmation messages, visual states).

2. UX checklist for Product Owners:

• Does the user always know what they can do next?
• Are all actions and outcomes clearly explained?
• Is app progress or system state visible?
• Is tone and layout consistent with ChatGPT?
• Do error messages guide users constructively?

The Unique UX Challenges of Designing Inside a Chat Interface

Unlike traditional apps, ChatGPT apps don't rely on menus, tabs, or visual hierarchies. Users interact through text - with fluid, nonlinear intent. This makes context one of the biggest UX challenges.

Small design gaps (e.g., unclear responses or missing context) can lead to confusion. That’s why good conversational design includes scenario testing, intelligent defaults, and visible state changes - even without a traditional UI.

Final Takeaways

Designing inside ChatGPT isn’t just about building functionality - it’s about earning user trust through clarity, empathy, and consistency.

At UX GIRL, we recommend:

• Start with a small MVP to test a focused user goal.
• Use OpenAI’s design principles as a design audit tool.
• Involve UX early - especially for dialogue design and testing.
• Don’t rely on AI to do everything. Guide the user intentionally.

Building with Apps SDK? Let UX GIRL help you design AI-powered experiences that convert, engage, and delight.