Human x Intelligent

Is AI redefining UX design or replacing it?
In this episode of Human × Intelligent, Madalena Costa sits down with Bruno Figueiredo, founder of UXLx and one of the longest-standing voices in UX in Europe, to explore how artificial intelligence is reshaping the design field.
From early web design to today’s AI-powered tools, Bruno brings a long-term perspective on technological shifts and explains why this moment feels fundamentally different. As AI accelerates tasks like coding, research synthesis and interface generation, the role of designers is starting to evolve in unexpected ways.
But while AI can generate outputs faster than ever and not all parts of design are equally solvable.
When we move from code to creativity, from execution to judgment and from data to human behavior, the limitations of AI become more visible.
This episode explores what AI can and cannot do in UX today and what designers, researchers and product teams need to understand to work with these systems effectively.

We discuss:
Why AI may be the biggest shift UX has ever experienced
Why code is easier for AI than creative design
The limits and risks of synthetic users and automated research
Why accessibility still depends on strong design foundations
The growing problem of AI transparency and training data
How AI is reshaping UX roles: specialists vs generalists
Why AI should be treated as a collaborator, not a replacement
What junior designers should focus on to stay relevant

//Human x Intelligent explores how humans and AI design, build and collaborate in intelligent systems//

The End of the Chatbox? Designing AI interfaces that act, not just answer
In this episode of Human × Intelligent, Madalena Costa explores one of the biggest design shifts happening in AI products right now: the possible end of the chatbox as the default interface for artificial intelligence.
Chat interfaces made AI accessible to millions of people. They are familiar, flexible and great for brainstorming, research, writing and exploration. But as AI systems become more agentic, able to plan, use tools, act across workflows and move work forward, the traditional chatbox starts to reveal its limitations.
When AI moves from answering questions to taking actions, the design problem changes.
This episode explores why chat interfaces can become inefficient inside real workflows and what product designers, UX professionals and product teams should start learning now to design more embedded, contextual and trustworthy AI experiences.
We discuss:
Why chat became the dominant AI interface
Why chat breaks in action-based workflows
The shift from conversation interfaces to action-driven experiences
UX patterns for agentic systems: previews, rationale, progress, undo and adjustable autonomy
How designers can move from building chat interfaces to designing human-AI collaboration
The future of AI interfaces is likely not 'no UI' or invisible magic. It’s embedded intelligence that supports work directly inside the product experience.

This episode was originally going to be about something else, but a conversation over the weekend reminded me of a workflow I use quite often when developing and designing applications.
So instead, I decided to share one Human × Intelligent workflow I keep coming back to:
Figma → Claude → Figma
Rather than treating AI as a chatbot outside the workflow, this setup connects Claude directly to the design environment using Model Context Protocol (MCP). That means the model can analyze interfaces, reason about product systems and help accelerate design thinking.
In this episode, I talk about:
What changes when AI connects directly to design tools
Why context makes AI much more useful for product design
Real workflows I use: UX audits, design systems extraction, dashboard analysis and component generation
The difference between Official Figma MCP and Figma Console MCP
What worked well, what didn’t work so well and what I’m still experimenting with
Why I think the real shift is AI becoming part of the workspace
This is not about replacing designers, but actually, it’s about building better collaboration between human judgment and intelligent systems.
If you’re exploring AI workflows for product design, design systems or complex SaaS products, this episode should give you a practical mental model for where things are heading.

Example workflows mentioned in the episode
UX audit of a flow: Analyze selected screens for hierarchy, cognitive load, accessibility, spacing consistency, CTA clarity and user flow friction.
Design system extraction: Analyze selected UI and identify typography scale, color tokens, spacing tokens, component patterns and layout grid.
Reusable component generation: Convert layouts into base components, variants and nested structures optimized for scale.
Dashboard refactoring:  Audit dashboards for information hierarchy, data density, scanning patterns, visual grouping and progressive disclosure.
Retention system mapping: Map a product UI to triggers, actions, rewards, feedback loops and habit formation patterns.

Setup steps
Sign up for a Figma Pro seat and Claude Pro or Max
Install Node
Install Claude Code
Create a Figma token
Enable Figma Dev MCP mode
Configure the Figma MCP server
Install Figma Console MCP locally
Install the design systems MCP assistant
Install the Desktop Bridge plugin
Install the Figma MCP server in Claude Desktop
Restart Claude Desktop
Run 'check Figma status'
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Links:
Episode page: 
Madalena on LinkedIn: /madalenafigueirasdacosta
Subscribe: https://substack.com/@humanxintelligent

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🎙️ Human × Intelligent explores how humans and intelligent systems evolve together, across product, behavior and culture.

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#AIAdoption #EnterpriseAI #HumanInTheLoop #ResponsibleAI #AIGovernance #AIWorkflows #AITrust #AILeadership

'Most AI pilots don’t fail in the demo. They fail inside the workflow.'
In this episode of Human × Intelligent, Madalena Costa speaks with Krystel Leal, a fractional AI deployment lead working at the intersection of enterprise AI implementation, customer success and real-world AI adoption.
Krystel shares a simple signal that reveals when teams are moving too fast with AI: If no one can explain why the AI produced an output, the team doesn’t understand the guardrails, the workflow or the problem being solved.
We explore what actually changes when AI starts working inside a team, where AI trust breaks and why human judgment and ownership still matter in AI-driven organizations.
The conversation also breaks down one of the most common mistakes teams make today: delegating decisions to AI instead of delegating tasks.

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In this episode, we explore:
- What changes first when AI works in a team: behavior vs mindset
- Why enterprise AI pilots often fail after the demo
- The difference between delegating tasks and delegating decisions
- The biggest signal that a team is moving too fast with AI
- Why human-in-the-loop is an ownership problem and not a checkbox
- How fear and misconceptions appear when teams start using AI daily
- Why companies must become AI education systems
- How human communication principles apply to AI prompting
- Why 'made by humans' may become a differentiator in an AI-driven world

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Key takeaway
AI does not replace judgment. The most successful teams use AI as a thinking partner and not as a decision maker.
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About the guest
Krystel Leal is a fractional AI deployment lead who spent years working in Silicon Valley tech startups before specializing in enterprise AI implementation.
She works with organizations to turn stalled AI pilots into real production systems, redesigning workflows, ownership structures and verification processes so AI adoption actually delivers value.
Her core belief: Most AI investments fail not because of the technology, but because the system around them was never built.
Connect with Krystel on LinkedIn.
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🎙️ Human × Intelligent explores how humans and intelligent systems evolve together, across product, behavior and culture.

Hosted by Madalena Costa.

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Links:
- Episode page: https://humanxintelligent.com/episodes/if-you-cant-explain-why-ai-output-happened-youre-moving-too-fast
- Krystel on LinkedIn: https://www.linkedin.com/in/krysteleal/
- Subscribe for more Human × Intelligent: https://substack.com/@humanxintelligent

In this episode, I’m joined by Krasi Bozhinkova to explore AI cosplay, the shift from AI as a tool to AI as a performed intelligence, where emotion, presence and perceived personhood become more persuasive than proof itself.

This conversation goes beyond capability.

We talk about:
- The moment AI moved from a tool to performing intelligence
- Why humans respond to emotional UX as if it were personhood
- What signals show users are no longer interacting with a system but with someone
- Why perception now competes with performance
- What responsibility do product teams carry when persuasion becomes indistinguishable from intelligence

This is not a conversation about what AI can do.
It’s about what that means for the future of product design, trust and human decision-making.
📤 https://owtcome.com/signal-brief-report-jan-26
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🎙️ Human × Intelligent explores how humans and intelligent systems evolve together, across product, behavior and culture.
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