I’m a professional with 18 years of experience scaling digital products from startups to global enterprises. I align product, design, and engineering to turn complex problems into actionable, scalable solutions.
ProjectsStarted in R&D delivering complex projects for Samsung, Nokia, and HP. This experience built my foundation in research, UI coding, and systems thinking to effectively bridge design and engineering.
Products & LeadershipTransitioning from projects to product, I delivered a Google-featured mobile app at Michelin before expanding into product leadership (PO, PM). Led operations across logistics, government, and fintech, scaling teams to 60+ professionals across 7 squads and impacting 60M+ users.
EntrepreneurshipCo-founded a B2B hiring & payments marketplace backed by Endeavor and Microsoft. Navigating its funding and post-pandemic shutdown sharpened my ability to manage uncertainty.
NowI help companies translate design strategy into users' hands. My current focus is exploring AI to enhance design processes and product deliveries.
In 2013 at Google SP with Jean Hansen, our app was selected, and we received exclusive mentorship.Facilitating the AI for Leaders workshop in 2025.
2025. Designed and coded from scratch by me using AI.
Case Study · Bloop
5-Day Prototype: Art Marketplace App
Role
Facilitator, Product Designer
Team
Founder, Product Designer
PROBLEM
Unpress is an Austin-based journalism platform spearheaded by media leaders from CNN, NBC, and Gawker Media.
Using a Design Sprint, I mapped core user flows and simplified the journey for artists. We also created the brand identity in this time. We focused on critical pain points like pricing and publishing complexity, delivering a high-fidelity prototype in just 5 days that secured stakeholder buy-in.
Artists struggled with pricing and publishing complexity, creating friction in the first experience and reducing confidence in the product before launch.
SOLUTION
RESULTS
5 DaysTime to Market
100%Stakeholder Buy-in
"Stakeholders aligned quickly around the sprint outcome, and the prototype gave the team confidence to move forward."
The pandemic forced the Conquer Business School to migrate from in-person to online overnight. Speed was critical for survival. We needed to launch recorded courses immediately, but the existing legacy system and brand didn't represent this new digital-first era.
I redesigned websites and platforms to support this massive scale. The result was a robust digital ecosystem that handled the surge of over 2 million new students. This successful pivot positioned the company for its acquisition by the Wiser Group.
The organization needed to migrate from in-person learning to digital delivery at scale, but the legacy platform and brand were not ready for a digital-first experience.
SOLUTION
RESULTS
+100Screens Designed
+2MNewly Enrolled Students
Case Study · Materialize
Fixing Rage Clicks to Increase Bookings
Role
UX Researcher
Team
Customer Success Manager
PROBLEM
Founded in 2019, Materialize was accelerated by Endeavor Scale-Up and backed by investors to scale. It operated as a B2B startup where companies bought hour credits to book video calls, while payments, validations, ratings and dispute handling maintained trust and quality. In 2025, the company surpassed half a million bookings. As a marketplace, customer trust depends on a strong feedback loop after key sessions.
As a marketplace, the customer journey had to stay frictionless until booking confirmation. Hotjar data exposed a critical drop-off: users were "rage clicking" a non-interactive element at the final step, and bookings were being lost.
The culprit was a redundant choice. 95% of users had only one wallet but were forced to "select" it—a step that looked broken and blocked progress.
I removed the friction by defaulting to the single wallet. Now, users skip the selection entirely, while the multi-wallet picker remains only for the <5% who need it.
SOLUTION
Optimizing the user flow based on data.
RESULTS
0Rage Clicks
+14%Increase in Bookings
"The updated flow removed friction at the final step and delivered a measurable lift in bookings."
Case Study · Unpress
Consistent Video Experience
Role
Lead Designer
Team
2 Designers, CTO, CEO, PM
PROBLEM
Unpress is an Austin-based platform for authentic journalism spearheaded by global media leaders from CNN, NBC, and Gawker Media, including former VPs and pioneers in video journalism. Its mission is to combat media polarization by rewarding credibility and authentic storytelling.
Some screens from the legacy platform before the redesign.
The key design challenges were:
TO DO
Reduce anti-patterns and establish a design system
tech debtDesign Bug
Support horizontal and portrait videos
new features
Enable the web platform on desktop and mobile
new features
Make news easier to browse
user feedback
Reduce visual clutter when watching stories
user feedback
Fix unclear visual communication
user feedback
SOLUTION
Design System
Figma files
flowchart TB
foundations["fa:fa-layer-group Core Library: Colors, Types, Styles, Icons, States, Brand"]
web["fa:fa-globe Web Components Library"]
app["fa:fa-mobile-screen-button App Components Library"]
web_mobile["fa:fa-mobile-screen Web Mobile: Portrait, Landscape"]
web_desktop["fa:fa-desktop Web Desktop: Responsive, monitor sizes..."]
app_ios["fab:fa-apple App iOS: Ipad, iPhone, Portrait, Landscape, ..."]
app_android["fab:fa-android App Android: Samsung, Motorola, Tablet, Portrait, Landscape..."]
testing_ideas["fa:fa-flask LAB: User testing, navigable prototype, ideas, presentations..."]
foundations --> web
foundations --> app
web --> web_mobile
web --> web_desktop
app --> app_ios
app --> app_android
web --> testing_ideas
app --> testing_ideas
classDef layer fill:#ffffff,stroke:#7b7770,color:#1f1e1a,stroke-width:1px;
class foundations,web,app,web_mobile,web_desktop,app_ios,app_android,testing_ideas layer;
This Figma structure made the system much easier to design with day to day, keeping production work consistent, organized and easier to scale while leaving room for exploration in a separate LAB. Once it was fully in place, team velocity doubled.
Dynamic layout
Most video platforms still split vertical and horizontal browsing. I created a dynamic layout that unifies both. Please test it below: switch devices, shuffle scenarios, change story position, and try to break it!
Grid + Carousel PlaygroundShuffle scenarios, switch devices, and test how 16:9 and 9:16 videos behave across layouts.
Carousel
Grid
Carousel
Grid
From there, I focused the browsing experience on two core components, Grid and Carousel, which could scale cleanly from the app to mobile web and desktop web.
News card anatomy
The structure is directly related to the main questions of journalism:
What,
Where,
Who and
When.
This structure speeds up browsing news.
RESULTS
2xFaster development deliveries after Design System
100%Unified interface for vertical & horizontal reading
“I had the pleasure of working with Maycon on UI/UX, and I highly recommend him. He has a sharp eye for clean, modern visual design and a strong instinct for user-centered layout and flow. His ability to take feedback—not just accept it, but actively improve on it with thoughtful iteration—sets him apart.”
Modernized public services for citizens of Osasco, Brazil.
Problem
Describe the context, business, and product background for this case.
Describe the main challenge or problem that needed to be solved.
Solution
Describe the final solution and key features.
Results
XX%
Key metric
XX
Another metric
Add a client or stakeholder quote validating the outcome.
Case Study · CSAT
Non-deterministic CSAT
Role
Service Designer
Team
Backend Developer, Customer Success Manager (CSM)
PROBLEM
I co-founded Materialize in 2019, building an 'Airbnb for remote tech talent'. Selected by Endeavor Scale-Up and Microsoft for Startups, we ran a B2B marketplace where companies bought hour credits to book software engineers and other tech roles online.
By 2023, we surpassed half a million bookings, but this scale left us with limited visibility into the quality of online sessions.
“
CSAT response rates were too low. Only 8% of all buyers who booked responded to the CSAT survey.
To diagnose this issue raised by the CSM, I mapped the end-to-end feedback journey using a Service Blueprint.
09:41
MON 14
On a scale of 0 to 5, how satisfied were you with your session?
10:09
FRI 18
On a scale of 0 to 5, how satisfied were you with your session?
14:30
WED 16
On a scale of 0 to 5, how satisfied were you with your session?
Seller
Stay online and delivers work during session
Buyer
Receives CSAT survey: "On a scale of 0 to 5, how satisfied were you?"
Friction
Click/Taps Ignore or Answer — most ignore, some answer with external form.
Buyer
Receives targeted outreach for support or account growth
Line of Visibility
Frontstage (Visible to User)
Platform
Sends booking confirmation & reminders
Platform
Tracks session duration & logs hours
Platform
Survey appears on user’s device
Friction
Redirects to external form (Microsoft Forms)
CSM
Engages at-risk accounts & identifies upsell
Line of Internal Interaction
Backstage (Internal Processes)
Platform
Matches buyer ↔ seller & schedules
CSM
Monitors active accounts
Platform
Automation fires CSAT survey across channels
Gap
Score stored — low qualitative data
CSM
Manual triage for churn mitigation & expansion
Metric (Funnel conversion)
100%Confirmed bookings
92%Seller show-up
78%Buyer viewed CSAT
8%Response CSATOnly 30% leave comments
6.9%CSM InterventionInsufficient data to act
Average time
24-48hBefore meeting
1hMeeting
+30mPost-call
<24hTriage
24-48hFollow-up
Hypothesis: 78% of buyers saw the survey, but only 8% replied — a 70-point drop on a single screen. The number-scale question was the prime suspect.
SOLUTION
FIRST EXPERIMENT
Would a humanized conversation yield more responses?
Current
“On a scale of 0 to 5, how satisfied were you?”
8% replied
New
“Hey, how was your session?”
40% replied
We took a sample of buyers who had viewed the standard CSAT form but hadn't responded, and sent them a conversational message via WhatsApp.
That 40% came from a pilot on buyers who had already opted in to WhatsApp contact — the warmest segment we could test against. When we rolled the conversational format out to the full base, response settled at 24%: lower than the pilot, but still 3× the 8% baseline — and now sustained across the entire customer population, not a curated subset.
SECOND EXPERIMENT
OK, replies jumped 3×. But now we have thousands of free-text answers and no score to plot. Can AI turn a conversation into a CSAT score?
I distilled five key references directly into the system instruction, then enforced a structured JSON output (score, category, justification). Almost immediately, meaningful results began to surface.
Applied Book Insights
Reichheld, F. F. & Markey, R. (2011). The Ultimate Question 2.0. Harvard Business Review Press.
Dixon, M., Toman, N. & DeLisi, R. (2013). The Effortless Experience. Portfolio/Penguin.
Hayes, B. E. (2008). Measuring Customer Satisfaction and Loyalty. ASQ Quality Press.
Oliver, R. L. (1997). Satisfaction: A Behavioral Perspective on the Consumer. McGraw-Hill.
Parasuraman, A., Zeithaml, V. A. & Berry, L. L. (1990). Delivering Quality Service. Free Press.
By embedding real academic references, we established a testable baseline. Still, taking these generated scores as absolute truth would be naive.
THIRD EXPERIMENT
Books gave us a framework. But would the model agree with real customers? Can AI infer a CSAT score from text alone?
We calibrated the AI on 40,950 real Brazilian e-commerce reviews from the Olist Sentiment dataset (CC BY 4.0) — each one a piece of text paired with a real customer score.
The prompt applies NPS, CES, SERVQUAL, Oliver's Disconfirmation, and CSAT frameworks, enriched with statistical patterns and calibration examples mined from the ground truth. Try it below — type any customer feedback and see how the AI infers a CSAT score from text with no numeric rating.
↓ Try it live
RESULTS
3×CSAT response rate8% → 24% · sustained over the first quarter post-rollout
100%Qualitative coveragevs <30% before · the 0–5 question was retired, so every reply is now a free-text answer scored by the prompt
−16%Churn reductioncumulative over the 3 months following rollout · attributed to earlier CSM intervention enabled by richer signal
“His true strength lies in deconstructing a problem from the ground up, and his best solutions are rooted in simplicity: reducing steps and screens.”
