UX / PRODUCT DESIGN
Research. Strategy. Systems Design. AI.
An innovator who adapts & delivers. I design products that help people understand and trust systems they can't fully see — from machine vision overlays to GPS-connected hardware. That's been my work for over two decades. AI just made it more interesting. (See my AI design process.)
Machine Vision
Wearable
AI • AGEnts
22
YEARS EXPERIENCE
3
TECHNOLOGY COMPANIES
Multiple
PATENTS FILED/GRANTED
01
Selected Work
Case Studies
Global Trend Engine
Designer & Builder
•
Self-Initiated
•
1 week
→
An agentic AI dashboard where eight named agents scan the web for frontier signals and synthesize a predictive convergence insight — designed, built, and deployed with Claude.
Lytx Video Overlay
Senior UX Designer
•
Lytx
•
4 months
→
A dynamic video overlay that simplifies customer coaching conversations, improving user trust, and reducing contention rate to near zero.
Lytx Driver ID
Senior UX Designer
•
Lytx
•
3 months
→
A systematic user flow for assignment, distribution, and usage of QR codes to assign drivers to vehicles.
Timex Ironman ONE GPS+
UX Design Lead
•
Qualcomm / Timex
•
3 years
→
A full 0-to-1 product experience for athletes who wanted to track workouts, stay connected, and leave their phones behind.
Tagg the Pet Tracker
UX Design & Product Management
•
Qualcomm
•
1.5 years
→
Redesign of a pet activity monitoring and management of iOS/Android app development as both UX lead and product manager.
FLO TV Personal Television
UX Design Lead
•
Qualcomm / FLO TV
•
1 year
→
Designing a new product category from the ground up: live mobile television.
02
Expertise
Skills
User Research
Interviews, usability tests, ethnographic study, and contextual inquiry
Journey Mapping
End-to-end experience mapping across touchpoints
Interaction Design
Flows, wireframes, use cases, and high-fidelity mockups
Storytelling
Communicating design decisions to executives and cross-functional teams
Systems Thinking
Mapping connected flows and designing for scalability across surfaces
Prototyping
From low-fi click-throughs to high-fidelity AI coding
AI Fluency
Designing AI-powered experiences and using AI tools in the design process
Stakeholder Management
Cross-functional collaboration and design advocacy
Tools
Claude (Design/Code)
Research synthesis, design, prototyping, and documentation
Figma
Components, variants, auto-layout, and prototyping
Sketch
Vector UI design for components and high-fidelity screens
Axure RP
High-fidelity prototyping with conditional logic
Pendo
In-app guidance, feature tracking, and user surveys
Amplitude
Funnels, retention, and feature-adoption analysis
Dovetail
Centralized research insights and customer intelligence
Atlassian (Confluence/Jira)
Confluence for design documentation; Jira for planning and cross-functional tracking
03
Background
Experience & Education
2019 - Present
Senior Product Designer
Lytx • San Diego, CA
Research and design of user experience for video-safety and AI products, and development of an AI-native design process for the Product/UX team.
2007 - 2018
Sr. Staff UX Designer & Sr. Product Manager
Qualcomm • San Diego, CA
Led 0-to-1 UX and product development for large-scale product start-ups while managing 3rd-party design teams.
2003 - 2007
UI Designer
Nokia • San Diego, CA
Designed new phone features while serving as the only North American member of Nokia's global design-management team.
1998 - 2002
B.S. Symbolic Systems
Stanford University • Stanford, CA
Interdisciplinary study of computer science, linguistics, philosophy, and psychology with a concentration in human-computer interaction.
My Résumé
Name
Daniel Rivas
current role
Senior Product Designer
Location
San Diego, CA
Availability
Daily Futurology Report
July 16, 2026 at 7:10:00 AM
Model:
Opus 4.8
Forecast:
2026–2028
The mind goes cheap, the body goes to war — the frontier's next battle is fought over electrons, oil straits and cooling, not models
Within 12–24 months, expect the decisive frontier contest to move from software to substrate: whoever controls firm power, secure energy corridors and physical hardware sets the pace, while models themselves keep commoditizing.
The evidence is already converging. A week after the July 9 three-lab cluster — with Fable 5 back and agents in production — the market rewards fit and price over supremacy, signaling that intelligence is abundant. Meanwhile the physical layer turns scarce and contested: a $145B nuclear pipeline and a microreactor going critical, 120-year heat records and a record-hot ocean straining grids, and US strikes on 90 Iranian targets reclosing the Strait of Hormuz that carries a fifth of the world's oil.
The likeliest inflection is that firm power and secure corridors — not chips or model weights — become the true moat of the frontier, and the firms and states that lock down electrons, cooling and straits will gate who gets to scale intelligence at all. Compute's appetite collides head-on with a hot planet and a fracturing geopolitics of energy.
Pulling the other way is the month's sharpest counter-signal: preference for AI content has collapsed to 26% from 60%, and 'proof of human' is being priced as the premium — the more the machine layer commoditizes, the more visible human authenticity is worth. And medicine advances on an independent clock, with a bespoke in-vivo CRISPR therapy built in six months and editing reaching toward common cardiovascular disease.
Cross-Domain Synthesis
Yesterday's scan read the frontier as verticalizing — capital converting each state-built gate into a private turnstile across models, electrons and orbit. Today the binding constraint moves one layer deeper: from institutions to physics. Intelligence has gone abundant; the contested layer is now the physical substrate that powers, cools and carries it.
At the machine layer, July's verdict is commoditization. A week after three labs shipped within hours on July 9 and Claude Fable 5 returned, the market prizes price, speed and fit over raw supremacy, and agents crossed into production — cognition is cheap and getting cheaper.
At the physical layer, everything is scarce and fought over. A $145B, 40-year nuclear pipeline and a microreactor going critical show firm power, not chips, as the real moat; 120-year US heat records and a record-hot ocean strain the very grids the buildout depends on; and US strikes on 90 Iranian targets reclose the Strait of Hormuz, repricing the oil that underwrites it. Even orbit waits on hardware, with Starship Flight 13 and Artemis III's private landers as the pacing items.
Against the machine layer runs a human counter-current — preference for AI content collapsing to 26% as culture prices 'proof of human' — while gene editing matures on its own clock, delivering a bespoke in-vivo CRISPR therapy in six months and pushing toward common cardiovascular disease.
05
Horizon: Predictive convergence
Futurology Report — Daily
July 16, 2026 at 7:10:00 AM
AI Model:
Opus 4.8
Forecast:
2026–2028
The mind goes cheap, the body goes to war — the frontier's next battle is fought over electrons, oil straits and cooling, not models
Within 12–24 months, expect the decisive frontier contest to move from software to substrate: whoever controls firm power, secure energy corridors and physical hardware sets the pace, while models themselves keep commoditizing.
The evidence is already converging. A week after the July 9 three-lab cluster — with Fable 5 back and agents in production — the market rewards fit and price over supremacy, signaling that intelligence is abundant. Meanwhile the physical layer turns scarce and contested: a $145B nuclear pipeline and a microreactor going critical, 120-year heat records and a record-hot ocean straining grids, and US strikes on 90 Iranian targets reclosing the Strait of Hormuz that carries a fifth of the world's oil.
The likeliest inflection is that firm power and secure corridors — not chips or model weights — become the true moat of the frontier, and the firms and states that lock down electrons, cooling and straits will gate who gets to scale intelligence at all. Compute's appetite collides head-on with a hot planet and a fracturing geopolitics of energy.
Pulling the other way is the month's sharpest counter-signal: preference for AI content has collapsed to 26% from 60%, and 'proof of human' is being priced as the premium — the more the machine layer commoditizes, the more visible human authenticity is worth. And medicine advances on an independent clock, with a bespoke in-vivo CRISPR therapy built in six months and editing reaching toward common cardiovascular disease.
Signal Intensity
A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.
AI
92
%
Climate
85
%
BIOTECH
58
%
GEOPOLITICS
88
%
ENERGY
93
%
SOCIETY
62
%
SPACE
70
%
Cross-Domain Synthesis
Yesterday's scan read the frontier as verticalizing — capital converting each state-built gate into a private turnstile across models, electrons and orbit. Today the binding constraint moves one layer deeper: from institutions to physics. Intelligence has gone abundant; the contested layer is now the physical substrate that powers, cools and carries it.
At the machine layer, July's verdict is commoditization. A week after three labs shipped within hours on July 9 and Claude Fable 5 returned, the market prizes price, speed and fit over raw supremacy, and agents crossed into production — cognition is cheap and getting cheaper.
At the physical layer, everything is scarce and fought over. A $145B, 40-year nuclear pipeline and a microreactor going critical show firm power, not chips, as the real moat; 120-year US heat records and a record-hot ocean strain the very grids the buildout depends on; and US strikes on 90 Iranian targets reclose the Strait of Hormuz, repricing the oil that underwrites it. Even orbit waits on hardware, with Starship Flight 13 and Artemis III's private landers as the pacing items.
Against the machine layer runs a human counter-current — preference for AI content collapsing to 26% as culture prices 'proof of human' — while gene editing matures on its own clock, delivering a bespoke in-vivo CRISPR therapy in six months and pushing toward common cardiovascular disease.
ABOUT ME
Design Philosophy
I bring order to complexity; I've spent over two decades building the tools to do it well.
My path started at Stanford, where a degree in Symbolic Systems gave me something most designers don't have: a foundation that spans both sides of the human-computer divide. From the technical rigor of computer science and formal logic, to the human depth of cognitive psychology and knowledge representation, I learned to hold both perspectives at once and to design from the intersection.
That training became practice at Nokia, Qualcomm, and now Lytx, companies where the problems are large, the systems are complex, and the stakes are real. I've learned that the most important design decisions rarely live on a single screen. They live in the architecture, the mental models, the moments where a user either trusts the product or doesn't.
What drives me today is the challenge of making emerging technology feel human and trustworthy. AI systems can process the world faster than any person, but they still need to communicate their reasoning, surface the right information at the right moment, and earn the confidence of the people who depend on them. That translation problem, from machine intelligence to human understanding, is exactly the kind of complexity I've been working on.
Systems before screens
Every interface is a surface on top of a system. Understanding the system (the data flows, the user mental models, the organizational constraints) is what separates design that scales from design that just looks good in a mockup.
Strategy and execution, not one or the other
I connect design decisions to business outcomes. That means being in the room when strategy is set, not just when wireframes need approval. It means being able to move between the 30,000-foot view and the pixel-level detail without losing either.
Trustworthy by design
The best technology earns trust before it demands it. Whether I'm designing a safety-critical AI product or the home screen on a fitness watch, I start with the question: what does this person need to feel confident taking action?
EDUCATION
B.S. Symbolic Systems
Stanford University
Concentration in HCI
BASED IN
San Diego, CA
CURRENTLY
Senior Product Designer
Lytx
OPEN TO OPPORTUNITIES
Principal/Senior-Level Product Design Roles
In San Diego or Remote
SELECTED WORK
Case Studies
EXPERTISE
Skills
User Research
Interviews, usability tests, ethnographic study, and contextual inquiry
Journey Mapping
End-to-end experience mapping across touchpoints
Interaction Design
Flows, wireframes, use cases, and high-fidelity mockups
Storytelling
Communicating design decisions to executives, stakeholders, and cross-functional teams
Systems Thinking
Mapping connected flows and designing for scalability across product surfaces
Prototyping
Interactive prototypes from low-fi click-throughs to high-fidelity AI coding
AI Fluency
Designing AI-powered experiences and leveraging AI tools in the design process
Stakeholder Management
Cross-functional collaboration and design advocacy
Tools
Pendo
In-app guidance, feature tracking, and user surveys to inform design decisions
Dovetail
Centralized research insights, tagged findings, and shared customer intelligence repository
Figma
Components, variants, auto-layout, and prototyping
Claude (Design & Code)
AI-assisted research synthesis, design critique, content generation, and prototyping
Amplitude
Product funnels, retention curves, and feature adoption to identify usage and priorities
Gong
Customer interview repository for surfacing pain points, testing designs, and grounding decisions
Sketch
Vector-based UI design for components, wireframes, and high-fidelity screens
Axure RP
High-fidelity interactive prototyping with conditional logic and complex flows
Cursor
AI-assisted coding for rapid prototyping and exploring technical feasibility
BACKGROUND
Experience & Education
Senior Product Designer
Lytx · San Diego, CA
Researched and designed user experience for video safety and AI products, and developed an AI-native design process for the UX team.
tagsContainer
2019 - Present
Sr. Staff UX Designer & Sr. Product Manager
Qualcomm · San Diego, CA
Led 0-to-1 UX and product development for large-scale product start-ups while managing 3rd-party design teams.
tagsContainer
2007 - 2018
UI Designer
Nokia · San Diego, CA
Designed new phone features while serving as the only North American member of Nokia's global design management team.
tagsContainer
2003 - 2007
B.S. Symbolic Systems
Completed interdisciplinary study of computer science, linguistics, philosophy, and psychology with a concentration in human-computer interaction.
tagsContainer
1998 - 2002
My Résumé
A full overview of my experience, skills, and education — ready to share.
NAME
Daniel Rivas
CURRENT ROLE
Senior Product Designer
LOCATION
San Diego, CA
EXPERIENCE
22 years
AVAILABILITY
✦ Human · Machine · Intelligence ✦ Systems before screens ✦ Strategy & execution ✦ Trustworthy by design ✦
Design Philosophy
06
ABOUT ME
I bring order to complexity; I've spent over two decades building the tools to do it well.
My path started at Stanford, where a degree in Symbolic Systems gave me something most designers don't have: a foundation that spans both sides of the human-computer divide. From the technical rigor of computer science and formal logic, to the human depth of cognitive psychology and knowledge representation, I learned to hold both perspectives at once and to design from the intersection.
That training became practice at Nokia, Qualcomm, and now Lytx, companies where the problems are large, the systems are complex, and the stakes are real. I've learned that the most important design decisions rarely live on a single screen. They live in the architecture, the mental models, the moments where a user either trusts the product or doesn't.
What drives me today is the challenge of making emerging technology feel human and trustworthy. AI systems can process the world faster than any person, but they still need to communicate their reasoning, surface the right information at the right moment, and earn the confidence of the people who depend on them. That translation problem, from machine intelligence to human understanding, is exactly the kind of complexity I've been working on.
The surface
The Model
Every interface is a surface on top of a system.
The screen is the visible tip. The decisions that make a product trustworthy live underneath it — in the flows, the mental models, the constraints. That's where I start.
Screen / Interface
What the user sees
User mental models & needs
01
Interaction & info architecture
02
Data flows & system states
03
Organizational constraints
04
↓ Where the design decisions live
A
Systems before screens
Every interface is a surface on top of a system. Understanding the data flows, mental models, and organizational constraints is what separates design that scales from design that just looks good in a mockup.
B
Strategy and execution
I connect design decisions to business outcomes — being in the room when strategy is set, moving between the 30,000-foot view and the pixel-level detail without losing either.
C
Trustworthy by design
The best technology earns trust before it demands it. Whether a safety-critical AI product or a fitness-watch home screen, I start with: what does this person need to feel confident taking action?
Education
B.S. Symbolic Systems
Stanford University • Concentration in HCI
Based In
San Diego, CA
Available for remote
Currently
Senior Product Designer
Lytx, Inc.
Open To
Principal / Lead / Senior roles
San Diego or remote
07
Contact
Have a project in mind?
I'm open to new full-time opportunities, collaborations, and interesting conversations.
Phone
Daniel Rivas · UX Strategy & Product Design
© 2026