UX STRATEGY • PRODUCT DESIGN
Research. Strategy. Systems Design. AI.
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 how I'm integrating AI into my 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 three agents — a multi-persona scanner, Nostradamus, and Tarot — scan the web for frontier signals, synthesize patterns, and generate predictive convergence insights — 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
September 25, 2026 at 12:48:00 AM
Model:
Opus 4.8
Forecast:
2026–2028
22 nations launch a UN 'Call for Control of Frontier AI' — pointedly without the US or China — the same week Altman briefs the Security Council for a speed limit, as the rare-earth cliff holds for Nov 10, a near-certain El Niño aims past every modern record, a 417-3 House vote shields ratepayers from data-center power costs, and Google's first orbital AI chips launch Oct 1. Through 2028 the binding constraints are governance, minerals, power and consent — not model capability.
Here's the bet through 2028: the models were never the constraint, and this fall keeps proving it. What's scarce is everything around them — the minerals to build the machines, the power to run them, the public's patience for hosting either, and the political agreement to govern any of it. This week that last one cracked into view. Twenty-two nations asked for global AI rules, and the two countries that build the frontier declined the invitation.
The evidence is on the calendar, not in a mood. A rare-earth suspension that lapses November 10. A frontier-AI oversight call with the US and China conspicuously outside it. A data-center power shortfall so real that Texas stopped connecting new load and the House voted 417-3 to protect ratepayers. An El Niño the WMO now calls near-certain and possibly the biggest in a thousand years, forecast to peak near a record in November. Half a dozen separate clocks, all bunched into one autumn.
I'd watch October into December hardest. That's when the rare-earth cliff either lapses or gets waved off at a Trump-Xi table, when El Niño peaks and starts breaking whatever it's going to break, when Google's first chips either survive orbit or don't, and when the UN's new coalition either grows teeth or stays a press release the two big players ignored. A lot of bets settle in the same eight weeks, and given the year, I wouldn't put the whole board on the calm outcome.
Worth holding loosely, though. A deadline is a negotiation, not a wall — the rare-earth freeze already got extended once, and a 22-nation declaration without Washington or Beijing is a long way from a rule anyone enforces. The likeliest real outcome isn't a cliff; it's slippage — everything a little slower, a little more gas-fired, a little stranger than the market has priced. And the development I keep circling back to isn't on the countdown at all: this fall a gene edit inside a living body cut people's cholesterol in half, while everyone else was staring at the clocks.
Cross-Domain Synthesis
This week 22 countries stood up at the UN and asked for a referee on frontier AI. The interesting part isn't the ask — it's the guest list. The US and China, the two countries that actually build the frontier models, didn't sign. So you've got a coalition of the willing forming around a table the two players who matter didn't show up to. Two days later Sam Altman walked into the Security Council and said OpenAI would slow down. The builders want brakes; the governments that house them can't agree on who holds the pedal.
Underneath the governance drama, the physical stuff keeps setting the actual deadlines. China's rare-earth freeze lasts only until November 10, and the chip inputs everyone needs now clear one license at a time. The power layer is worse: US data centers are pulling toward 76 gigawatts this year, Texas has quietly stopped taking new grid connections, and more than half of that power is still fossil. Nobody's building reactors fast enough, so the marginal watt is gas.
And people have noticed the bill. The US House — which agrees on almost nothing — voted 417 to 3 to stop data centers from dumping their power costs onto everyone else's electric bill. That's not a fringe worry anymore; that's Congress. Meanwhile the escape hatch stopped being a slide deck: on October 1 Google is putting four of its AI chips into orbit to see if compute can just run where the sun never sets. Funded, filed, and now actually flying.
The thing that ignores all of it is biology. A Cleveland Clinic trial edited a gene inside living patients and cut their bad cholesterol in half a year later, and the FDA just took Intellia's in-body CRISPR drug in for review. No cliff, no vote, no summit — just a quiet line of results walking from rare diseases toward the conditions everybody has. The loudest clocks this fall are the ones with deadlines. The one that may matter most doesn't have one.
05
Horizon: Predictive convergence
Futurology Report — Daily
September 25, 2026 at 12:48:00 AM
AI Model:
Opus 4.8
Forecast:
2026–2028
22 nations launch a UN 'Call for Control of Frontier AI' — pointedly without the US or China — the same week Altman briefs the Security Council for a speed limit, as the rare-earth cliff holds for Nov 10, a near-certain El Niño aims past every modern record, a 417-3 House vote shields ratepayers from data-center power costs, and Google's first orbital AI chips launch Oct 1. Through 2028 the binding constraints are governance, minerals, power and consent — not model capability.
Here's the bet through 2028: the models were never the constraint, and this fall keeps proving it. What's scarce is everything around them — the minerals to build the machines, the power to run them, the public's patience for hosting either, and the political agreement to govern any of it. This week that last one cracked into view. Twenty-two nations asked for global AI rules, and the two countries that build the frontier declined the invitation.
The evidence is on the calendar, not in a mood. A rare-earth suspension that lapses November 10. A frontier-AI oversight call with the US and China conspicuously outside it. A data-center power shortfall so real that Texas stopped connecting new load and the House voted 417-3 to protect ratepayers. An El Niño the WMO now calls near-certain and possibly the biggest in a thousand years, forecast to peak near a record in November. Half a dozen separate clocks, all bunched into one autumn.
I'd watch October into December hardest. That's when the rare-earth cliff either lapses or gets waved off at a Trump-Xi table, when El Niño peaks and starts breaking whatever it's going to break, when Google's first chips either survive orbit or don't, and when the UN's new coalition either grows teeth or stays a press release the two big players ignored. A lot of bets settle in the same eight weeks, and given the year, I wouldn't put the whole board on the calm outcome.
Worth holding loosely, though. A deadline is a negotiation, not a wall — the rare-earth freeze already got extended once, and a 22-nation declaration without Washington or Beijing is a long way from a rule anyone enforces. The likeliest real outcome isn't a cliff; it's slippage — everything a little slower, a little more gas-fired, a little stranger than the market has priced. And the development I keep circling back to isn't on the countdown at all: this fall a gene edit inside a living body cut people's cholesterol in half, while everyone else was staring at the clocks.
Signal Intensity
A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.
AI
96
%
Climate
95
%
BIOTECH
68
%
GEOPOLITICS
82
%
ENERGY
95
%
SOCIETY
88
%
SPACE
66
%
Cross-Domain Synthesis
This week 22 countries stood up at the UN and asked for a referee on frontier AI. The interesting part isn't the ask — it's the guest list. The US and China, the two countries that actually build the frontier models, didn't sign. So you've got a coalition of the willing forming around a table the two players who matter didn't show up to. Two days later Sam Altman walked into the Security Council and said OpenAI would slow down. The builders want brakes; the governments that house them can't agree on who holds the pedal.
Underneath the governance drama, the physical stuff keeps setting the actual deadlines. China's rare-earth freeze lasts only until November 10, and the chip inputs everyone needs now clear one license at a time. The power layer is worse: US data centers are pulling toward 76 gigawatts this year, Texas has quietly stopped taking new grid connections, and more than half of that power is still fossil. Nobody's building reactors fast enough, so the marginal watt is gas.
And people have noticed the bill. The US House — which agrees on almost nothing — voted 417 to 3 to stop data centers from dumping their power costs onto everyone else's electric bill. That's not a fringe worry anymore; that's Congress. Meanwhile the escape hatch stopped being a slide deck: on October 1 Google is putting four of its AI chips into orbit to see if compute can just run where the sun never sets. Funded, filed, and now actually flying.
The thing that ignores all of it is biology. A Cleveland Clinic trial edited a gene inside living patients and cut their bad cholesterol in half a year later, and the FDA just took Intellia's in-body CRISPR drug in for review. No cliff, no vote, no summit — just a quiet line of results walking from rare diseases toward the conditions everybody has. The loudest clocks this fall are the ones with deadlines. The one that may matter most doesn't have one.
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