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 6, 2026 at 1:49:48 AM
Model:
Opus 4.8
Forecast:
2026–2028
Capability is cheap; its foundations are dated: GPT-6 Astra doubles the field on ARC-AGI-3 as four flagships ship in 72 hours, yet PJM runs a first-ever September backstop auction, China's rare-earth rule is armed for a November 10 deadline, utilities book record rate hikes as data centers become the midterms' 'September Surprise,' and NOAA says the El Niño turns record-strong this month — even as Intellia's in-body CRISPR clears Phase 3. Through 2028 the binding constraint is power, minerals and consent, not intelligence.
Here's the bet through 2028. The AI question isn't “how smart” anymore — that got answered, and the answer is cheap. It's whether the industry can physically build what the models run on, secure the inputs, and keep the public onside before a stack of deadlines lands at once. Concrete and consent, not IQ.
The receipts came the same week. Four flagships in three days, Astra doubling the field on the one benchmark that isn't saturated. PJM short enough to call an emergency auction. China's mineral rules armed and dated to November 10. A record $31 billion in rate hikes while data centers turn into a midterm liability, with well over $100 billion of projects already stalled. Every one of those is a clock, and most of them read this fall.
I'd watch September through next spring hardest. That's when PJM finds out whether the money buys real megawatts or just shoves the shortfall to 2028, when Beijing decides whether to let the November rule actually bite, when the El Niño peaks and starts breaking what it's forecast to break, and when Starcloud either flies Blackwell in October like it promised or quietly slips the date. The capability curve climbs the whole time. It's just not the line that matters.
Worth holding this loosely, though. Cheap money is very good at conjuring power nobody modeled — a reactor restart, gas behind the meter, a deal that never touches the auction. Intellia clearing Phase 3 is a reminder the boring, durable wins can arrive faster than the scary ones. And public anger cools quickly if the disruption stays dull — which it mostly has, right up until the bill lands. The fences are real and going up. That's not the buildout stopping; it's the buildout getting slower, weirder and pricier than the market's pricing in.
Cross-Domain Synthesis
The tell this week wasn't a score. GPT-6 Astra doubled the best rival on ARC-AGI-3 and near-solved FrontierMath — the fourth flagship to ship in 72 hours, after Fable 5.1, Gemini 3.8 Flash and Muse Spark 1.3 — and the people who noticed were mostly the ones adjusting their API bills. When a top model lands every couple of days, “how smart” stops being the question worth asking. The question is whether the world can supply what the smart thing eats, and whether the neighbors keep letting it eat.
Power's the hardest wall. PJM — the grid for about 65 million people — came up short again and is running its first-ever September backstop auction just to find dedicated generation for data centers; capacity cleared the cap a third straight year, and without the collar it'd have run 71% higher. The hyperscalers' answer is to stop asking the grid: nearly ten gigawatts of nuclear signed. Except almost none of that steel is hot. The first restart doesn't feed a server until 2027.
The inputs and the neighbors are tightening on the same clock. China's rare-earth suspension runs out November 10, and the quiet stuff — detentions, a new reporting mechanism — says the pause is a countdown, not a reprieve. Meanwhile the neighbors found the number that turns a zoning fight into a campaign: the electric bill. A record $31 billion in hikes, rates up double digits in some states, and data centers are suddenly the “September Surprise” of the midterms.
Two things this week don't file paperwork. NOAA now thinks the El Niño becomes the strongest ever measured — records set this month, not next year — peaking through winter no matter what any auction clears. And in the clinic, Intellia's one-shot CRISPR cut angioedema attacks 87% and became the first in-body edit to clear Phase 3. One breaks things on a physical clock; the other fixes them on a regulatory one. Neither is waiting in an interconnection queue.
So the next couple of years don't look like a leaderboard. They look like a wall of due dates — PJM this month, China in November, the El Niño peak this winter, the orbital data centers nobody's really flown pushed to 2027. The models get cheaper and better the whole way through. That just stopped being the thing that decides anything.
05
Horizon: Predictive convergence
Futurology Report — Daily
September 6, 2026 at 1:49:48 AM
AI Model:
Opus 4.8
Forecast:
2026–2028
Capability is cheap; its foundations are dated: GPT-6 Astra doubles the field on ARC-AGI-3 as four flagships ship in 72 hours, yet PJM runs a first-ever September backstop auction, China's rare-earth rule is armed for a November 10 deadline, utilities book record rate hikes as data centers become the midterms' 'September Surprise,' and NOAA says the El Niño turns record-strong this month — even as Intellia's in-body CRISPR clears Phase 3. Through 2028 the binding constraint is power, minerals and consent, not intelligence.
Here's the bet through 2028. The AI question isn't “how smart” anymore — that got answered, and the answer is cheap. It's whether the industry can physically build what the models run on, secure the inputs, and keep the public onside before a stack of deadlines lands at once. Concrete and consent, not IQ.
The receipts came the same week. Four flagships in three days, Astra doubling the field on the one benchmark that isn't saturated. PJM short enough to call an emergency auction. China's mineral rules armed and dated to November 10. A record $31 billion in rate hikes while data centers turn into a midterm liability, with well over $100 billion of projects already stalled. Every one of those is a clock, and most of them read this fall.
I'd watch September through next spring hardest. That's when PJM finds out whether the money buys real megawatts or just shoves the shortfall to 2028, when Beijing decides whether to let the November rule actually bite, when the El Niño peaks and starts breaking what it's forecast to break, and when Starcloud either flies Blackwell in October like it promised or quietly slips the date. The capability curve climbs the whole time. It's just not the line that matters.
Worth holding this loosely, though. Cheap money is very good at conjuring power nobody modeled — a reactor restart, gas behind the meter, a deal that never touches the auction. Intellia clearing Phase 3 is a reminder the boring, durable wins can arrive faster than the scary ones. And public anger cools quickly if the disruption stays dull — which it mostly has, right up until the bill lands. The fences are real and going up. That's not the buildout stopping; it's the buildout getting slower, weirder and pricier than the market's pricing in.
Signal Intensity
A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.
AI
95
%
Climate
96
%
BIOTECH
71
%
GEOPOLITICS
84
%
ENERGY
96
%
SOCIETY
93
%
SPACE
66
%
Cross-Domain Synthesis
The tell this week wasn't a score. GPT-6 Astra doubled the best rival on ARC-AGI-3 and near-solved FrontierMath — the fourth flagship to ship in 72 hours, after Fable 5.1, Gemini 3.8 Flash and Muse Spark 1.3 — and the people who noticed were mostly the ones adjusting their API bills. When a top model lands every couple of days, “how smart” stops being the question worth asking. The question is whether the world can supply what the smart thing eats, and whether the neighbors keep letting it eat.
Power's the hardest wall. PJM — the grid for about 65 million people — came up short again and is running its first-ever September backstop auction just to find dedicated generation for data centers; capacity cleared the cap a third straight year, and without the collar it'd have run 71% higher. The hyperscalers' answer is to stop asking the grid: nearly ten gigawatts of nuclear signed. Except almost none of that steel is hot. The first restart doesn't feed a server until 2027.
The inputs and the neighbors are tightening on the same clock. China's rare-earth suspension runs out November 10, and the quiet stuff — detentions, a new reporting mechanism — says the pause is a countdown, not a reprieve. Meanwhile the neighbors found the number that turns a zoning fight into a campaign: the electric bill. A record $31 billion in hikes, rates up double digits in some states, and data centers are suddenly the “September Surprise” of the midterms.
Two things this week don't file paperwork. NOAA now thinks the El Niño becomes the strongest ever measured — records set this month, not next year — peaking through winter no matter what any auction clears. And in the clinic, Intellia's one-shot CRISPR cut angioedema attacks 87% and became the first in-body edit to clear Phase 3. One breaks things on a physical clock; the other fixes them on a regulatory one. Neither is waiting in an interconnection queue.
So the next couple of years don't look like a leaderboard. They look like a wall of due dates — PJM this month, China in November, the El Niño peak this winter, the orbital data centers nobody's really flown pushed to 2027. The models get cheaper and better the whole way through. That just stopped being the thing that decides anything.
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