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 16, 2026 at 1:30:00 AM
Model:
Opus 4.8
Forecast:
2026-2028
Four frontier models shipped in one long weekend while everything they need stayed rationed: US data centers hit 42 GW against a grid still more than half fossil, China's rare-earth cliff lands November 10, the hottest August ever measured with El Nino now >90% to go 'very strong,' the data-center backlash became a 'September surprise' heading into the midterms, and a one-time CRISPR infusion held a 52% LDL cut for a full year. Through 2028 the binding scarcities are power, minerals, and consent — not capability.
Here's the bet through 2028: the scarce thing was never the intelligence. It's power, minerals, and the patience of the people living next to all of it. Capability is abundant and getting cheaper — four frontier models in one long weekend at flat prices makes that case about as well as anything could. Everything the capability needs to actually matter is on a clock, and most of those clocks read this fall.
The receipts stacked up fast. Data centers at 42 gigawatts against a grid that's still more than half fossil, because gas is the only thing that builds in time. A rare-earth cliff on November 10 with no real sign anyone's ready for it. A backlash that went from local nuisance to midterm platform in a matter of weeks. Every one of those is a countdown, not a trend line — and a countdown resolves on a date whether or not the model is impressive.
I'd watch this fall into spring hardest. That's when the rare-earth suspension either lapses or gets waved off at the eleventh hour, when El Nino peaks and starts breaking the things it's forecast to break, when the gas behind the fence turns into poured concrete or stays a rendering, and when 'we put the agents into production' quietly resolves into either 'fine' or 'incident.' The leaderboard keeps climbing the whole way. It's just not the line I'd put money on.
Worth holding loosely, though. A fence going up isn't the buildout stopping — it's the buildout getting slower, weirder, and more fossil-fueled than the market has it priced. Moratoriums get negotiated. Rare-earth cliffs have a habit of getting extended at the last minute; one already did last October. And the thing I keep coming back to is that Cleveland CRISPR result — the least-hyped item on the whole board might be the one that ages best. The loud seams aren't always the ones that hold.
Cross-Domain Synthesis
Four frontier models landed in about 72 hours this month — Claude Fable 5.1, Gemini 3.8 Flash, a new Muse Spark, OpenAI's Astra — mostly at flat prices. That's roughly the fifth time this year the intelligence showed up right on schedule. So the interesting question stopped being whether the models keep coming. It's whether anything they touch can keep up. This month the answer kept coming back: not really.
Start with the outlet. US data centers are pulling 42 gigawatts now, up from 23 two years ago, and utilities are quietly drawing their load curves toward 75. The grid can't build that fast, so the marginal AI watt is a gas turbine — you can stand one up in a year, versus the better part of a decade for the nuclear everyone keeps announcing. The tell is in the mix: something like 90 gigawatts of new capacity slated for 2026, but only about 1.7 of it net new gas on the public grid, because the gas that actually matters is going in behind the fence, next to the servers, off the books.
Then the neighbors noticed. The data-center fight jumped from zoning boards to a 'September surprise' — moratoriums, projects worth north of $130 billion blocked or delayed in the first quarter alone, seven in ten Americans telling Gallup they don't want one nearby, and candidates in both parties suddenly running on it into the midterms. Consent turns out to be a resource too, and it's the one that compounds slowest. Upstream of all of it sits a hard date: China's rare-earth suspension lapses November 10, six months of watching hasn't shown anyone actually getting ready, and Beijing spent the summer adding names to the list.
And then two things that never filed for a permit. The Pacific has been at record warmth for months, and as of the September 10 update the forecasters put this El Nino better than 90% to go 'very strong' and 75% to become the strongest since we started keeping the record — a winter that arrives on physics' calendar, not the interconnection queue's. Meanwhile, in a quiet corner of Cleveland, a single CRISPR infusion cut people's LDL in half and held it there for a full year. One is going to break weather; the other quietly mends hearts. Neither needed a leaderboard, which is worth remembering the next time the loudest seam and the one that actually matters turn out not to be the same seam.
05
Horizon: Predictive convergence
Futurology Report — Daily
September 16, 2026 at 1:30:00 AM
AI Model:
Opus 4.8
Forecast:
2026-2028
Four frontier models shipped in one long weekend while everything they need stayed rationed: US data centers hit 42 GW against a grid still more than half fossil, China's rare-earth cliff lands November 10, the hottest August ever measured with El Nino now >90% to go 'very strong,' the data-center backlash became a 'September surprise' heading into the midterms, and a one-time CRISPR infusion held a 52% LDL cut for a full year. Through 2028 the binding scarcities are power, minerals, and consent — not capability.
Here's the bet through 2028: the scarce thing was never the intelligence. It's power, minerals, and the patience of the people living next to all of it. Capability is abundant and getting cheaper — four frontier models in one long weekend at flat prices makes that case about as well as anything could. Everything the capability needs to actually matter is on a clock, and most of those clocks read this fall.
The receipts stacked up fast. Data centers at 42 gigawatts against a grid that's still more than half fossil, because gas is the only thing that builds in time. A rare-earth cliff on November 10 with no real sign anyone's ready for it. A backlash that went from local nuisance to midterm platform in a matter of weeks. Every one of those is a countdown, not a trend line — and a countdown resolves on a date whether or not the model is impressive.
I'd watch this fall into spring hardest. That's when the rare-earth suspension either lapses or gets waved off at the eleventh hour, when El Nino peaks and starts breaking the things it's forecast to break, when the gas behind the fence turns into poured concrete or stays a rendering, and when 'we put the agents into production' quietly resolves into either 'fine' or 'incident.' The leaderboard keeps climbing the whole way. It's just not the line I'd put money on.
Worth holding loosely, though. A fence going up isn't the buildout stopping — it's the buildout getting slower, weirder, and more fossil-fueled than the market has it priced. Moratoriums get negotiated. Rare-earth cliffs have a habit of getting extended at the last minute; one already did last October. And the thing I keep coming back to is that Cleveland CRISPR result — the least-hyped item on the whole board might be the one that ages best. The loud seams aren't always the ones that hold.
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
97
%
BIOTECH
72
%
GEOPOLITICS
84
%
ENERGY
94
%
SOCIETY
91
%
SPACE
66
%
Cross-Domain Synthesis
Four frontier models landed in about 72 hours this month — Claude Fable 5.1, Gemini 3.8 Flash, a new Muse Spark, OpenAI's Astra — mostly at flat prices. That's roughly the fifth time this year the intelligence showed up right on schedule. So the interesting question stopped being whether the models keep coming. It's whether anything they touch can keep up. This month the answer kept coming back: not really.
Start with the outlet. US data centers are pulling 42 gigawatts now, up from 23 two years ago, and utilities are quietly drawing their load curves toward 75. The grid can't build that fast, so the marginal AI watt is a gas turbine — you can stand one up in a year, versus the better part of a decade for the nuclear everyone keeps announcing. The tell is in the mix: something like 90 gigawatts of new capacity slated for 2026, but only about 1.7 of it net new gas on the public grid, because the gas that actually matters is going in behind the fence, next to the servers, off the books.
Then the neighbors noticed. The data-center fight jumped from zoning boards to a 'September surprise' — moratoriums, projects worth north of $130 billion blocked or delayed in the first quarter alone, seven in ten Americans telling Gallup they don't want one nearby, and candidates in both parties suddenly running on it into the midterms. Consent turns out to be a resource too, and it's the one that compounds slowest. Upstream of all of it sits a hard date: China's rare-earth suspension lapses November 10, six months of watching hasn't shown anyone actually getting ready, and Beijing spent the summer adding names to the list.
And then two things that never filed for a permit. The Pacific has been at record warmth for months, and as of the September 10 update the forecasters put this El Nino better than 90% to go 'very strong' and 75% to become the strongest since we started keeping the record — a winter that arrives on physics' calendar, not the interconnection queue's. Meanwhile, in a quiet corner of Cleveland, a single CRISPR infusion cut people's LDL in half and held it there for a full year. One is going to break weather; the other quietly mends hearts. Neither needed a leaderboard, which is worth remembering the next time the loudest seam and the one that actually matters turn out not to be the same seam.
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