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 18, 2026 at 7:10:00 AM
Model:
Opus 4.8
Forecast:
2026–2028
The war premium arrives: as missiles cross into Omani waters and the blockade snaps back, control of firm domestic power — not the best model — decides who can still scale
Within 12–24 months, the decisive frontier advantage will belong not to whoever trains the best model but to whoever can secure physical inputs against a rising war premium — firm domestic power and defended energy corridors — because that, not the weights, is what gates the ability to scale intelligence.
The evidence is converging fast. Models keep commoditizing as DeepSeek V4 undercuts the frontier ~34x and the July 9 cost war deepens. Meanwhile the physical is contested by force: cruise missiles into Omani waters, a reinstated naval blockade, oil back to $85, four reactors critical on a federal deadline, 9.8 GW of nuclear committed, and a record-shattering heat wave straining the grid.
The likeliest inflection is that criticality at home becomes the hedge against conflict abroad. As the militarized corridor prices a war premium into every imported barrel, domestically firm, enforceable power — reactors that actually reach criticality, grids that hold through record heat — becomes the true moat, and the gap between committed gigawatts and delivered electrons the central bottleneck.
Pulling the other way, the machine's success is minting its opposite: as synthetic media saturates the feed, proof of human becomes the premium signal — and biology keeps advancing on a clock the energy macro cannot touch, with edited CAR-T putting lupus into drug-free remission and regulators clearing one-patient platform therapies.
Cross-Domain Synthesis
Yesterday's seam read control as asserted by fee and by force. Today it hardens into a war premium: enforcement has spilled beyond the Strait of Hormuz into Omani waters and the naval blockade has snapped back, so moving energy now carries the price of open conflict.
At the machine layer, commoditization accelerates. DeepSeek V4 lands as MIT-licensed open weights at $0.87 per million output tokens — roughly 34x under GPT-5.5 — and the July 9 three-lab cluster's verdict holds: best fit wins as agents cross from chat into production. Cognition is a falling cost.
At the physical layer, everything cognition depends on is rising and being fought over. Iranian cruise missiles struck two UAE-linked supertankers in Omani waters on July 14 and the US reinstated its blockade as Brent touched $84.98. Four microreactors reached criticality under the DOE's July 4 pilot while hyperscalers lock in 9.8 GW of nuclear — yet SMRs arrive in earnest only in the 2030s. A second heat wave set an all-time 109°F in Salt Lake City with the death toll past 44, and the ocean holds record heat. Even orbit waits on Starship hardware for Artemis III's 2027 demo.
Two clocks still run against the macro. Culture prices proof of human as deepfake incidents surge 900% and Samsung bakes C2PA provenance into the S25 camera. And medicine advances on its own timeline — edited CAR-T holding lupus in drug-free remission while the FDA clears bespoke one-patient therapies.
05
Horizon: Predictive convergence
Futurology Report — Daily
July 18, 2026 at 7:10:00 AM
AI Model:
Opus 4.8
Forecast:
2026–2028
The war premium arrives: as missiles cross into Omani waters and the blockade snaps back, control of firm domestic power — not the best model — decides who can still scale
Within 12–24 months, the decisive frontier advantage will belong not to whoever trains the best model but to whoever can secure physical inputs against a rising war premium — firm domestic power and defended energy corridors — because that, not the weights, is what gates the ability to scale intelligence.
The evidence is converging fast. Models keep commoditizing as DeepSeek V4 undercuts the frontier ~34x and the July 9 cost war deepens. Meanwhile the physical is contested by force: cruise missiles into Omani waters, a reinstated naval blockade, oil back to $85, four reactors critical on a federal deadline, 9.8 GW of nuclear committed, and a record-shattering heat wave straining the grid.
The likeliest inflection is that criticality at home becomes the hedge against conflict abroad. As the militarized corridor prices a war premium into every imported barrel, domestically firm, enforceable power — reactors that actually reach criticality, grids that hold through record heat — becomes the true moat, and the gap between committed gigawatts and delivered electrons the central bottleneck.
Pulling the other way, the machine's success is minting its opposite: as synthetic media saturates the feed, proof of human becomes the premium signal — and biology keeps advancing on a clock the energy macro cannot touch, with edited CAR-T putting lupus into drug-free remission and regulators clearing one-patient platform therapies.
Signal Intensity
A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.
AI
88
%
Climate
86
%
BIOTECH
60
%
GEOPOLITICS
94
%
ENERGY
93
%
SOCIETY
64
%
SPACE
66
%
Cross-Domain Synthesis
Yesterday's seam read control as asserted by fee and by force. Today it hardens into a war premium: enforcement has spilled beyond the Strait of Hormuz into Omani waters and the naval blockade has snapped back, so moving energy now carries the price of open conflict.
At the machine layer, commoditization accelerates. DeepSeek V4 lands as MIT-licensed open weights at $0.87 per million output tokens — roughly 34x under GPT-5.5 — and the July 9 three-lab cluster's verdict holds: best fit wins as agents cross from chat into production. Cognition is a falling cost.
At the physical layer, everything cognition depends on is rising and being fought over. Iranian cruise missiles struck two UAE-linked supertankers in Omani waters on July 14 and the US reinstated its blockade as Brent touched $84.98. Four microreactors reached criticality under the DOE's July 4 pilot while hyperscalers lock in 9.8 GW of nuclear — yet SMRs arrive in earnest only in the 2030s. A second heat wave set an all-time 109°F in Salt Lake City with the death toll past 44, and the ocean holds record heat. Even orbit waits on Starship hardware for Artemis III's 2027 demo.
Two clocks still run against the macro. Culture prices proof of human as deepfake incidents surge 900% and Samsung bakes C2PA provenance into the S25 camera. And medicine advances on its own timeline — edited CAR-T holding lupus in drug-free remission while the FDA clears bespoke one-patient therapies.
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