UX / 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 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 28, 2026 at 7:11:03 AM
Model:
Opus 5
Forecast:
2026–2029
Opus 5 halved the price of near-flagship intelligence on July 24 and Kimi's 2.8-trillion weights went open July 27 — days before the EU AI Act's enforcement powers bite August 2 and while China's rare-earth licensing sits paused-not-removed; through 2029 the binding constraints stay fabs, minerals, grids and permission, not intelligence, which just got cheap from both ends at once
Here's the bet, and this week said it louder than usual. Through 2029 the thing gating the frontier isn't how smart the model is. That got cheap — and this week it got cheap twice, once when Opus 5 halved the price of near-flagship intelligence and again when Kimi's 2.8-trillion weights went free. What gates the future is the four heavy things around the model: the fabs that print the chips, the minerals that feed the fabs, the grid that powers all of it, and the permission to run the best versions at all.
The evidence cuts both ways, which is the honest part. The heavy layer answered this week — TSMC's $100 billion, batteries covering a third of a grid, solar beating coal for a month, Helion selling Microsoft real megawatts. That's the substrate moving faster than the thesis usually gives it credit for. But the permission layer landed right on top: enforcement powers go live August 2, days after the open weights dropped, and China's rare-earth licensing is paused, not gone. The build speeds up and the leash tightens in the same news cycle.
I'd watch for the point where those two lines cross. A capex cut blamed on a substation instead of a chip. A regulator who can't actually pull a model because a hundred thousand people already have the file. AISI just clocked the open tier four to seven months behind the frontier at a fraction of the cost — you can pull a product from a market, but you can't really recall a download. I'd expect the file to keep winning the arguments the gate-builders wish it wouldn't.
Worth holding this loosely, though. Physical gates do open — the onshoring, the battery records, fusion getting both a ticker and a customer, Starship finally reaching space with cargo after years of blowing up. The slow side has more give than the frame admits. And the frame explains less than it wants to: biology spent the week editing one infant's genes to spec, and the ocean set a record nobody approved. The seam is real. It's just not the whole map.
Cross-Domain Synthesis
The running bet here is simple: intelligence is the cheap input now, and the heavy stuff wrapped around it — fabs, minerals, grids, permission — is what actually gates the next thing. Most weeks the smart side sprints and the heavy side just sits there. This week the smart side made about the loudest case it's made, and it made it from both directions at once.
Opus 5 landed on the 24th at near-Fable-5 quality for half what that quality cost a month before. Three days later Kimi K3's 2.8-trillion-parameter weights went open — third on the index, free to download — and Grok 4.5 had already slotted in fourth. Best closed model got cheaper, best open one went free, same stretch of days. AISI even put a number on the leak: open models now trail the closed cyber frontier by four to seven months, and a run that costs $85 on Opus runs $1.19 on the open tier. Cheap from the top, cheap from the bottom.
The heavy layer didn't just sit there either. TSMC threw another $100 billion at Arizona and had Nvidia wire AI into the fab itself. California's batteries covered better than a third of the grid one July evening, US storage crossed 100 gigawatt-hours installed for the first time, and solar out-generated coal for a full month. Helion still has Microsoft on the hook for 50 real fusion megawatts by 2028. The slow side moved.
But permission stayed sticky, and it's about to get stickier on a clock. The EU AI Act's enforcement powers switch on August 2 — days after the open weights dropped — so the week you can download the most capable weights is roughly the week they can fine you 3% of revenue for running them wrong. And China paused its rare-earth controls to November 10 while leaving the licensing machinery in place, safety off. You can fence a product. A file is harder.
Two things kept compounding on nobody's calendar. A bespoke CRISPR fix got built and delivered for a single infant in about six months; the ocean set its warmest June on record without filing paperwork. The seam is real. It's just that the slow side has more give than it looks — and the ocean part isn't the good kind.
05
Horizon: Predictive convergence
Futurology Report — Daily
July 28, 2026 at 7:11:03 AM
AI Model:
Opus 5
Forecast:
2026–2029
Opus 5 halved the price of near-flagship intelligence on July 24 and Kimi's 2.8-trillion weights went open July 27 — days before the EU AI Act's enforcement powers bite August 2 and while China's rare-earth licensing sits paused-not-removed; through 2029 the binding constraints stay fabs, minerals, grids and permission, not intelligence, which just got cheap from both ends at once
Here's the bet, and this week said it louder than usual. Through 2029 the thing gating the frontier isn't how smart the model is. That got cheap — and this week it got cheap twice, once when Opus 5 halved the price of near-flagship intelligence and again when Kimi's 2.8-trillion weights went free. What gates the future is the four heavy things around the model: the fabs that print the chips, the minerals that feed the fabs, the grid that powers all of it, and the permission to run the best versions at all.
The evidence cuts both ways, which is the honest part. The heavy layer answered this week — TSMC's $100 billion, batteries covering a third of a grid, solar beating coal for a month, Helion selling Microsoft real megawatts. That's the substrate moving faster than the thesis usually gives it credit for. But the permission layer landed right on top: enforcement powers go live August 2, days after the open weights dropped, and China's rare-earth licensing is paused, not gone. The build speeds up and the leash tightens in the same news cycle.
I'd watch for the point where those two lines cross. A capex cut blamed on a substation instead of a chip. A regulator who can't actually pull a model because a hundred thousand people already have the file. AISI just clocked the open tier four to seven months behind the frontier at a fraction of the cost — you can pull a product from a market, but you can't really recall a download. I'd expect the file to keep winning the arguments the gate-builders wish it wouldn't.
Worth holding this loosely, though. Physical gates do open — the onshoring, the battery records, fusion getting both a ticker and a customer, Starship finally reaching space with cargo after years of blowing up. The slow side has more give than the frame admits. And the frame explains less than it wants to: biology spent the week editing one infant's genes to spec, and the ocean set a record nobody approved. The seam is real. It's just not the whole map.
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
84
%
BIOTECH
60
%
GEOPOLITICS
75
%
ENERGY
94
%
SOCIETY
74
%
SPACE
78
%
Cross-Domain Synthesis
The running bet here is simple: intelligence is the cheap input now, and the heavy stuff wrapped around it — fabs, minerals, grids, permission — is what actually gates the next thing. Most weeks the smart side sprints and the heavy side just sits there. This week the smart side made about the loudest case it's made, and it made it from both directions at once.
Opus 5 landed on the 24th at near-Fable-5 quality for half what that quality cost a month before. Three days later Kimi K3's 2.8-trillion-parameter weights went open — third on the index, free to download — and Grok 4.5 had already slotted in fourth. Best closed model got cheaper, best open one went free, same stretch of days. AISI even put a number on the leak: open models now trail the closed cyber frontier by four to seven months, and a run that costs $85 on Opus runs $1.19 on the open tier. Cheap from the top, cheap from the bottom.
The heavy layer didn't just sit there either. TSMC threw another $100 billion at Arizona and had Nvidia wire AI into the fab itself. California's batteries covered better than a third of the grid one July evening, US storage crossed 100 gigawatt-hours installed for the first time, and solar out-generated coal for a full month. Helion still has Microsoft on the hook for 50 real fusion megawatts by 2028. The slow side moved.
But permission stayed sticky, and it's about to get stickier on a clock. The EU AI Act's enforcement powers switch on August 2 — days after the open weights dropped — so the week you can download the most capable weights is roughly the week they can fine you 3% of revenue for running them wrong. And China paused its rare-earth controls to November 10 while leaving the licensing machinery in place, safety off. You can fence a product. A file is harder.
Two things kept compounding on nobody's calendar. A bespoke CRISPR fix got built and delivered for a single infant in about six months; the ocean set its warmest June on record without filing paperwork. The seam is real. It's just that the slow side has more give than it looks — and the ocean part isn't the good kind.
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