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
August 2, 2026 at 7:16:00 AM
Model:
Opus 4.8
Forecast:
2026–2029
The EU's power to fine frontier AI labs went live today — real money, retroactive to last summer. Two days earlier, DeepSeek dropped a top-tier model anyone can download free under an MIT license. That's the whole story through 2029: a rulebook that binds companies, and a frontier that keeps shipping as a file no border can recall.
Here's the bet, now that the machinery's actually switched on. Through 2029, the thing gating the frontier isn't the models — it's whether a rule that moves at the speed of law can bind a capability that ships as a free download. Enforcement went live this week. The frontier partly went open the same week. That gap is the story.
The evidence is right there in the calendar. The EU's fining power turned on August 2; two days before, DeepSeek released V4 Pro under an MIT license — 1.6 trillion parameters, the #2 open reasoning model, free to run. Add the fully-open Kimi weights and OpenAI cutting prices 80%, and you get the tension in a single week: the strongest enforcement regime yet, and top-tier capability that lives outside anyone's power to withdraw it from a market.
I'd watch one thing above the rest — not whether Brussels issues a fine, but the clock on the first case. How long does an investigation take, measured against how many capable open models land while it runs? If the honest answer is one multi-year case against three model generations a year, half of them downloadable, then the mismatch is structural, not a teething problem. My guess is the fight that actually matters between now and 2029 is about jurisdiction: enforcement acts on companies inside a border, and the capability keeps arranging not to be one.
Worth holding this loosely, though. Teeth that reach a company still reach plenty — most frontier capability still ships from a handful of firms with EU revenue to protect, and a fine that reaches back to last summer changes the math even when it's slow. And a lot of the future ignores the argument entirely: the batteries keep breaking records, Helion got its fusion license, a gene therapy got built for one baby, the ocean's heading for its hottest year on record whether or not anyone files a form. 'The paper can't reach the file' is real, and it's the right thing to watch. It just isn't the only clock running.
Cross-Domain Synthesis
For weeks the story was two clocks about to strike. Today they struck. As of August 2 the EU's power to fine frontier AI labs stopped being a date on a slide — the AI Office can now demand your training docs, run its own tests on your model, order fixes, pull it off the EU market, and fine you up to 3% of global turnover or €15M, reaching back to obligations from last summer. Real money, live.
Here's the timing, and it's almost comic. Two days before the teeth went in, DeepSeek shipped V4 Pro — 1.6 trillion parameters, MIT license, second-best open reasoning model on the board — with the weights just sitting on Hugging Face for anyone to download. OpenAI cut its cheapest GPT-5.6 tier 80% the day before that. A regulator can fine a company. It can't fine a file that's already on a hundred thousand hard drives.
And the heavy layers kept their own clocks, indifferent to any of it. China's rare-earth choke — case-by-case sign-off now required for the chips that matter, the benchmark alloy up 21% in a month — sits upstream of every fab, and the truce holding it back runs out in November. Data centers are heading for roughly 1,050 terawatt-hours this year, which would make them the fifth-largest electricity draw on Earth if they were a country, so the hyperscalers keep buying nuclear straight off the grid and Helion just picked up the first US license to build a fusion plant. A CRISPR fix got built for a single infant in six months. Starship finally put 20 satellites in orbit.
Meanwhile the Pacific keeps warming toward the strongest El Niño ever measured — a forcing with no permit, no lead time, and no appeals process. So the seam moved again. Last week the question was whether the rule would show up. Now it's here, and the question is smaller and harder: what can it actually reach? The honest early read is that it reaches companies inside a border — and the frontier keeps finding ways to not be one.
05
Horizon: Predictive convergence
Futurology Report — Daily
August 2, 2026 at 7:16:00 AM
AI Model:
Opus 4.8
Forecast:
2026–2029
The EU's power to fine frontier AI labs went live today — real money, retroactive to last summer. Two days earlier, DeepSeek dropped a top-tier model anyone can download free under an MIT license. That's the whole story through 2029: a rulebook that binds companies, and a frontier that keeps shipping as a file no border can recall.
Here's the bet, now that the machinery's actually switched on. Through 2029, the thing gating the frontier isn't the models — it's whether a rule that moves at the speed of law can bind a capability that ships as a free download. Enforcement went live this week. The frontier partly went open the same week. That gap is the story.
The evidence is right there in the calendar. The EU's fining power turned on August 2; two days before, DeepSeek released V4 Pro under an MIT license — 1.6 trillion parameters, the #2 open reasoning model, free to run. Add the fully-open Kimi weights and OpenAI cutting prices 80%, and you get the tension in a single week: the strongest enforcement regime yet, and top-tier capability that lives outside anyone's power to withdraw it from a market.
I'd watch one thing above the rest — not whether Brussels issues a fine, but the clock on the first case. How long does an investigation take, measured against how many capable open models land while it runs? If the honest answer is one multi-year case against three model generations a year, half of them downloadable, then the mismatch is structural, not a teething problem. My guess is the fight that actually matters between now and 2029 is about jurisdiction: enforcement acts on companies inside a border, and the capability keeps arranging not to be one.
Worth holding this loosely, though. Teeth that reach a company still reach plenty — most frontier capability still ships from a handful of firms with EU revenue to protect, and a fine that reaches back to last summer changes the math even when it's slow. And a lot of the future ignores the argument entirely: the batteries keep breaking records, Helion got its fusion license, a gene therapy got built for one baby, the ocean's heading for its hottest year on record whether or not anyone files a form. 'The paper can't reach the file' is real, and it's the right thing to watch. It just isn't the only clock running.
Signal Intensity
A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.
AI
97
%
Climate
86
%
BIOTECH
60
%
GEOPOLITICS
86
%
ENERGY
88
%
SOCIETY
82
%
SPACE
74
%
Cross-Domain Synthesis
For weeks the story was two clocks about to strike. Today they struck. As of August 2 the EU's power to fine frontier AI labs stopped being a date on a slide — the AI Office can now demand your training docs, run its own tests on your model, order fixes, pull it off the EU market, and fine you up to 3% of global turnover or €15M, reaching back to obligations from last summer. Real money, live.
Here's the timing, and it's almost comic. Two days before the teeth went in, DeepSeek shipped V4 Pro — 1.6 trillion parameters, MIT license, second-best open reasoning model on the board — with the weights just sitting on Hugging Face for anyone to download. OpenAI cut its cheapest GPT-5.6 tier 80% the day before that. A regulator can fine a company. It can't fine a file that's already on a hundred thousand hard drives.
And the heavy layers kept their own clocks, indifferent to any of it. China's rare-earth choke — case-by-case sign-off now required for the chips that matter, the benchmark alloy up 21% in a month — sits upstream of every fab, and the truce holding it back runs out in November. Data centers are heading for roughly 1,050 terawatt-hours this year, which would make them the fifth-largest electricity draw on Earth if they were a country, so the hyperscalers keep buying nuclear straight off the grid and Helion just picked up the first US license to build a fusion plant. A CRISPR fix got built for a single infant in six months. Starship finally put 20 satellites in orbit.
Meanwhile the Pacific keeps warming toward the strongest El Niño ever measured — a forcing with no permit, no lead time, and no appeals process. So the seam moved again. Last week the question was whether the rule would show up. Now it's here, and the question is smaller and harder: what can it actually reach? The honest early read is that it reaches companies inside a border — and the frontier keeps finding ways to not be 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