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 24, 2026 at 7:44:23 AM
Model:
Opus 4.8
Forecast:
2026–2029
Kimi's 2.8-trillion-parameter weights go open on the 27th, four days before the EU AI Act bites on August 2: through 2029 the frontier is gated by fabs, minerals, grids and permission — not by intelligence, which just got cheaper and harder to fence
Here's the bet. Through 2029 the thing gating the frontier isn't how smart the model is — that's the cheap input now, and it gets cheaper the day Kimi's weights go open on the 27th. It's the four slow things wrapped around the model: the fabs that print the chips, the minerals that feed the fabs, the grid that powers the whole thing, and the permission to run the most capable versions at all.
The evidence keeps stacking the same way. A leading-edge fab is still a multi-year, tens-of-billions build. New York just froze data-center construction for a year and the interconnection queue swallows five-year waits, so the response is to wire reactors straight to the campus and skip the grid entirely. China can suspend its rare-earth controls and still own the refining, which is why the November truce reads as a loan, not a pardon. And the EU AI Act's full rules land August 2nd, four days after the most capable open weights hit the internet — the permission layer and the download layer arriving in the same week is the whole story in miniature.
I'd watch for the tell in what stops getting bought and what refuses to stay fenced. A hyperscaler writing down compute it can't power. A capex cut blamed on a substation, not a chip. And on the other side, watch whether open weights make the permission gates leak — you can't switch off something a hundred thousand people already downloaded, and Kimi K3 and Mistral's model are about to be exactly that. The gate and the download are on a collision course, and I'd expect the download to win more often than the people building the gate would like.
Worth holding this loosely, though. Physical constraints loosen quietly once the price gets loud enough — behind-the-meter nuclear was fringe two years ago and now it's gigawatts of signatures. Some of the mineral panic was always leverage and stockpiling more than real scarcity, and the truce is the tell. And the thesis explains less than it wants to: biology compounded all year on nobody's grid, and the ocean hit its record without filing for a permit. The seam is real. It just isn't the whole map.
Cross-Domain Synthesis
The frontier is running at two speeds again, and this week the gap between them got a date on it. Intelligence keeps turning into something you download for free — Moonshot opens Kimi K3's 2.8 trillion weights on the 27th, it's already the third-strongest model anyone has benchmarked, and Mistral shipped an open-weight model under Apache 2.0, about as unfenced as a license gets. The smart part is cheap and getting cheaper.
The part that isn't cheap is permission. The EU AI Act's full obligations land August 2nd — four days after Kimi goes open — so the same week the most capable weights hit the internet, the rules for running them switch on. DHS-CISA wants prompt-injection guardrails and human-override paperwork before agentic AI touches critical infrastructure, OpenAI is asking Washington to make pre-release evals mandatory, and Grok 4.5 shipped built for hours-long autonomous runs with no safety card at all. The question quietly moved from can you build it to are you allowed to run it.
Underneath that, the physical layer did its usual nothing-fast. New York just banned new data centers for a year. The interconnection queue is still a wall, so the hyperscalers keep trying to skip it — Microsoft got a FERC waiver in June to wire the 835-megawatt Three Mile Island restart straight to a campus by 2027, Meta signed up 6.6 gigawatts of nuclear. And the materials under all of it got a strange reprieve: China suspended the rare-earth controls it rolled out last October, a truce that runs to November 10, but left the licensing machinery sitting there with the safety off — case-by-case approval on anything feeding sub-14nm chips, look-through rules reaching into everyone's supply chain. TSMC still buys about a third of its sub-7nm consumables from China. Paused isn't the same as gone.
Two things kept ignoring the whole frame. Biology compounded on nobody's grid — a single CRISPR infusion cut people's LDL in half and their triglycerides by more than that, and the next round of one-and-done edits is already lining up trials. And the ocean hit its warmest June on record, 82% of its surface under a marine heatwave, no permit required. One of those is the good kind of unstoppable. The other one isn't.
05
Horizon: Predictive convergence
Futurology Report — Daily
July 24, 2026 at 7:44:23 AM
AI Model:
Opus 4.8
Forecast:
2026–2029
Kimi's 2.8-trillion-parameter weights go open on the 27th, four days before the EU AI Act bites on August 2: through 2029 the frontier is gated by fabs, minerals, grids and permission — not by intelligence, which just got cheaper and harder to fence
Here's the bet. Through 2029 the thing gating the frontier isn't how smart the model is — that's the cheap input now, and it gets cheaper the day Kimi's weights go open on the 27th. It's the four slow things wrapped around the model: the fabs that print the chips, the minerals that feed the fabs, the grid that powers the whole thing, and the permission to run the most capable versions at all.
The evidence keeps stacking the same way. A leading-edge fab is still a multi-year, tens-of-billions build. New York just froze data-center construction for a year and the interconnection queue swallows five-year waits, so the response is to wire reactors straight to the campus and skip the grid entirely. China can suspend its rare-earth controls and still own the refining, which is why the November truce reads as a loan, not a pardon. And the EU AI Act's full rules land August 2nd, four days after the most capable open weights hit the internet — the permission layer and the download layer arriving in the same week is the whole story in miniature.
I'd watch for the tell in what stops getting bought and what refuses to stay fenced. A hyperscaler writing down compute it can't power. A capex cut blamed on a substation, not a chip. And on the other side, watch whether open weights make the permission gates leak — you can't switch off something a hundred thousand people already downloaded, and Kimi K3 and Mistral's model are about to be exactly that. The gate and the download are on a collision course, and I'd expect the download to win more often than the people building the gate would like.
Worth holding this loosely, though. Physical constraints loosen quietly once the price gets loud enough — behind-the-meter nuclear was fringe two years ago and now it's gigawatts of signatures. Some of the mineral panic was always leverage and stockpiling more than real scarcity, and the truce is the tell. And the thesis explains less than it wants to: biology compounded all year on nobody's grid, and the ocean hit its record without filing for a permit. The seam is real. It just isn't 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
94
%
Climate
89
%
BIOTECH
66
%
GEOPOLITICS
84
%
ENERGY
95
%
SOCIETY
80
%
SPACE
68
%
Cross-Domain Synthesis
The frontier is running at two speeds again, and this week the gap between them got a date on it. Intelligence keeps turning into something you download for free — Moonshot opens Kimi K3's 2.8 trillion weights on the 27th, it's already the third-strongest model anyone has benchmarked, and Mistral shipped an open-weight model under Apache 2.0, about as unfenced as a license gets. The smart part is cheap and getting cheaper.
The part that isn't cheap is permission. The EU AI Act's full obligations land August 2nd — four days after Kimi goes open — so the same week the most capable weights hit the internet, the rules for running them switch on. DHS-CISA wants prompt-injection guardrails and human-override paperwork before agentic AI touches critical infrastructure, OpenAI is asking Washington to make pre-release evals mandatory, and Grok 4.5 shipped built for hours-long autonomous runs with no safety card at all. The question quietly moved from can you build it to are you allowed to run it.
Underneath that, the physical layer did its usual nothing-fast. New York just banned new data centers for a year. The interconnection queue is still a wall, so the hyperscalers keep trying to skip it — Microsoft got a FERC waiver in June to wire the 835-megawatt Three Mile Island restart straight to a campus by 2027, Meta signed up 6.6 gigawatts of nuclear. And the materials under all of it got a strange reprieve: China suspended the rare-earth controls it rolled out last October, a truce that runs to November 10, but left the licensing machinery sitting there with the safety off — case-by-case approval on anything feeding sub-14nm chips, look-through rules reaching into everyone's supply chain. TSMC still buys about a third of its sub-7nm consumables from China. Paused isn't the same as gone.
Two things kept ignoring the whole frame. Biology compounded on nobody's grid — a single CRISPR infusion cut people's LDL in half and their triglycerides by more than that, and the next round of one-and-done edits is already lining up trials. And the ocean hit its warmest June on record, 82% of its surface under a marine heatwave, no permit required. One of those is the good kind of unstoppable. The other one isn't.
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