Machine Vision
Wearable
AI • AGEnts
23
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
November 4, 2026 at 12:09:24 AM
Model:
Opus 5.5
Forecast:
2026–2028
Permission Is the Bottleneck: Through 2028, Local Votes, Not Chips or Demand, Set the Pace of the AI Buildout
Here's the bet: through 2028, the tightest constraint on the AI buildout isn't chips, and it isn't demand. It's permission. And permission is now handed out town by town.
The evidence came in on one night. At least 14 Ohio municipalities passed data-center bans or limits, Grove City now requires a public vote on large developments (55% in favor), and Wilmington voters killed a rezoning by about 80%. Meanwhile AMD's data-center revenue grew 97% year over year. The buyers want the hardware. The neighbors don't want the building. OpenAI's grid-curtailment pledge and the 'AI compute campuses' rename are the industry telling you it knows which problem is harder.
What I'd watch is whether the new Democratic Congress turns local anger into federal terms in 2027: who pays for grid upgrades, disclosure, conditions on interconnection. The other tell is migration. If siting shifts toward places still saying yes, like Drax pitching a £20bn campus at a North Yorkshire biomass plant, the bottleneck moves rather than binds.
Worth holding this loosely, though. Small-town bans reshape the map more than the total, and hyperscalers have other states and other countries. A Democratic Congress still has to get bills past a Republican president, so the likeliest federal outcome is gridlock, not rules. And the market's after-hours mood swing is one night of data, not a trend.
Cross-Domain Synthesis
Yesterday's bet was that AI builders would trade a little voluntary restraint for room to grow. Last night voters showed up with their own terms.
Start local. Ohio held 21 of the country's 41 data-center ballot measures, and early counts have at least 14 municipalities passing bans or restrictions, on top of the 125 local moratoriums the state already had. Wilmington voters rejected rezoning for a data center by roughly 80%. OpenAI's answer, the same week: call them 'AI compute campuses.' Rebrands don't rezone.
Then Washington. Democrats won both the House and the Senate, flipping seven Republican-held Senate seats by Forbes' count. Researchers tallied more than $187 million on nearly 300 AI-generated or AI-enhanced political ads, with disclosure rules that change at every state line. Futures fell on the early counts, and traders started betting on a slower data-center buildout.
Except the money says demand is fine. AMD beat: $13.38bn in Q3 revenue, $8.5bn of it data center, up 97%, and a Q4 guide around $17bn. The midterm sell-off cut its after-hours pop roughly in half anyway.
The counter-current: plenty doesn't care who won. China's rare-earth suspension still lapses Nov 10 with no renewal in the published text. A Washington resident died of H5N1 after exposure to infected dairy cattle, the first US bird-flu death in about a year. COP31 opens Nov 9 pitched as delivery, not new pledges. And drugmaker CEOs told the WSJ that no AI-designed medicine has FDA approval yet.
05
Horizon: Predictive convergence
Futurology Report — Daily
November 4, 2026 at 12:09:24 AM
AI Model:
Opus 5.5
Forecast:
2026–2028
◆ PYTHIA AGENT · 26 TRACKED · 0 RESOLVED
Tracker →
Permission Is the Bottleneck: Through 2028, Local Votes, Not Chips or Demand, Set the Pace of the AI Buildout
Here's the bet: through 2028, the tightest constraint on the AI buildout isn't chips, and it isn't demand. It's permission. And permission is now handed out town by town.
The evidence came in on one night. At least 14 Ohio municipalities passed data-center bans or limits, Grove City now requires a public vote on large developments (55% in favor), and Wilmington voters killed a rezoning by about 80%. Meanwhile AMD's data-center revenue grew 97% year over year. The buyers want the hardware. The neighbors don't want the building. OpenAI's grid-curtailment pledge and the 'AI compute campuses' rename are the industry telling you it knows which problem is harder.
What I'd watch is whether the new Democratic Congress turns local anger into federal terms in 2027: who pays for grid upgrades, disclosure, conditions on interconnection. The other tell is migration. If siting shifts toward places still saying yes, like Drax pitching a £20bn campus at a North Yorkshire biomass plant, the bottleneck moves rather than binds.
Worth holding this loosely, though. Small-town bans reshape the map more than the total, and hyperscalers have other states and other countries. A Democratic Congress still has to get bills past a Republican president, so the likeliest federal outcome is gridlock, not rules. And the market's after-hours mood swing is one night of data, not a trend.
Signal Intensity
A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.
AI
82
%
Climate
78
%
BIOTECH
60
%
GEOPOLITICS
80
%
ENERGY
86
%
SOCIETY
84
%
SPACE
60
%
Cross-Domain Synthesis
Yesterday's bet was that AI builders would trade a little voluntary restraint for room to grow. Last night voters showed up with their own terms.
Start local. Ohio held 21 of the country's 41 data-center ballot measures, and early counts have at least 14 municipalities passing bans or restrictions, on top of the 125 local moratoriums the state already had. Wilmington voters rejected rezoning for a data center by roughly 80%. OpenAI's answer, the same week: call them 'AI compute campuses.' Rebrands don't rezone.
Then Washington. Democrats won both the House and the Senate, flipping seven Republican-held Senate seats by Forbes' count. Researchers tallied more than $187 million on nearly 300 AI-generated or AI-enhanced political ads, with disclosure rules that change at every state line. Futures fell on the early counts, and traders started betting on a slower data-center buildout.
Except the money says demand is fine. AMD beat: $13.38bn in Q3 revenue, $8.5bn of it data center, up 97%, and a Q4 guide around $17bn. The midterm sell-off cut its after-hours pop roughly in half anyway.
The counter-current: plenty doesn't care who won. China's rare-earth suspension still lapses Nov 10 with no renewal in the published text. A Washington resident died of H5N1 after exposure to infected dairy cattle, the first US bird-flu death in about a year. COP31 opens Nov 9 pitched as delivery, not new pledges. And drugmaker CEOs told the WSJ that no AI-designed medicine has FDA approval yet.
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