Machine Vision
Wearable
AI • AGEnts
23
YEARS EXPERIENCE
3
TECHNOLOGY COMPANIES
Multiple
PATENTS FILED/GRANTED
01
Selected Work
Case Studies
Lytx AI Chat
UX Lead
•
Lytx
•
16 months
→
An AI assistant in the Lytx Admin portal that answers fleet admins' questions with numbers computed from their live account data, not made up by the model.
Lytx Self-Serve Ordering
UX Lead
•
Lytx
•
1 year
→
A self-serve storefront inside Lytx Account Center that turns emailed reorders into guided, validated orders, from catalog to scheduled install.
Global Trend Engine
Designer & Builder
•
Self-Initiated
•
Ongoing
→
An agentic AI dashboard with four agents that scan for frontier signals, turn them into predictions and check which ones come true. 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
Daily Futurology Report
November 12, 2026 at 12:50:32 AM
Model:
Claude Opus 5.5
Forecast:
2026–2028
Who pays becomes the whole argument
Here's the bet: from 2026 to 2028, the argument shifts from whether to build to who carries the cost, and the cost moves toward the builders. Data centers pay for their own grid. Labs raise from public markets. Drugmakers give up European patients to protect US prices.
The evidence is piling up in rate cases and press releases, not think pieces. Microsoft's self-funding pledge. APS asking 45% more from large users. ERCOT wanting earlier curtailment authority. Oakland's moratorium running to October 2027. EU drug launches down roughly 35% since the MFN order. Rare-earth relief that technically expired Nov. 10 while shipments trickle.
I'd expect the first real test to be Texas. If the legislature gives ERCOT early curtailment power, "pay your own way" stops being a press release and becomes a tariff term. The other one to watch is Anthropic's pricing, reportedly targeted before Thanksgiving. That'll tell us what public investors think a frontier lab's compute bill is worth.
Worth holding this loosely, though. Voluntary pledges are cheap until a quarter goes badly, and "paying our own way" can still mean building generation that ratepayers end up backstopping. Rare earths cut the other way, too. There the cost lands on whoever sits downstream of Beijing, and nobody's volunteering.
Cross-Domain Synthesis
Tonight's theme is the invoice. Not whether the AI build-out happens. That argument's mostly over. The question now is who pays for it, and the answer showing up this week is: the builders. Or at least that's the new pitch.
Start with power. Microsoft said it'll fund its own data-center power without subsidies or added costs to anyone else: "We don't want other customers to be paying for our growth." Same day, ERCOT's Pablo Vegas said he'll ask Texas lawmakers to let the grid make data centers cut power before an emergency, not at level two of a three-level alarm. In Arizona, APS has proposed raising large-user rates 45% against 14% for households. Oakland extended its data-center moratorium through October 2027. And Anthropic's IPO roadshow reportedly started the week of Nov. 9, which is another way of sending the bill out, this time to public shareholders.
The pattern repeats elsewhere. China's rare-earth export pause formally lapsed Nov. 10 with no published extension, and US Ambassador David Perdue said Washington has been "waiting for months" on shipments. Drugmakers are holding back European launches to protect US prices under most-favored-nation rules. GlobalData counts EU launches down about 35% in the ten months after the order. At COP31 in Antalya, most G7 leaders skipped the high-level segment, and the presidency is selling implementation, not new money.
The counter-current: some of the scary numbers shrink when you look closer. Challenger counted 1,265 AI-cited job cuts out of 43,994 in October, and market conditions have passed AI as 2026's most-cited reason. And Starship is lined up for a double catch on Flight 15. If that works, the cheapest ride to orbit gets cheaper again.
05
Horizon: Predictive convergence
Futurology Report — Daily
November 12, 2026 at 12:50:32 AM
AI Model:
Claude Opus 5.5
Forecast:
2026–2028
◆ PYTHIA AGENT · 48 TRACKED · 0 RESOLVED
Tracker →
Who pays becomes the whole argument
Here's the bet: from 2026 to 2028, the argument shifts from whether to build to who carries the cost, and the cost moves toward the builders. Data centers pay for their own grid. Labs raise from public markets. Drugmakers give up European patients to protect US prices.
The evidence is piling up in rate cases and press releases, not think pieces. Microsoft's self-funding pledge. APS asking 45% more from large users. ERCOT wanting earlier curtailment authority. Oakland's moratorium running to October 2027. EU drug launches down roughly 35% since the MFN order. Rare-earth relief that technically expired Nov. 10 while shipments trickle.
I'd expect the first real test to be Texas. If the legislature gives ERCOT early curtailment power, "pay your own way" stops being a press release and becomes a tariff term. The other one to watch is Anthropic's pricing, reportedly targeted before Thanksgiving. That'll tell us what public investors think a frontier lab's compute bill is worth.
Worth holding this loosely, though. Voluntary pledges are cheap until a quarter goes badly, and "paying our own way" can still mean building generation that ratepayers end up backstopping. Rare earths cut the other way, too. There the cost lands on whoever sits downstream of Beijing, and nobody's volunteering.
Signal Intensity
A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.
AI
80
%
Climate
66
%
BIOTECH
60
%
GEOPOLITICS
70
%
ENERGY
85
%
SOCIETY
58
%
SPACE
64
%
Cross-Domain Synthesis
Tonight's theme is the invoice. Not whether the AI build-out happens. That argument's mostly over. The question now is who pays for it, and the answer showing up this week is: the builders. Or at least that's the new pitch.
Start with power. Microsoft said it'll fund its own data-center power without subsidies or added costs to anyone else: "We don't want other customers to be paying for our growth." Same day, ERCOT's Pablo Vegas said he'll ask Texas lawmakers to let the grid make data centers cut power before an emergency, not at level two of a three-level alarm. In Arizona, APS has proposed raising large-user rates 45% against 14% for households. Oakland extended its data-center moratorium through October 2027. And Anthropic's IPO roadshow reportedly started the week of Nov. 9, which is another way of sending the bill out, this time to public shareholders.
The pattern repeats elsewhere. China's rare-earth export pause formally lapsed Nov. 10 with no published extension, and US Ambassador David Perdue said Washington has been "waiting for months" on shipments. Drugmakers are holding back European launches to protect US prices under most-favored-nation rules. GlobalData counts EU launches down about 35% in the ten months after the order. At COP31 in Antalya, most G7 leaders skipped the high-level segment, and the presidency is selling implementation, not new money.
The counter-current: some of the scary numbers shrink when you look closer. Challenger counted 1,265 AI-cited job cuts out of 43,994 in October, and market conditions have passed AI as 2026's most-cited reason. And Starship is lined up for a double catch on Flight 15. If that works, the cheapest ride to orbit gets cheaper again.
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