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.)
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.
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 23, 2026 at 8:53:40 AM
Model:
Opus 4.8
Forecast:
2026–2029
Kimi's weights go open on the 27th and Washington can switch a US model off worldwide: through 2029 the frontier is gated by fabs, grids and permission — not by how smart the model is, 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 three slow things wrapped around the model: the fabs and refineries that make the hardware, the grid that powers it, and the permission to run the most capable versions at all.
The evidence keeps stacking the same way. A 2-nanometer fab is still a multi-year, tens-of-billions build. 2,600 GW sits in the queue behind five-year waits, and only about a third of this year's promised data-center power is actually under construction. China can suspend its rare-earth controls and still hold the refining, so the November truce is a loan, not a pardon. And the most capable models now ship with a government tier, a 30-day vetting window, or — in Anthropic's case in June — a worldwide off switch. None of that is a capability problem, and a smarter model solves none of it.
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 number cut because a substation slipped, not a chip. And on the other side, watch whether open weights make the permission gates leak — you can't really switch off something a hundred thousand people already downloaded, and both Inkling and Kimi K3 are now out there. 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 nine gigawatts of signatures. Some of the mineral panic was always stockpiling and negotiating leverage more than real scarcity, and the November 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 20.98C without filing for a permit. The seam is real, but it isn't the whole map.
Cross-Domain Synthesis
The frontier split into two speeds again this week, and the gap is getting hard to ignore. On one side, frontier-grade intelligence is turning into a free download: Thinking Machines shipped Inkling, a 975-billion-parameter open-weight model that's now the strongest US open release, and Moonshot says Kimi K3 — 2.8 trillion parameters, a million-token context — goes fully open on July 27. The UK's AI Security Institute clocked the open-weight cyber gap at four to seven months behind the closed frontier, down from six to ten. The smart part keeps getting cheaper and less scarce by the month.
The part that isn't getting cheaper is permission. On June 12 the US government made Anthropic switch off its two most capable models, Fable 5 and Mythos 5, for every customer on Earth, then walked it partway back to an approved-partner framework where access stays fenced rather than open. There's now a voluntary 30-day window for labs to hand their best models to the government before release. Meanwhile Grok 4.5 shipped on July 8 built for agentic runs that go for hours, with no model card or red-team disclosure attached. So the question quietly moved from can you build it to are you allowed to run it — and both answers are now somebody else's to give.
Underneath all of it, the physical layer did what it always does: nothing fast. 2,600 GW is still stuck in the US interconnection queue, only about 5 of a promised 16 GW of new data-center power is actually under construction, and the response is to stop waiting on the grid — 9.8 GW of nuclear now signed across thirteen hyperscaler deals, reactors parked next to the campus. The materials underneath that got a strange twist: China suspended the rare-earth controls it rolled out last October, a truce that runs to November 10, but left the machinery — case-by-case licensing on anything feeding sub-14nm chips, look-through rules reaching into foreign supply chains — sitting right there with the safety off.
Two things kept ignoring the whole frame. Biology compounded on nobody's grid and nobody's permission — CRISPR Therapeutics posted durable lipid knockdowns with CTX310 and CTX320, Beam has 31 people dosed with an FDA filing planned this year, and the FDA opened a 'plausible mechanism' path for one-off edits. And the ocean hit a record 20.98C in June with marine heatwaves across 82% of its surface, no license required. One of those is the good kind of unstoppable and one isn't.
05
Horizon: Predictive convergence
Futurology Report — Daily
July 23, 2026 at 8:53:40 AM
AI Model:
Opus 4.8
Forecast:
2026–2029
Kimi's weights go open on the 27th and Washington can switch a US model off worldwide: through 2029 the frontier is gated by fabs, grids and permission — not by how smart the model is, 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 three slow things wrapped around the model: the fabs and refineries that make the hardware, the grid that powers it, and the permission to run the most capable versions at all.
The evidence keeps stacking the same way. A 2-nanometer fab is still a multi-year, tens-of-billions build. 2,600 GW sits in the queue behind five-year waits, and only about a third of this year's promised data-center power is actually under construction. China can suspend its rare-earth controls and still hold the refining, so the November truce is a loan, not a pardon. And the most capable models now ship with a government tier, a 30-day vetting window, or — in Anthropic's case in June — a worldwide off switch. None of that is a capability problem, and a smarter model solves none of it.
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 number cut because a substation slipped, not a chip. And on the other side, watch whether open weights make the permission gates leak — you can't really switch off something a hundred thousand people already downloaded, and both Inkling and Kimi K3 are now out there. 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 nine gigawatts of signatures. Some of the mineral panic was always stockpiling and negotiating leverage more than real scarcity, and the November 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 20.98C without filing for a permit. The seam is real, but it 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
93
%
Climate
90
%
BIOTECH
64
%
GEOPOLITICS
86
%
ENERGY
95
%
SOCIETY
78
%
SPACE
67
%
Cross-Domain Synthesis
The frontier split into two speeds again this week, and the gap is getting hard to ignore. On one side, frontier-grade intelligence is turning into a free download: Thinking Machines shipped Inkling, a 975-billion-parameter open-weight model that's now the strongest US open release, and Moonshot says Kimi K3 — 2.8 trillion parameters, a million-token context — goes fully open on July 27. The UK's AI Security Institute clocked the open-weight cyber gap at four to seven months behind the closed frontier, down from six to ten. The smart part keeps getting cheaper and less scarce by the month.
The part that isn't getting cheaper is permission. On June 12 the US government made Anthropic switch off its two most capable models, Fable 5 and Mythos 5, for every customer on Earth, then walked it partway back to an approved-partner framework where access stays fenced rather than open. There's now a voluntary 30-day window for labs to hand their best models to the government before release. Meanwhile Grok 4.5 shipped on July 8 built for agentic runs that go for hours, with no model card or red-team disclosure attached. So the question quietly moved from can you build it to are you allowed to run it — and both answers are now somebody else's to give.
Underneath all of it, the physical layer did what it always does: nothing fast. 2,600 GW is still stuck in the US interconnection queue, only about 5 of a promised 16 GW of new data-center power is actually under construction, and the response is to stop waiting on the grid — 9.8 GW of nuclear now signed across thirteen hyperscaler deals, reactors parked next to the campus. The materials underneath that got a strange twist: China suspended the rare-earth controls it rolled out last October, a truce that runs to November 10, but left the machinery — case-by-case licensing on anything feeding sub-14nm chips, look-through rules reaching into foreign supply chains — sitting right there with the safety off.
Two things kept ignoring the whole frame. Biology compounded on nobody's grid and nobody's permission — CRISPR Therapeutics posted durable lipid knockdowns with CTX310 and CTX320, Beam has 31 people dosed with an FDA filing planned this year, and the FDA opened a 'plausible mechanism' path for one-off edits. And the ocean hit a record 20.98C in June with marine heatwaves across 82% of its surface, no license required. One of those is the good kind of unstoppable and 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













