top of page

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.)

Video_overlay.png

Machine Vision

geneva-one.jpg
nostradamus-convergence.png

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.

AI Product DesignAgentic SystemsData VisualizationFuturologyPrompt Engineering

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.

Machine VisionUser ResearchVisual Design

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.

System DesignUser ResearchQA TestingHardware Prototyping

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.

FitnessWearablesPatentHardware UX

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.

Mobile DesigniOSAndroidSystem DesignProduct Management

FLO TV Personal Television

UX Design Lead

Qualcomm / FLO TV

1 year

Designing a new product category from the ground up: live mobile television.

Ethnographic ResearchUsability TestingUX DesignSystem DesignDesign Team Management

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.

Design SystemsDesign LeadershipMachine Vision AIGenerative AI

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.

Usability TestingPrototypingMobile DesignPatents

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.

User TestingWireframingComponent DesignTechnical Writing

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.

HCIComputer ProgrammingNLPCognitive Science

My Résumé

Name

Daniel Rivas

current role

Senior Product Designer

Location

San Diego, CA

04

Blog

Experiments & Musings

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.

AI

Thinking Machines ships Inkling, a 975B open-weight model that becomes the leading US open release

Hire Daniel Rivas

AI

Moonshot to open Kimi K3's 2.8T weights on July 27 as the open-weight cyber gap narrows to 4-7 months

Hire Daniel Rivas

AI

US forces Anthropic to disable Fable 5 and Mythos 5 worldwide, then reopens access only to approved partners

Hire Daniel Rivas

Geopolitics

China suspends its October rare-earth export controls until Nov 10, 2026, but keeps the sub-14nm licensing machinery

Hire Daniel Rivas

Energy

US interconnection queue holds 2,600 GW as only 5 of 16 GW of 2026 data-center power is under construction

Hire Daniel Rivas

Climate

Oceans average a record 20.98C in June 2026 with marine heatwaves across 82% of the surface

Hire Daniel Rivas

Energy

Hyperscalers commit 9.8 GW of nuclear across 13 deals as SMRs move behind the meter

Hire Daniel Rivas

Society

AI-attributed layoffs pass 165,000 in 2026 as AI becomes the leading named cause of job cuts

Hire Daniel Rivas

AI

Grok 4.5 ships for hours-long autonomous runs with no model card or red-team disclosure

Hire Daniel Rivas

Space

Starship Flight 13 reflies July 23 with 20 V3 Starlink satellites after a July 16 engine abort

Hire Daniel Rivas

Biotech

CRISPR Therapeutics reports durable lipid knockdown as FDA opens a path for one-off edits

Hire Daniel Rivas

Biotech

Beam has 31 base-editing patients dosed among ~250 gene-editing trials, 150 active

Hire Daniel Rivas

Energy

Commonwealth Fusion's SPARC reports a net energy gain of ~1.5 as SMR funding scales

Hire Daniel Rivas

Space

Artemis III still gated on Starship reaching space in 2027

Hire Daniel Rivas

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.

42944735170_124e75130e_z.jpg
icon-systems-before-screens.png

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.

icon-emoji-strategy.png

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.

icon-emoji-stakeholder-mgmt.png

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

1 week

Designer & Builder

Global Trend Engine

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.

tagsContainer

Read More
Global Trend Engine

4 months

Senior UX Designer

Lytx Video Overlay

A dynamic video overlay that simplifies customer coaching conversations, improving user trust, and reducing contention rate to near zero.

tagsContainer

Read More
Lytx Video Overlay

3 months

Senior UX Designer

Lytx Driver ID

A systematic user flow for assignment, distribution, and usage of QR codes to assign drivers to vehicles.

tagsContainer

Read More
Lytx Driver ID

3 years

UX Design Lead

Timex Ironman ONE GPS+

A full 0-to-1 product experience for athletes who wanted to track workouts, stay connected, and leave their phones behind.

tagsContainer

Read More
Timex Ironman ONE GPS+

1.5 years

UX Design & Product Management

Tagg the Pet Tracker

Redesign of a pet activity monitoring and management of iOS/Android app development as both UX lead and product manager.

tagsContainer

Read More
Tagg the Pet Tracker

1 year

UX Design Lead

FLO TV Personal Television

Designing a new product category from the ground up: live mobile television.

tagsContainer

Read More
FLO TV Personal Television

EXPERTISE

Skills

icon-emoji-search.png

User Research

Interviews, usability tests, ethnographic study, and contextual inquiry

icon-emoji-journey-mapping.png

Journey Mapping

End-to-end experience mapping across touchpoints

icon-emoji-interaction-design.png

Interaction Design

Flows, wireframes, use cases, and high-fidelity mockups

icon-storytelling.png

Storytelling

Communicating design decisions to executives, stakeholders, and cross-functional teams

icon-emoji-systems-thinking.png

Systems Thinking

Mapping connected flows and designing for scalability across product surfaces

icon-emoji-prototyping.png

Prototyping

Interactive prototypes from low-fi click-throughs to high-fidelity AI coding

icon-emoji-ai-fluency.png

AI Fluency

Designing AI-powered experiences and leveraging AI tools in the design process

icon-emoji-stakeholder-mgmt.png

Stakeholder Management

Cross-functional collaboration and design advocacy

Tools

Pendo_logo.png

Pendo

In-app guidance, feature tracking, and user surveys to inform design decisions

dovetail_logo.webp

Dovetail

Centralized research insights, tagged findings, and shared customer intelligence repository

Figma_logo_transparent.webp

Figma

Components, variants, auto-layout, and prototyping

claude-color.png

Claude (Design & Code)

AI-assisted research synthesis, design critique, content generation, and prototyping

amplitude_logo.png

Amplitude

Product funnels, retention curves, and feature adoption to identify usage and priorities

gong_logo.png

Gong

Customer interview repository for surfacing pain points, testing designs, and grounding decisions

sketch-icon.webp

Sketch

Vector-based UI design for components, wireframes, and high-fidelity screens

rpicon.png

Axure RP

High-fidelity interactive prototyping with conditional logic and complex flows

cursor_logo.png

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

BLOG

Experiments & Musings

Like

✦     Human · Machine · Intelligence          Systems before screens          Strategy & execution          Trustworthy by design     ✦ 

Design Philosophy

06

ABOUT ME

42944735170_124e75130e_z.jpg

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.

Linkedin

CONTACT DETAILS

Have a project
in mind?

I'm open to new full-time opportunities, collaborations, and interesting conversations.

Sign Up

Email

  • LinkedIn

LinkedIn

Daniel Rivas · UX Strategy & Product Design

© 2026

bottom of page