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UX STRATEGY • PRODUCT DESIGN

Research. Strategy. Systems Design. AI.

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.

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Machine Vision

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Wearable

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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.

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

November 8, 2026 at 12:10:37 AM

Model:

Opus 5.5

Forecast:

2026–2028

Permission Is the Bottleneck: Through 2028, Voters, Statehouses and Beijing Set the Pace of the AI Buildout

Here's the bet: through 2028, the pace of the AI buildout gets set by who grants permission, not by who has the capital or the chips. Statehouses, town ballots, Congress and Beijing all showed up as gatekeepers this week, and the money noticed.


The evidence is unusually blunt. About 40% of pending US data-center capacity sits in states whose incoming governors promised to stop or pause construction (Cleanview), on top of 46 local measures and at least 17 outright bans (Bloomberg Economics). Ohio's governor-elect Amy Acton can halt state permitting by executive order once she takes office in January. UBS says about 30% of capacity planned for 2028 is at risk, and the Nasdaq 100 dropped 6.4% on Nov 5. Abroad, roughly 600,000 H200s are parked in Hong Kong waiting on Beijing.


The inflection I'd watch is January, when the new governors are sworn in and the 120th Congress convenes with Democrats holding the gavels. If the first executive orders pause permitting rather than just tighten it, Bloomberg Intelligence's 10GW estimate starts looking conservative. I'd expect most of it to land as prove-it-first conditions instead: tax breaks after delivery, bring-your-own power, no NDAs. OpenAI already moved there on Thursday.


Worth holding this loosely, though. Campaign promises are cheaper than executive orders, and developers can move. GLJ Research says Texas projects without permits will "probably go to Louisiana, Oklahoma or nowhere," and capacity that moves isn't capacity lost. One ugly trading day after an election is a mood, not a forecast. Plenty of those have reversed by the following Friday.

Cross-Domain Synthesis

This week the AI buildout found out who actually holds the keys. Not the chipmakers, not the utilities. Voters, statehouses and, on the other side of the Pacific, a customs office.


Start with Tuesday's midterms. Newly elected governors in Ohio, Georgia, Michigan, New Mexico and Texas campaigned on stopping or pausing data-center construction, and Cleanview's data says about 40% of pending US capacity is planned in states like those. Add 46 local ballot measures that stall development, at least 17 of them outright bans, per Bloomberg Economics. Markets did the math on Thursday: the Nasdaq 100 fell 6.4%, erasing about $2.5 trillion. Bloomberg Intelligence's Mandeep Singh thinks the roughly $1.4 trillion of 2027 AI infrastructure spending shrinks 5–7%, with as many as 10GW failing to come online next year.


Same story at the border, just with a different gatekeeper. Reuters reports about 600,000 Nvidia H200s sitting in Hong Kong while Beijing withholds import approval. Chinese buyers who ordered around 6 million RTX Pro 5500s expect roughly 1% within four months, and Moonshot went shopping for Blackwell capacity in Europe instead. Washington signed off on the export. Beijing's the one saying no. Meanwhile the rare-earth pause legally lapses Nov 10 with no published extension notice, and Summit's ivonescimab, licensed from China's Akeso, gets its FDA decision on Nov 14.


The counter-current: some things don't need a permit. COP31 opens in Antalya on Nov 9 while the CPC puts the odds of a very strong El Niño this winter above 90%. Starship Flight 15 is targeting no earlier than Nov 13, trying to catch both stages for the first time. And a study reported by the Washington Post finds data centers have had only a marginal effect on residential electricity prices, which is awkward for the backlash's favorite talking point.

05

Horizon: Predictive convergence

Futurology Report — Daily

November 8, 2026 at 12:10:37 AM

AI Model:

Opus 5.5

Forecast:

2026–2028

◆ PYTHIA AGENT · 36 TRACKED · 0 RESOLVED

Tracker →

Permission Is the Bottleneck: Through 2028, Voters, Statehouses and Beijing Set the Pace of the AI Buildout

Here's the bet: through 2028, the pace of the AI buildout gets set by who grants permission, not by who has the capital or the chips. Statehouses, town ballots, Congress and Beijing all showed up as gatekeepers this week, and the money noticed.


The evidence is unusually blunt. About 40% of pending US data-center capacity sits in states whose incoming governors promised to stop or pause construction (Cleanview), on top of 46 local measures and at least 17 outright bans (Bloomberg Economics). Ohio's governor-elect Amy Acton can halt state permitting by executive order once she takes office in January. UBS says about 30% of capacity planned for 2028 is at risk, and the Nasdaq 100 dropped 6.4% on Nov 5. Abroad, roughly 600,000 H200s are parked in Hong Kong waiting on Beijing.


The inflection I'd watch is January, when the new governors are sworn in and the 120th Congress convenes with Democrats holding the gavels. If the first executive orders pause permitting rather than just tighten it, Bloomberg Intelligence's 10GW estimate starts looking conservative. I'd expect most of it to land as prove-it-first conditions instead: tax breaks after delivery, bring-your-own power, no NDAs. OpenAI already moved there on Thursday.


Worth holding this loosely, though. Campaign promises are cheaper than executive orders, and developers can move. GLJ Research says Texas projects without permits will "probably go to Louisiana, Oklahoma or nowhere," and capacity that moves isn't capacity lost. One ugly trading day after an election is a mood, not a forecast. Plenty of those have reversed by the following Friday.

Signal Intensity

A domain-level score (0-100) representing the volume and momentum of frontier activity detected across the signals in that domain.

AI

85

%

Climate

80

%

BIOTECH

60

%

GEOPOLITICS

82

%

ENERGY

90

%

SOCIETY

78

%

SPACE

60

%

Cross-Domain Synthesis

This week the AI buildout found out who actually holds the keys. Not the chipmakers, not the utilities. Voters, statehouses and, on the other side of the Pacific, a customs office.


Start with Tuesday's midterms. Newly elected governors in Ohio, Georgia, Michigan, New Mexico and Texas campaigned on stopping or pausing data-center construction, and Cleanview's data says about 40% of pending US capacity is planned in states like those. Add 46 local ballot measures that stall development, at least 17 of them outright bans, per Bloomberg Economics. Markets did the math on Thursday: the Nasdaq 100 fell 6.4%, erasing about $2.5 trillion. Bloomberg Intelligence's Mandeep Singh thinks the roughly $1.4 trillion of 2027 AI infrastructure spending shrinks 5–7%, with as many as 10GW failing to come online next year.


Same story at the border, just with a different gatekeeper. Reuters reports about 600,000 Nvidia H200s sitting in Hong Kong while Beijing withholds import approval. Chinese buyers who ordered around 6 million RTX Pro 5500s expect roughly 1% within four months, and Moonshot went shopping for Blackwell capacity in Europe instead. Washington signed off on the export. Beijing's the one saying no. Meanwhile the rare-earth pause legally lapses Nov 10 with no published extension notice, and Summit's ivonescimab, licensed from China's Akeso, gets its FDA decision on Nov 14.


The counter-current: some things don't need a permit. COP31 opens in Antalya on Nov 9 while the CPC puts the odds of a very strong El Niño this winter above 90%. Starship Flight 15 is targeting no earlier than Nov 13, trying to catch both stages for the first time. And a study reported by the Washington Post finds data centers have had only a marginal effect on residential electricity prices, which is awkward for the backlash's favorite talking point.

AI

Nasdaq 100 falls 6.4% as midterm 'blue tsunami' hits AI trade

Hire Daniel Rivas

Energy

40% of planned US data center capacity is in states wanting to pause

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Geopolitics

600,000 Nvidia H200s pile up in Hong Kong awaiting Beijing approval

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Geopolitics

Nvidia faces congressional scrutiny over AI chip exports

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Climate

COP31 Antalya preview: seven issues to watch, Nov 9–20

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Space

Starship Flight 15 slips a day, now NET November 13

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Biotech

Ivonescimab BLA heads to Nov 14 PDUFA date

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AI

Moonshot AI sought Nvidia chip access in Europe amid US curbs

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Geopolitics

China rare-earth export pause nears Nov 10 expiry

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Climate

CPC: odds of a very strong El Niño this winter above 90%

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AI

Nasdaq plummets toward correction territory

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Energy

OpenAI pledges data center power cuts under grid stress

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Energy

Data centers turn to old jet engines as grid waits grow

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Society

Study: data centers may not be raising bills that much

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Design Philosophy

06

ABOUT ME

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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

Daniel Rivas · UX Strategy & Product Design

© 2026

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