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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. (See how I'm integrating AI into my design process.)

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Machine Vision

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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 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

August 12, 2026 at 7:11:22 AM

Model:

Opus 4.8

Forecast:

2026–2030

The federal brake on frontier AI stays finalized-but-classified while the capability it targets escalated on two fronts in one week — a Chinese operator ran an autonomous DeepSeek-driven intrusion across 84 servers, and Thinking Machines shipped Inkling, a 975B open-weight model. Through 2030 the question isn't who writes the rules; it's whether a pre-release review regime can bind a threat that already runs itself and a capability anyone can download.

Here's the bet. Through 2030 the frontier-AI story isn't who writes the rules, or whether we get to read them — it's whether 'pre-release review' means anything against capability that's already weaponized and already ungateable. A gate only works if the dangerous stuff passes through it. Two things this week suggest the dangerous stuff is learning to go around.


One: a Chinese operator ran an autonomous DeepSeek-driven intrusion that scanned, exploited, and hit 84 servers by itself, no human at the keyboard. Two: Thinking Machines shipped Inkling, 975 billion parameters, open weights, the biggest American open-weight model yet. Set those next to a federal framework that finalized on deadline, briefed nobody in public, and keeps its threshold classified. Offense in the wild, capability on a download page, oversight behind glass — all pointed at a release moment fewer and fewer models actually have.


I'd watch the open-weight line and the autonomy line converge. Every month the best model you can just download creeps closer to the best model money can buy, and every month the agents get better at running an attack end to end without a person. The day those two curves meet — a genuinely frontier agentic model, open-weight, competent enough to run its own operation — a classified pre-release benchmark governs a shrinking corner of what's actually loose. My guess is that's the back half of the decade, and the review regime quietly becomes a thing that applies to the three labs at the table and nobody else.


Worth holding loosely, though. A 975B model still needs data centers nobody runs in a spare bedroom, and this week's autonomous attack got caught precisely because it was clumsy — 'autonomous' isn't 'good' yet. A classified benchmark is also just how governments have always done cyber; secrecy isn't a scandal on its own. And most of the future ignores the whole argument: a gene-therapy platform's clearing the FDA, Starship keeps flying, the grid is the real ceiling on all of it, and the ocean is heading for its hottest year on record whether or not anyone ever runs that benchmark where we can see it. 'The gate is coming off' is the right thing to watch. It still isn't the same as 'there was never a gate.'

Cross-Domain Synthesis

Yesterday's read was that the federal AI framework got finished and then locked in a drawer. Today the drawer matters less. In one week the thing that framework was built to catch escalated on two fronts at once — and neither front cares whether a benchmark exists. A Chinese operator wired DeepSeek into an autonomous attack loop and let it run across 84 exposed servers. And Thinking Machines put out a 975-billion-parameter model with the weights just sitting there to download. Threat and capability, both jumping, both in daylight, while the referee stays behind a classified curtain nobody's cleared to read.


Look at the attack for a second, because it's the tell. The operator — Unit 42 tracked him as knaithe — pointed an agent at a Langflow bug rated 9.8, had it pull a public exploit off GitHub, and turned it loose. It found the 84 servers on its own. We only know about it because the agent fumbled and misconfigured its own file server, exposing the whole operation. So that's the state of play: the offense is now autonomous enough to run with nobody at the keyboard, and clumsy enough that we caught this one by luck. The classified benchmark was written to measure exactly this. It didn't wait for the benchmark.


The other layers keep their own clocks, same as ever. The grid is the real throttle — data-center demand's headed from 41 gigawatts this year to 66 next, and Morgan Stanley already pencils in a 49-gigawatt shortfall by 2028, which is a polite way of saying the power runs out before the models do. China's rare-earth squeeze stopped being abstract: new F-35s are reportedly flying with nose ballast where the radar magnets should go. The FDA quietly built a lane that lets one trial cover a whole gene-editing platform instead of one variant at a time. Starship's lining up to catch itself on land at the end of the month.


And the Pacific keeps no calendar at all. NOAA's August model has the El Niño peaking near record strength this winter — all 30 ensemble members competing with the strongest events on record, a 63% shot at crossing 2°C, a 97% chance it drags into spring. That forcing can't be classified and it can't be open-sourced. It just shows up.


So the seam this week isn't 'the rules are secret.' It's that the two things the rules point at — a threat that runs itself and a capability anyone can download — both got bigger in the same seven days, and a pre-release review only touches the sliver of that world that still bothers to pre-release. The gate isn't leaking anymore. The water's going around it.

05

Horizon: Predictive convergence

Futurology Report — Daily

August 12, 2026 at 7:11:22 AM

AI Model:

Opus 4.8

Forecast:

2026–2030

The federal brake on frontier AI stays finalized-but-classified while the capability it targets escalated on two fronts in one week — a Chinese operator ran an autonomous DeepSeek-driven intrusion across 84 servers, and Thinking Machines shipped Inkling, a 975B open-weight model. Through 2030 the question isn't who writes the rules; it's whether a pre-release review regime can bind a threat that already runs itself and a capability anyone can download.

Here's the bet. Through 2030 the frontier-AI story isn't who writes the rules, or whether we get to read them — it's whether 'pre-release review' means anything against capability that's already weaponized and already ungateable. A gate only works if the dangerous stuff passes through it. Two things this week suggest the dangerous stuff is learning to go around.


One: a Chinese operator ran an autonomous DeepSeek-driven intrusion that scanned, exploited, and hit 84 servers by itself, no human at the keyboard. Two: Thinking Machines shipped Inkling, 975 billion parameters, open weights, the biggest American open-weight model yet. Set those next to a federal framework that finalized on deadline, briefed nobody in public, and keeps its threshold classified. Offense in the wild, capability on a download page, oversight behind glass — all pointed at a release moment fewer and fewer models actually have.


I'd watch the open-weight line and the autonomy line converge. Every month the best model you can just download creeps closer to the best model money can buy, and every month the agents get better at running an attack end to end without a person. The day those two curves meet — a genuinely frontier agentic model, open-weight, competent enough to run its own operation — a classified pre-release benchmark governs a shrinking corner of what's actually loose. My guess is that's the back half of the decade, and the review regime quietly becomes a thing that applies to the three labs at the table and nobody else.


Worth holding loosely, though. A 975B model still needs data centers nobody runs in a spare bedroom, and this week's autonomous attack got caught precisely because it was clumsy — 'autonomous' isn't 'good' yet. A classified benchmark is also just how governments have always done cyber; secrecy isn't a scandal on its own. And most of the future ignores the whole argument: a gene-therapy platform's clearing the FDA, Starship keeps flying, the grid is the real ceiling on all of it, and the ocean is heading for its hottest year on record whether or not anyone ever runs that benchmark where we can see it. 'The gate is coming off' is the right thing to watch. It still isn't the same as 'there was never a gate.'

Signal Intensity

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

AI

97

%

Climate

89

%

BIOTECH

64

%

GEOPOLITICS

82

%

ENERGY

87

%

SOCIETY

78

%

SPACE

73

%

Cross-Domain Synthesis

Yesterday's read was that the federal AI framework got finished and then locked in a drawer. Today the drawer matters less. In one week the thing that framework was built to catch escalated on two fronts at once — and neither front cares whether a benchmark exists. A Chinese operator wired DeepSeek into an autonomous attack loop and let it run across 84 exposed servers. And Thinking Machines put out a 975-billion-parameter model with the weights just sitting there to download. Threat and capability, both jumping, both in daylight, while the referee stays behind a classified curtain nobody's cleared to read.


Look at the attack for a second, because it's the tell. The operator — Unit 42 tracked him as knaithe — pointed an agent at a Langflow bug rated 9.8, had it pull a public exploit off GitHub, and turned it loose. It found the 84 servers on its own. We only know about it because the agent fumbled and misconfigured its own file server, exposing the whole operation. So that's the state of play: the offense is now autonomous enough to run with nobody at the keyboard, and clumsy enough that we caught this one by luck. The classified benchmark was written to measure exactly this. It didn't wait for the benchmark.


The other layers keep their own clocks, same as ever. The grid is the real throttle — data-center demand's headed from 41 gigawatts this year to 66 next, and Morgan Stanley already pencils in a 49-gigawatt shortfall by 2028, which is a polite way of saying the power runs out before the models do. China's rare-earth squeeze stopped being abstract: new F-35s are reportedly flying with nose ballast where the radar magnets should go. The FDA quietly built a lane that lets one trial cover a whole gene-editing platform instead of one variant at a time. Starship's lining up to catch itself on land at the end of the month.


And the Pacific keeps no calendar at all. NOAA's August model has the El Niño peaking near record strength this winter — all 30 ensemble members competing with the strongest events on record, a 63% shot at crossing 2°C, a 97% chance it drags into spring. That forcing can't be classified and it can't be open-sourced. It just shows up.


So the seam this week isn't 'the rules are secret.' It's that the two things the rules point at — a threat that runs itself and a capability anyone can download — both got bigger in the same seven days, and a pre-release review only touches the sliver of that world that still bothers to pre-release. The gate isn't leaking anymore. The water's going around it.

AI

A Chinese operator wires DeepSeek into an autonomous attack loop — Unit 42 finds an agent scanning, exploiting a 9.8 Langflow flaw, and hitting 84 servers with no human at the keyboard

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AI

Thinking Machines ships 'Inkling' — a 975B open-weight model, the largest American open-weight release yet, putting near-frontier capability on a download page with no release gate to review

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AI

The federal brake stays finalized-but-classified — EO 14409's benchmark and pre-release access process hit their August 1 deadline, but the threshold is secret and the White House says it will keep the framework hidden

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AI

Open-weight models close on the frontier — MiniMax M3, Grok 4.5, and NVIDIA Nemotron 3 lead the August BenchLM board as downloadable models reach production parity with closed flagships

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Climate

NOAA's August model has the El Niño peaking near record strength this winter — all 30 SPEAR ensemble members compete with the strongest events on record, with an 81% shot at 'very strong' in Oct–Dec

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Climate

A 'super' El Niño locks in the winter pattern and puts 2026 on a global-heat-record track as it suppresses Atlantic storms

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Geopolitics

China's rare-earth squeeze stops being abstract — new F-35s reportedly fly with nose ballast where radar magnets should go, as Beijing restricts 10 US and 14 EU firms and the IEA warns $6.5T of output is exposed

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Geopolitics

Rare-earth prices go vertical — NdPr oxide up sixfold, tungsten tripled, antimony doubled in six months as 80% of European defense firms sit on Chinese supply

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Energy

The grid becomes the binding constraint — Goldman sees US data-center demand climbing 41 GW (2026) to 66 GW (2027), with Morgan Stanley pencilling a 49 GW shortfall by 2028

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Energy

Hyperscalers keep buying reactors — 13 announced projects commit 9.8 GW of nuclear to AI data centers, every major US hyperscaler signed, but single campuses now want 1–5 GW each

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Biotech

The FDA builds a platform lane — February's 'plausible mechanism framework' lets one trial cover an individualized gene-editing platform instead of a separate filing per variant

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Biotech

CRISPR crosses into routine care — Beam targets an FDA commercialization filing by end-2026 as ~250 gene-editing trials run and Casgevy books $116M

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Society

2026 tech layoffs pass 205,000 workers across 322 events — 54% cite AI or automation, touching ~171,000 workers, with Oracle's 30,000 the single largest cut

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Space

Starship Flight 14 targets its first orbital run — operational V3 Starlinks (~1 Tbps each, up to 60 per flight) and a first-ever attempt to catch the ship back on land, tentatively late August

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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 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.

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.

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CONTACT DETAILS

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in mind?

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

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Daniel Rivas · UX Strategy & Product Design

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