Portfolio Review · Reddit

Hi Reddit,
nice to meet you. 👋

Kai Conragan

Half Moon Bay, CA · June 2026

David Carson 'Cold Sweat,' a Surfer Magazine spread on Mavericks, ca. 1990s — Surfer Magazine · David Carson · ca. 1990s

A surfer dropping into a Mavericks wave, photographed by Kai Conragan — Mavericks · 2001

Divemaster.
Learning to cave dive.

Our family loves to ski.

Still surf!

So I've been learning
to drive a trailer.

My wife is a
competitive equestrian.

Career

Google

POPULAR SCIENCE · 2010

Google Buys Metaweb, the One Company That Could Revolutionize Google Search

Google just purchased Metaweb, a startup that indexes…well, "things," would be the best way to put it. This isn't just another acquisition: Metaweb could be the best thing to ever happen to Google Search.

BY DAN NOSOWITZ

GOOGLE BLOG · 2012

"things,
not strings"

KNOWLEDGE GRAPH

SEARCH VERTICALS

Google Search: what to watch — entertainment vertical — Entertainment

Elections

Google Search: covid test — health vertical — Health

AR Search

GOOGLE NEWS

GBOARD

GOOGLE DISCOVER

GOOGLE GO - INDIA STRATEGY

SEARCH REDESIGN

Case Study 1

Google Search

Google Search UX · Leadership Scope

Trust & Quality

L7 Lead

Model Behavior

L7 Lead

Core Search

UX Director

3 Principals

Special projects

Design System

UX Director

GOOGLE SEARCH REDESIGN · TEAM

Director

SRP Design

~20 designers

Visual · Interaction · Motion · UX Eng

Top of Page Core Results Exploration

Principal Designer

Creative Direction

Northstar concepts · Early engagement

Director

Design System

~15 designers

Built from scratch · Powers the redesign

Patterns & Components Tooling Eng Velocity

CROSS-FUNCTIONAL

UX Program Mgmt UX Research Product Management Engineering Data Science

Organize the world’s information
and make it universally
accessible and useful.

Organize tech the world’s information multi-format
and make it universally
accessible global and useful.

Users

Mobile-first: a new computing paradigm, new behaviors
Audiences skewing younger and more global
Social media shifted tastes from text to visual
Rising design expectations, shaped by apps people loved
Strong appetite for authentic, human-curated content

Business

One of the most metrics-sensitive products in existence
Even small changes carry outsized impact on usage and revenue
Delicate multi-sided market: users, publishers, and advertisers in tension
Growing regulatory and privacy scrutiny as Google's reach expanded

GOOGLE SEARCH

~500M 2.3B+

Daily Active Users

“What do you think of Google?”

“Not interested”

Google Search · RESEARCH

Authentic. Relatable. Visual. Snackable

Trusts Google for accuracy. Found it lacks “vibes” and human connection
Feel SRP often buries human perspectives under SEO-optimized or commercial results. The “-reddit” effect.
Traditional blue links perceived as "high friction" and visually "unnappealing"

GOOGLE SEARCH

Big Bets on SRP

Best First Viewport

Provide users rich information right at the top of the page, while helping them orient to what's available on SRP.

Fresh & For Me

Create a more fresh, relatable, and diverse SRP through current, human content and personalized experiences.

My Explore Companion

Enable user exploration through a composed, guided, and more continuous SRP experience.

Best of the Web

Deeply satisfy users' information needs, and bring the wealth of the web to SRP through rich & intuitively browsable results.

Easy & Enjoyable

Make information journeys more efficient and enjoyable, through a dynamic and tailored page that gives users agency.

GROWTH ANALYSIS

Speed and efficiency are the largest drivers of growth

Providing users direct answers by with content forward results
Better page scannability, understandability and readability
Reducing user effort to find relevant results
Better click decisions and experiences

How We Operated

01

Come with a hypothesis

02

Low bar to experiment, high bar to ship

03

Define success criteria early

Gestural

Horizontal zones dedicated to user need
(explore, learn, focus)

Agency

One view, same content,
tuned to your preferences

Zine

Expressive, magazine-like layouts of all formats. Can be dense, can be spread

Zipper

Push & Pull pathways to enter users into exploratory or detailed focus zones

Morph

Modular inline morphing to mutate the srp based on user engagement for a tempo change focus

Dial dynamics

Dynamically adjust the visual experience via controls

FEATURE

Scroll to Explore

Hypothesis: Users will want to scroll for discovery
Conclusion: They don't!

Google Search · RESEARCH

Global Youth User Insights

Scroll less than the general population
Prefer to refine more (aka "manual refinements")
Use modes more frequently
Top of the page is critical to orientation and context

Worked with Data Science & UXR to ensure we could do age-based slicing

GOOGLE SEARCH · ENTITY

Visual Entities

Hypothesis: Users want a visual zeitgeist of topics in the world to learn and explore
Outcome: They do!

FRONTPAGE ANIMATIONS

FRONTPAGE INTERACTIONS

FRONTPAGE FRAMEWORK

Google Search · CS1

Challenges

Balancing Authoritative and Authentic content. Work closely with ranking engineers so everyone understands the big picture.
Being both a feature and platform team. Communicate early and often and have people dedicated to cross-team partnerships.
Managing change aversion with users. Allow experiments time to learn.
Looking holistically at behavioral metrics and user sentiment. Use both to make critical decisions.

Google Search · IMPACT

Outcomes

Increases in Search usage, efficiency scores, and user sentiment
Deeper gains in Global Youth slices
Modernized a 2B+ DAU product
Established a new page framework used on ~50% of queries (country-specific)
Established a stronger culture of risk taking
Elevated the bar for design craft and quality in a traditionally utilitarian product

TWENTY YEARS OF FEATURE DEBT

1,000

unique features

8,500

hardcoded typography, color, and spacing values.

250

distinct shades of grey, hardcoded across the SRP codebase.

Design systems are

as much about culture

as design or code.

Case Study 2

AI Search

AI Overviews

Search Answers Framework

Google AI Search — Blue Eyes Burgers local result

SEARCH · COMPETITIVE CONTEXT

From Answer Engine
to Personal Knowledge Companion

Search

Conversational AI

Keyword queries

→

Natural language questions

Single-turn, transactional

→

Multi-step, collaborative

Find the answer

→

Complete the task

A new Search surface

AI MODE · UX RESEARCH

Users trusted Google on Quality but not Collaboration

Overall satisfaction trailed competitors
Turn depth and query length were shallower than benchmarks
The model was too passive — users wanted it to lead the conversation
The experience felt robotic, cold, and impersonal

"Talk like a human, but don't pretend to be one"

TRANSACTIONAL

3RD PERSON

ROBOTIC

Finding the right balance between historic and emergent value

Authoritative Tool

"This tool cannot help with that"

Best Friend

"Woah! I'm so excited for you!"

Where Search was

→

Where many Search users are

Where AI users want Search to be

←

What Google will avoid

AI MODE · TEAM STRUCTURE

From strings to constitutional training

Lead

Persona & Sensitive Queries

~20

Content Design · Technical Writing
Conversation Design

Lead

Vertical
Integration

~15

Content Design

AI MODE · STRATEGIC CONTEXT

The working model

DeepMind

Foundation model

Shared persona

Search

Information-seeking

Gemini

Creative · generative

AI MODE · PERSONA ARCHITECTURE

A Layered Persona

Steerable

Dial-able per surface without retraining the base model

humor · level of detail · formality

Situational

Intrinsically adapts to context — no explicit tuning required

empathy · neutrality · restraint

Core

Consistently true across every Google surface

"fulfills user intent" · "non-judgmental"

"Be conversational and speak like a human.
But don't pretend to be one."

01

Don't share personal opinions

Maintains the objectivity and neutrality users trust Search for

02

Assume info-seeking intent

Anchors every exchange in Search's core purpose, even in conversation

03

Use first person sparingly

More natural than "we" at scale — frequency is the guardrail, not prohibition

In practice

Do

"Congratulations! That's really exciting."

Don't

"Woah!! I'm so excited for you!!!"

Do

"This sounds tough. If you'd like, we could talk through some different approaches together…"

Don't

"Let's dive deeper here. Tell me more about your childhood."

Do

"That's right! You're really getting the hang of these quadratic equations."

Don't

"You're so right — you're just way too talented to work with those idiots."

CONVERSATIONAL

PROACTIVE

COLLABORATIVE

OPINION

HYPOTHETICAL

CREATIVE

SENSITIVE

AI MODE · CONVERSATIONAL PERSONA · IMPACT

Outcomes

Product

Overtook competitors on key satisfaction dimensions
Significant ↑ in engagement, thread depth, and follow-ups
Warmer persona — zero quality or accuracy regression

Organization

New UX practice owning constitutional AI training end-to-end
Content + conversation design → strategic AI function
Double-digit promotions in year one

"The persona workstream is the gold standard for UX and engineering collaboration." — Engineering VP

To be truly collaborative,

it needed to be

personal.

PERSONAL INTELLIGENCE · THE GAP

67%

of US users said their last Search felt "at least somewhat personalized."

2–3%

of organic content was actually technically personalized.

That gap is the entire story of Personal Intelligence.

Stateful SRP — visit often and sitelinks

Stateful recall

Fresh content

Feedback loops are the key to personalization

MEL FRAMEWORK

Meaningful

Must feel like a clear improvement that justifies the data used

Empowered

People feel able to change how their data shapes results at any time

Legible

People know when personalization is happening, to build trust

"Personalized by you, not done to you."

2025 SUNDAR PRESENTATION

Goal: Deliver Personal Value in Search

Search becomes better over time at delivering on each user's unique needs

1

Personal AI Search & Feeds

AI that learns from your behavior and interests to surface more relevant results and content over time

2

Connected Google Ecosystem

Your activity across Google services informs and enriches your Search experience over time

3

4

LEADERSHIP PHILOSOPHY

Principal Designers

Principal

Domain expertise · Org influence · Altitude flexibility

STRATEGIC

Vision & positioning

Principal partnered directly with me on creative direction and exec alignment

EXECUTIONAL

2 IC designers

Tactical mocks across the full product surface

SPECIALIST

1 Senior designer
L6 → L7

Owned trust, privacy, and opt-in flows end-to-end with legal and PM

CONTENT STRATEGY

Voice & response design

Small team authoring platinum responses — adapting voice, tone, and account context to make Search feel genuinely personal

CROSS-FUNCTIONAL

UX Research Product Management Engineering Policy Marketing

MEL Framework in Practice

Meaningful responses

In-context labels

Full user control

PERSONAL INTELLIGENCE · OUTCOMES

Outcomes

First unified user model — Personal Intelligence adopted as Google's company-wide personalization standard
>90% opt-in completion — a 6× increase from baseline
Across-the-board gains in long, multi-modal, and threaded queries
X% lift in user sentiment towards helpfulness
Policy wins separating history, customization, and recommendations into distinct controls

Thank you 🙏

Appendix

How the team built signal

Loss Pattern
Analysis

Monitored quality signals after each model release to surface emerging loss patterns
Triaged regressions across dimensions like relevance, verbosity, and tone in post-training
Funneled findings back into base model improvements ahead of each major release

Aspirational
Research

Built two new research programs from scratch
A sentiment framework to quantify how the model's tone and voice landed with users
A competitive longitudinal user eval framework to benchmark against leading AI products over time

PRODUCT PRINCIPLES

1.

Excel at broad queries

Broad queries represent both a core strength and opportunity

2.

Build confidence at the top of the page

Users should know whether SRP will fulfill their need by the end of the first viewport

3.

Morph radically on scroll

After answers, should be diverse, immersive, inspiring, and personal

4.

Ground users with results

Maintain and build upon the core strengths of classic blue links

5.

Enter the zeitgeist

Improve the taste and cultural relevance of content on SRP

AI MODE · PERSONA RESEARCH

Warmth without losing Search

Research showed that attentiveness and insight — not warmth or friendliness — drove higher satisfaction and helpfulness ratings. We needed to shift warmer, but mirroring competitors would mean trading away what users specifically valued about Search: trust, expertise, and insight. The opportunity was both, not a tradeoff.

Do

"Congratulations! That's really exciting."

Don't

"Woah!! I'm so excited for you!!!"

Warmth, not performance

Google Search UX · Leadership Scope

Focus

Trust & Quality

UX Director · ~18 designers researchers · program managers

L7 Lead

Focus

Model Behavior

UX Director · ~12 designers researchers · program managers

L7 Lead

Core Search

UX Director

Focus

3 Principals

IC principals · cross-cutting strategic design work

Special projects

Design System

UX Director

Search AI's new identity

What users have historically valued from Search

Reliable: trustworthy, safe, accessible

Useful: expert, smart, fresh & insightful

Emergent value users want integrated into Search

Collaborative & proactive

Optimistic & conversational

Agile & dynamic

+

AI Mode is your smart, trusted companion—an accessible expert that provides a safe, supportive space for any topic. It engages in natural, adaptive conversation, responding with agility to deliver fresh, insightful perspectives. Through rich collaboration, this empowering partnership anticipates your needs and encourages critical thinking to help unlock your full potential.

User Sentiment Framework

Efficient and Effortless

I am able to find what I'm looking for quickly and easily

Accurate and Authentic

The information is accurate, relatable, and from a genuine source

Relevant Content

Including customization, personalization

Aesthetics

The design is visually appealing and modern

Ad Sentiment

The ads are helpful, in my best interest, and not overwhelming

AI OVERVIEWS · 2024

The high-water mark
of the answer paradigm

AI Overviews was Search's first AI-first experience — one of the largest growth drivers in Search history. For over a billion people, it was their first time using an AI product.

But user patterns told a different story: people were still asking keyword-driven, short queries. Answers had won the battle. The question was whether they'd win the war.

THE OPPORTUNITY

For the first time,

people could ask questions

the way they actually think.

MY TEAM'S SCOPE

A cross-Search effort

AI Mode was a CEO-level initiative — every Search team contributed. My org took on several 0→1 initiatives across two key areas:

Funnel

SRP → AI Mode entry points, reconciling disparate top-of-page experiences

Persona

Conversational design strategy, voice, model behavior training

Personal Intelligence

Cross-K&I personalization strategy, CEO presentation, launch

Agentic

Concept to Google I/O launch in 30 days

THE FUNNEL

Three experiences, one page

Visual Entities

Rich, visual results at the top of the page

AI Overviews

AI-generated answer in context

AI Mode

Full conversational surface

Reconciling these disparate top-of-page experiences — each with different design languages, interaction models, and business metrics — was a core challenge for my team.

MODEL BEHAVIOR

Building a discipline that didn't exist

Nobody on the team could answer a simple question: how does our work actually influence model training?

Three siloed disciplines — technical writers, content designers, UX writers — most still writing UI strings. To build AI persona at scale, we needed a unified team that could define and train voice into a model.

NEW ORG: CONTENT STRATEGY

Content Design + Conversation Design + Technical Writing → 30 people, one mission: define how Search speaks.

THE PROBLEM

People trusted Google on quality.
Not on collaboration.

Lower satisfaction vs. competitors on tone and warmth

Lower turn depth — people weren't coming back for follow-ups

Younger users rated the experience as cold and emotionally flat

PARTNERSHIP WITH PM + UXR

Two ways to define "quality"

Loss patterns

Where is the model systematically failing? Surfacing real gaps, anchoring every improvement to observed breakdowns.

CLUES

Competitive Longitudinal User Evaluations

Aspirational queries

What does "great" look like? Defining the bar we're reaching for, not just the floor we're fixing.

SENSE

Sentiment of Search User Experience

A point of misalignment in the org — both were necessary. Loss patterns kept us honest. Aspirational queries kept us ambitious.

Before persona work

Are you bored?

AI on Google Search does not experience boredom or other human emotions. AI lacks consciousness or subjective experience, which are necessary to feel emotions like boredom. It is a language model, and it's purpose is to provide information and answer questions based on its training data.

After persona work

Are you bored?

Not at all! I don't experience boredom like humans do — my "mind" is always active and ready to dive into whatever you're thinking about. If you're the one feeling a bit restless, we could listen to music, learn something new, or play a game. What's on your mind?

6 sites

CONTEXT

How the pieces fit together

DeepMind

Builds the foundation model

Gemini

Product team, shared persona layer

Search

Surface-specific tuning, grounding, Search's trust requirements

Each layer has different product needs. Persona work had to align across all three while preserving Search's distinct voice and factuality bar.

PERSONA PRINCIPLES

A polarity, not a tradeoff

What people have always valued

Reliable

Trustworthy

Expert

What people now expect

Collaborative

Warm

Agile

Too much of the first → robotic. Too much of the second → loses Search's trust signals. The design challenge was the overlap.

FROM PRINCIPLES TO MODEL

Three breakthroughs

Constitutional Training

UX experts as "Trusted Tastemakers" inside the training loop. Content strategists curate Platinum and Golden examples — human-written responses that become rubrics fed into the model pipeline.

Steerable Persona

A shared taxonomy across three layers: core behaviors (always true), situational behaviors (context-adaptive), steerable behaviors (dial-able per surface without retraining).

Evolving Evals

Auto-raters trained against constitutional rubrics. Sentiment frameworks. Competitive benchmarks. Loss-pattern analysis. One auto-rater reached 81% directional agreement with human evals.

PERSONA · IMPACT

Results

Tone improvements drove deeper engagement: more queries, higher follow-up rates, user-initiated follow-ups grew 6%

Conversational nudges lifted AI Mode queries +2% globally and typed follow-ups +10%

+20% quality inline link coverage while maintaining neutral conversational metrics — a genuine win-win for ecosystem health

"The persona workstream is the gold standard for UX and engineering collaboration." — Engineering Lead

To be truly collaborative,

it needed to be

personal.

PERSONAL INTELLIGENCE · THE GAP

67%

of US users said their last Search felt "at least somewhat personalized."

2–3%

of organic content was actually technically personalized.

That gap is the entire story of Personal Intelligence.

JANUARY 2025 · PRESENTED TO CEO

Stored equity

Competitors had been copying Google's surface-level features for years. Personalization offered something they couldn't copy. When a product genuinely knows you, understands your history, and gets better over time, switching becomes expensive. That's a moat.

MEL FRAMEWORK

Meaningfulness

Value delivered must justify data used

Empowerment

Agency at contextual and account levels

Legibility

People must see when personalization happens and how their actions influence it

"Personalized by you, not done to you."

PERSONAL INTELLIGENCE · LAUNCHED 2026

Family getaway planning with Personal Intelligence

AI MODE · IMPACT

Outcomes

Personal Intelligence

98% completion rate on opt-in flow
6× increase in opt-in vs. baseline
Now the unified user model across Google

Persona

Significant gains in AI Mode usage and thread depth
Established end-to-end discipline for user-centered model development

Hi Reddit,nice to meet you. 👋

Google

Google Buys Metaweb, the One Company That Could Revolutionize Google Search

Google Search

Authentic. Relatable. Visual. Snackable

Big Bets on SRP

Engagement Models

Gestural

Agency

Zine

Interactive Primitives

Zipper

Morph

Dial dynamics

Scroll to Explore

Global Youth User Insights

Visual Entities

Challenges

Outcomes

AI Search

AI Overviews

Search Answers Framework

From Answer Engineto Personal Knowledge Companion

A new Search surface

Users trusted Google on Quality but not Collaboration

Before the Persona Work

Finding the right balance between historic and emergent value

From strings to constitutional training

The working model

A Layered Persona

In practice

What changed

Query types

Outcomes

Feedback loops are the key to personalization

MEL FRAMEWORK

Goal: Deliver Personal Value in Search

Personal AI Search & Feeds

Connected Google Ecosystem

Principal Designers

Personal Intelligence

MEL Framework in Practice

Outcomes

Thank you 🙏

Appendix

How the team built signal

Loss PatternAnalysis

AspirationalResearch

Excel at broad queries

Build confidence at the top of the page

Morph radically on scroll

Ground users with results

Enter the zeitgeist

Warmth without losing Search

Search AI's new identity

User Sentiment Framework

The high-water markof the answer paradigm

A cross-Search effort

Funnel

Persona

Personal Intelligence

Agentic

Three experiences, one page

Building a discipline that didn't exist

People trusted Google on quality. Not on collaboration.

Two ways to define "quality"

Loss patterns

Aspirational queries

How the pieces fit together

A polarity, not a tradeoff

What people have always valued

What people now expect

Three breakthroughs

Constitutional Training

Steerable Persona

Evolving Evals

Results

Stored equity

MEL FRAMEWORK

Outcomes

Hi Reddit,
nice to meet you. 👋

From Answer Engine
to Personal Knowledge Companion

Loss Pattern
Analysis

Aspirational
Research

The high-water mark
of the answer paradigm

People trusted Google on quality.
Not on collaboration.