PROJECT 01

Jul 2025 – Aug 2025

MICROSOFT MONETIZE · INVESTOPEDIA

Publisher

agents

An in-site agentic layer that keeps readers on the page, and makes ads feel useful instead of noisy.

AI-native Design

Interviews

Wireframing

Prototyping

Impact

$1.4M revenue

projected for client

ROLE

Product Designer

TIMELINE

Jul 2025 – Aug 2025

TEAM

Mentor, PM, Engineer, Data scientist

CLIENT

Investopedia

Cover.jpg

Agentic layer

Personalization

Anticipates what you need

Ad delivery

Tailored ads

Earned, not imposed

Personalization

Curated feed

Tailored to reading history

01 PROBLEM

Modern-day readers are frustrated by the

wall of irrelevant ads

and long articles

Publisher websites were still valuable, but the experience often felt cluttered and effort-heavy. Readers had to navigate dense pages, intrusive ads, pop-ups, and scattered recommendations before getting to what they actually needed.

Fig-01.jpg

A sample of Investopedia article and category pages surveyed for ad density and layout friction.

Fig-02.jpg

Screenshot of LLM chat bot screens like ChatGPT and Perplexity

That means fewer clicks, shorter sessions, and

falling revenue

for

publishers

For publishers, this created a direct tension. The more users relied on external AI summaries, the less time they spent on-site — reducing sessions, ad impressions, and monetization opportunities.

Impact.jpg

Business-impact diagram or session drop.

02 INTERVIEWS

from readers

They wanted content that felt

personal, easy

and

proactive

I interviewed 12 people who regularly consume content across lifestyle, finance, technology, travel, and food. The goal was to learn how they discover, read, trust, and use AI alongside publisher content.

Across interviews, readers wanted less effort and more relevance. They valued content that helped them decide quickly, surfaced useful next steps, and felt tailored without becoming overwhelming.

Research.jpg

12

Participants who read publisher sites at least a few times a week

5

Topics: fashion & lifestyle, cooking, technology, travel, and finance

100%

Had used AI tools in some capacity. Most of them use ChatGPT.

03 COMPETITIVE ANALYSIS

the system

AI-native platforms are becoming

more adaptive

Secondary research showed that AI-native platforms were already changing user expectations. Instead of making users browse static pages, these experiences responded to intent, context, and preferences in real time.

  • Spec-03.jpg

    Perplexity

    Describe, then compare

    Users can say what they’re looking for, and Perplexity helps compare relevant options.

  • Spec-02.jpg

    YouTube

    AI along the journey

    Chat on videos, summaries under videos, and overviews on search — not a single isolated feature.

  • Spec-01.jpg

    Amazon Rufus

    Integrated everywhere

    Chat in the nav, review summaries, and audio highlights for the product — available throughout the app.

04 DIRECTION

The same website,

personalized

to each user

They wanted the website to understand what they were trying to do and help them get there faster.

So I explored an AI-native publishing experience where the site more responsive to user needs. Instead of treating every reader the same, it could adapt to intent, summarize long articles in their proficiency level, surface relevant context, and introduce ads when they are useful.

The same article or homepage no longer had to look the same for every reader.

Traditional.jpg

05 SOLUTION

click through it

Product

walkthrough

Penny learns intent, keeps the brand’s voice in the recirculation, and only introduces sponsored solutions when they help. Same site, different readers.

Feature 01

Flow-01.jpg

Summarizes the article so the users knows what they're getting into

Feature 02

Flow-02.jpg

Tailored and curated content, from customizing the homepage to making a special tailored reading list

Feature 03

Flow-03.jpg

A reading list and tailored insights from prior activity and conversation.

Feature 04

Flow-04.jpg

Sponsored solutions in context — ads that feel useful instead of disruptive.

06 OUTCOME

outcome.md

what changed

Penny created value across

the entire

publishing ecosystem

Penny turned AI into an in-site assistant that benefited every side. Readers got more relevant content and useful solutions, publishers gained engagement and commission opportunities, and advertisers reached users with better context.

Impact

$1.4M/yr revenue

projected for Investopedia

Ecosystem.jpg

07 EXPERIENCE

experience.md

what I learnt

Focusing on the

bigger picture

became just as important as the details

Prioritization

Tight timelines made it obvious: focus on the ideas that created the most impact, instead of trying to solve everything at once.

Feedback

Asking better questions in critiques and feedback sessions helped avoid assumptions and move forward with a clearer direction.

Keep exploring my work!

PROJECTS

Let's Talk

I'm most energized by projects where I can dig into complex problems, collaborate with smart people, and ship things that genuinely improve someone's day.

Watching

Love Island 🤪

Off Campus

Cooking

ratatoille

Avacado Toast

Biryani

Made with <3 by

Reet

Oberoi

Comment

Reet Oberoi

Open to full-time roles, and interesting conversations about hard design problems.

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