Awarded Most Innovative Project

Awarded Most Innovative Project

Awarded Most Innovative Project

Making async portfolio reviews 3x more efficient for feedback seekers

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TLDR;

Tldr;

problem

The current way of doing async portfolio reviews is broken for feedback seekers (mostly junior designers) because they deal with scattered feedback, confusing low-context feedbacks and manual work of analyzing multiple feedbacks.

solution

Floop allows visual feedback annotation right on the website and hence reduces the low-context confusion for feedback seekers. It offers one place to organize and manage feedback. Moreover, encourages actionable feedback through guided questions.

impact

Helps feedback seekers manage and organize feedbacks 3x more efficiently.

my role

0->1 design (research + validate + visuals) of this tool, prototyped and implemented with Lovable.dev AI tools.

Storytime

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You send someone your portfolio to review and they reply with either

OR

You’re left guessing:
What part looked good?
What part didn’t?
What should I change?

Meanwhile, the feedback is scattered across

It’s inefficient. It’s frustrating.

It’s inefficient. It’s frustrating.

uughh

That's where floop loops in

It's a simple, structured way to get and give portfolio feedback. It keeps everything in one place, ties comments to exact sections, and lets reviewers know what kind of feedback you’re looking for.

Process

Design approach

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initial assumption

Understanding 'where' of the feedback during async portfolio reviews is confusing.

Tested assumption

20

Interviews confirmed that there exists efforts for reviewers as well as feedback seekers. But it also revealed few more challenges.

Problem themes

03

Lack of context

Lack of direction

Lack of organization

process, decision & skills
  • Created semi-structured interview protocol.

  • Conducted interviews.

  • Coded (thematic analysis) the interviews and found overlapping challenges.

  • Categorized the overlapping challenges and found 3 themes.

  • Extracted quotes that can serve as user stories.

how might we

Get more quality feedback to the seekers and help them manage them

hmw

hmw

Design and rationale

feature #1

Annotation reduces confusion of context

The need

"

Over text, mentors gave 1–2 lines per question. For visuals, they’d say, 'This isn’t working,' but no screenshots.

~ Design student

14/20

Feedback seekers mentioned that interpreting where the feedback is meant for is confusing.

impact

2x

reduces confusion felt by feedback seekers in understanding low-context feedbacks.

design rationale

Feedback annotations solves the issue of location ambiguity in portfolio reviews. Annotation eliminates confusion about feedback placement because it enables direct commenting on specific interface elements.

It also reduces time spent on clarification, creating a more efficient review experience for both reviewers and feedback seekers.

feature #2

All feedbacks in one place reduces the pain-point of managing scattered feedback

The need

"

Notes scatter across physical books/digital apps...I often forget feedback

~ Design student

16/20

Feedback seekers mentioned that they find it difficult to manage and organize feedbacks.

impact

3x

more organized feedback than previously.

design rationale

In the current system, feedback seeker has to do all the work of keeping all feedbacks in one doc or one figma or organize them, but UrL automatically does that.

feature #3

Summarizing multiple feedbacks with AI

The need

If it's easier to give feedback, quantity and quality of feedback increases and hence there comes the need for better organization and management.

impact

2x

better in analyzing areas of improvement.

design rationale

Even though UrL makes it easier to organize feedback, AI summary would give junior designers an opportunity to see what similar themes of feedback are generated.

This helps them to understand what higher level improvements need to be done in the portfolio with the help of AI.

feature #4

Save feedback that aligns to implement later

The need

"

I filter constructive feedback (with alternatives) vs empty criticism.

~ Junior designer (2 YOE)

15/20

Feedback seekers filter out feedbacks that does not align with them.

impact

3x

easier to manage feedback you wanna implement later.

design rationale

When a junior designer is swamped with multiple feedback, filtering out what to implement is crucial. Especially, what to implement that resonates with one's goal is crucial. Hence this feature to save something that junior designers wanna implement later.

feature #5

Guiding questions to direct reviewers for better feedback

The need

As a feedback seeker,
I sometimes don’t feel like the feedback aligns with me
because this kind of feedback is not what I wanted.

As a reviewer,
I sometimes get confused
because I don’t know what the person wants feedback on.

impact

2x

more actionable feedback

design rationale

A lot of times reviewers are left hanging to guess what kind of feedback does the seeker want. And on the flip side, seekers sometimes feel that the feedback does not align with what they had in mind.

This is an articulation problem and hence guiding question tries to solve this problem through 3 clear questions that would guide reviewers to give out actionable feedback.

Floop is in development and is estimated to be beta launched by the first week of August 2025!

UrL is in development and is estimated to be beta launched by the first week of July!

Floop won Most Innovative Idea at InnoQuest Innovation competition at Indiana University in April 2025.

It was also selected for top 100 projects in Lovable's hackathon.

Self reflection

Prototyping with Lovable was super fun and useful. I can't believe that I got MVP set up in 2 nights and 100 prompts. The way I got micro ideas to be implemented from the AI prototype was super useful.

Another reflection is, I learned how to showcase the value in terms of outcomes rather than just results. For example, junior designers get confidence through this tool rather than just feedbacks.

Prototyping with Lovable was super fun and useful. I can't believe that I got MVP set up in 2 nights and 100 prompts. The way I got micro ideas to be implemented from the AI prototype was super useful.

Another reflection is, I learned how to showcase the value in terms of outcomes rather than just results. For example, junior designers get confidence through this tool rather than just feedbacks.

Prototyping with Lovable was super fun and useful. I can't believe that I got MVP set up in 2 nights and 100 prompts. The way I got micro ideas to be implemented from the AI prototype was super useful.

Another reflection is, I learned how to showcase the value in terms of outcomes rather than just results. For example, junior designers get confidence through this tool rather than just feedbacks.

Prototyping with Lovable was super fun and useful. I can't believe that I got MVP set up in 2 nights and 100 prompts. The way I got micro ideas to be implemented from the AI prototype was super useful.

Another reflection is, I learned how to showcase the value in terms of outcomes rather than just results. For example, junior designers get confidence through this tool rather than just feedbacks.

If you are a designer who has feedback on this tool, reach out to me and I would love to talk about it.

Hit me up to talk about this project over a cup of chai!

How did I AI prototype?

How did I AI prototype?

How did I reach out to designers?

How did I reach out to designers?

What inspired you to create this tool?

What inspired you to create this tool?

Copyright © 2025 Dharam Lokhandwala. Updated in January 2025.

Copyright © 2025 Dharam Lokhandwala.

Updated in January 2025.

Process

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