Designpreneur x Parson MPS CD

48hrs AI Design Hackathon

Published on April 13, 2025 | 10 min read

Table of Content

Table of Content

Context

Hackathon Overview

Over the weekend, I had the absolute joy and honor of teaming up with Jolyn Tran and Hye Lynn Suh at the AI Design Hackathon hosted by Designpreneurs Hackathon and Parsons School of Design - The New School. Judge by Han-Shen Chen and Dana Jefferson — visionaries shaping the future of AI at Microsoft and Adobe.

Over an intense 48 hours, we tackled one of the biggest challenges of our time—urban food waste and its impact on climate and biodiversity.

Timeline

48 hours (April 11-13)

Role

UIUX Designer (Vee)

Motion Graphic (Hye Lynn)

UX Research (Jolyn)

Industry

Sustainability & Technology

Skills

User Interview

User Flow

Wireframing

Our Prompt

How might we use AI to mediate between human and ecological needs in urban spaces in the year 2030?

The Problem

People won’t compost if it’s not easy or rewarding

Composting is now required in NYC — but most people find it confusing, inconvenient, or not worth the effort

Without a system that makes composting feel effortless, visible, and rewarding, participation stays low and food waste keeps piling up.

The Solution

What if composting wasn't required… what if it was fun?

Our goal was to make composting feel effortless and joyful while addressing a real urban need in a human-centered way. We weren’t just designing for compliance — we were designing for connection.


This thinking led us to create Posty — an AI-powered compost companion designed to transform food waste into tangible good. Posty is a composting bot designed to roam NYC apartments. It rewards residents for dropping off food scraps, tracks environmental impact, and helps route waste to the right places using AI.

Bluetooth Sync + AI-Powered Experience

Connect your bucky bucket to the app in just a few taps

Compost & Earn

Every time you compost with Posty, you earn points toward real rewards. It’s effortless, trackable, and designed to make sustainable living feel good.

♻️ Compost Calculator & AI Smart Scanner

Snap & Scan: Point your camera at any food or item—our AI tells you instantly if it’s compostable!

Track Your Impact: See how much waste you’re saving from landfills with our compost calculator

JTBD

Starting with NYC

We needed a solution that meets people where they are and make them actually want to compost

Discover

Understanding the problem

Over 1 million tons of food waste each year. And 97% of that goes to landfill or incineration — creating methane, a greenhouse gas over 80x more harmful than CO₂ in the short term.

80x more harmful than CO₂

Methane (CH4): a greenhouse gas far more harmful than carbon dioxide

1M tons

of food waste each year in NYC

97%

of that goes to landfill or incineration

Composting could divert this waste and return it to the local environment, but the systems in place are fragmented and unapproachable. We knew that to design a compelling solution, we had to deeply map the system — understanding not just the technical flow, but the social, behavioral, and emotional bottlenecks.

We realized that with our solution, we can create a circular ecosystem, but with the help of our mentors, we also understood that we needed to heavily narrow down our user narrative.

Define

Understanding our potential users

We visited the Union Square compost drop-off site and met with the Lower East Side Ecology Center. Their staff was passionate, but overwhelmed and underfunded. They wanted to scale, but needed community buy-in and better tools

We also talked with regular New Yorkers, many of whom told us composting felt gross, pointless, or too much work. Their honesty was vital.

"I don’t really care"

"Too much work"

"Too lazy"

“It’s gross”

We also talked with regular New Yorkers, many of whom told us composting felt gross, pointless, or too much work. Their honesty was vital.

Define

Competitors Research

We also benchmarked AI food waste competitors such as Lomi, Winnow, and EvoBin

But none of them offered a joyful, human-centered interaction that changes behavior. Posty isn’t just a bin — it’s a community-powered compost movement, built to scale.

Design

Building our narratives

From these insights, we built a user narrative around Frank — a fictional 26-year-old New Yorker who’s never composted, doesn’t really understand how it works, and doesn’t think it matters. Frank’s perspective helped us design with empathy.

Frank

Frank

Work

Work

Master’s Student

Master’s Student

Location

Location

New York City

New York City

Age

Age

26 | He/hims

26 | He/hims

“If composting is now mandatory in NYC and comes with a fine for noncompliance, why isn’t there an easy way to do it—and actually benefit from it at the same time?”

“If composting is now mandatory in NYC and comes with a fine for noncompliance, why isn’t there an easy way to do it—and actually benefit from it at the same time?”

Motivations

Motivations

  • Interaction with Posty

  • NYC Composting Fee

  • Lacks structured ways to Compost

  • Building mandates

Pain Points

Pain Points

  • Doesn’t really know what composting is

  • Doesn’t care about composting

  • Doesn’t think his impact will create change

Needs

Needs

  • Something easy to use

  • Gradual exposure

  • Motivation-based system

  • Beneficial points-system

Design

How Might We?

make a composting system that is so easy, so rewarding, and so fun that people actually want to do it?

Design

Sketching

To explore potential solutions, we started building our flow and sketching out our mobile screens

With every step of our system's map, we kept Frank in mind and designed to spark incentive, joy, and emotions.

While my teammates worked on Posty Ecosystem - a trio of bots named Posty, Bucky (AI-Powered smart bin), Dumpy (the delivery bot). I was in charge of designing the end to end UX flow and app wireframes.

Design

Moodboard

Posty uses a warm, nature-inspired palette paired with the modern Mulish typeface to convey transparency, sustainability, and approachability. The colors balance clarity with optimism, while Mulish ensures a clean, friendly user experience.

Posty

Mulish Medium 30px

Mulish Medium 16px

Mulish Medium 14px

Our Solution

Meet Posty!

Pitch Video

7 minute Pitch Video

Reflection

AI Application

  • ChatGPT: We used ChatGPT early on for research, brainstorming, and writing our script. It was super helpful in organizing our thinking, though it slowed down a bit once we fed it a lot of context or longer prompts.


  • Gemini: We turned to Gemini when ChatGPT started lagging. It gave us faster, more direct answers in some cases and was useful when we needed quick iterations.


  • Sora: This was easily our favorite tool. We used it to generate hyper-realistic video content and found the best results came from layering generations — starting with text-to-cartoon image, then converting to realistic image, and finally into video. It takes a few steps, but the payoff is worth it. Having a subscription definitely helped unlock its full potential.


  • ElevenLabs: This became our go-to for voiceovers. We used it for Posty’s personality and our final narration. The voices were clear, expressive, and surprisingly funny when we wanted them to be.


  • Suno: We used this for music generation. It was a bit tricky to control, but it produced interesting and unique sounds we wouldn’t have come up with ourselves. It’s more of a creative wildcard than a precision tool.


  • Luma Dream Machine: While we appreciated the realism Sora offered, Luma felt more synthetic and less controllable. That said, it might be more useful for abstract or stylized visuals where realism isn’t the goal.


  • CapCut / Kapwing AI: We tried these for video generation but ultimately didn’t use them. The results felt too generic or overly AI-generated and didn’t match the tone or aesthetic we were going for.


  • Flora Fauna: There’s potential here for designers, but it requires a very specific workflow, usually going from text to image before making a video. It wasn’t intuitive for the kind of rapid experimentation we were doing.


  • Canva AI: We explored it briefly but moved on quickly. It felt limited compared to other tools that gave us more flexibility and control.


  • Gamma: This was helpful early on when we needed to pull together fast presentation drafts for mentor reviews. It lets us focus on ideas and structure before locking in visuals.


Overall Review:

  • Sora dominated for realistic video, especially when we used staged generation steps.

  • Voice and personality tools like ElevenLabs added life to the project in unexpected ways.

  • AI tools often require workarounds to get what you want — we had to experiment a lot with layering, prompting, and hybrid workflows.

  • Not all tools are worth the hype — we learned which were truly usable and which were more novelty

vyvee.design@gmail.com


© Vee Mai, 2025