Tyler Spitzer-Wu


// University of Michigan
// B.S. Urban Technology
// Taubman College of Architecture and Urban Planning
// Minors in Computer Science and Real Estate Development
// Class of 2027

I am fascinated with the use of technology within the processes and systems of the built environment to improve efficiency and delight in development and user experience. Cities are centers of innovation, culture, and economy with unparalleled vitality; I am interested in how scalable products and efficient services can be deployed in them to maximally respond to the needs of a city’s users. I aspire to deploy my programming skills, design intuition, and entrepreneurial approach to positively impact cities in product, design, and technology roles.


Product Intern
    Cedar (AI + architecture startup)
    Summer 2025

VP External Affairs, Co-Founder
    URB Consulting
    Oct 2024 - Present

Design Intern
    Fletcher Studio Landscape Arch. + Urban Design
    Oct 2023 - Dec 2023





tylersw@umich.edu
Résumé
LinkedIn

AI + SMS Public Reporting

UT 402: Urban AI
APR 2025

// Python, Streamlit, Google Apps Script, OpenAI API, Google Sheets API
// product development, prompt engineeringFor my Urban AI class, I was challenged to create a prototype for a product that solved an urban problem using AI in some form. I wanted to make something that could facilitate a win-win situation; from what I had been studying in classes, it seemed like a lot of urban problems went unsolved because the responsibility to solve the problem was allocated in an unbalanced way between the government, the public, and the private sector. So, my primary ethos when brainstorming was to create something that would create positives for everyone without placing an unfair amount of burden on any one party.

The system I created is quite simple: when a member of the public sees something in their city that they’d like to report to the appropriate department, they simply explain it in a text message and send it to one central phone number. When the message is received, it is sent through an AI model that processes the message, chooses the department best suited to respond to the incident, and gives the incident an “urgency ranking” based on how quickly response is needed. See the short video demo below to see how it works.


This system takes the onus off of the public to find the relevant department and call/email them to report an issue. Instead, when someone sees something in public that needs municipal attention, like a pothole, a fallen tree, or a dirty public bathroom, they can just shoot a quick text to one number. On the government’s side, the system pretty much eliminates situations where a member of the public reaches out to the wrong department for a certain issue, which wastes everyone’s time. A city that adopts this type of system can very easily add specific context explaining each of their departments’ scopes of responsibility and essentially guarantee that complaints are routed to the right people.

So, it’s a win for residents, as they can report a public issue with very little effort; it’s a win for the government, as they can spend more time actually addressing issues rather than responding to complaints irrelevant to them; and it’s a win for the city overall, as more public issues get reported and responded to.
Tech Details:
- SMS fetch with Google Voice + Google Apps Script to filter and put messages into Google Sheets

- Python script calling Google Sheets API to get messages

- OpenAI API call to use ChatGPT to process messages (which department, urgency level)

- Python script with Streamlit library to create live dashboard

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