Carson Emenecker

Computer Science at UW–Madison · Class of 2029

I build software for
real‑world problems.

I study computer science at UW–Madison and build practical software for operational workflows, specialized industries, and AI-powered tools.

View selected workAbout me

Selected Work

[ Screenshot pending — demo-environment capture ]
FIG. 01 — Manufacturing Operations Platform (capture pending)
Private

Manufacturing Operations Platform

A private manufacturing platform that connects receiving, planning, production, inventory, traceability, palletization, and shipping in one operational system.

Built around real manufacturing workflows where the state of physical material has to remain consistent as it moves from receiving through production and outbound fulfillment. My contribution: I led the product definition, architecture, and implementation of a full-stack manufacturing platform, translating real operational workflows into data models, interfaces, APIs, and guarded state transitions. I owned the technical decisions, implementation review, data-integrity hardening, and production-readiness process, using AI-assisted development throughout the build.

Next.js + ReactTypeScriptPostgreSQLPrismaTailwind CSSVitest
[ Screenshot pending — synthetic-data capture ]
FIG. 02 — Industrial Systems Prototype (capture pending)
Prototype

Industrial Systems Prototype

A private industrial software prototype for keeping complex technical requirements accurate, traceable, and coordinated as they change through a commercial workflow.

I wanted to understand how software could improve a technical workflow in a specialized industrial market where the outcome depends on multiple interacting requirements staying correct as they change. My contribution: I conducted domain research, translated recurring workflow problems into product requirements, defined the information model, and designed and built the interactive prototype.

Next.js + ReactTypeScriptTailwind CSSVitest

Shipped Experiments

CodeReview AI input screen with pasted source code ready for review.
CodeReview AI findings view showing categorized security issues and improvement suggestions with severity ratings.
FIG. 03A–B — CodeReview AI, input → findingsFIG. 03 — CodeReview AI, findings

CodeReview AI

Live

AI-powered code review that scans pasted code and returns categorized bugs, security issues, and improvement suggestions with severity ratings.

My contribution: designed and built the product end to end, including the review interface, Claude-powered analysis flow, authentication, and billing.

Solo buildReactSupabaseStripeClaude API
Visit CodeReview AI
AI Flashcard Generator input screen where the user supplies their own Anthropic API key, stored in memory only, and pastes notes or text to generate flashcards.

FIG. 04 — AI Flashcard Generator

AI Flashcard Generator

Live

A lightweight browser-based tool that turns pasted material into study-ready flashcards using the Claude API.

Visit the AI Flashcard Generator
AI Knowledge Base Chat setup screen where the user supplies their own Anthropic API key, names a knowledge base, and pastes the source content to chat over.

FIG. 05 — AI Knowledge Base Chat

AI Knowledge Base Chat

Live

A browser-based tool that lets users provide their own source material and ask questions answered only from that content.

Visit AI Knowledge Base Chat

About

I’m a computer science student at UW–Madison with a background in biomedical sciences and emergency medical training, including earning NREMT certification. Those experiences shaped how I approach software: understand the real workflow first, pay attention to edge cases, and build systems people can rely on. I’m especially interested in operational software and specialized industries, where good products require learning the domain rather than just writing code. I like taking ambiguous problems from first principles through product design, architecture, implementation, testing, and iteration.

Principles

  • Build for reality, not the demo.
  • Understand the workflow before writing software.
  • Prefer durable systems over impressive complexity.
  • Ship, observe, and improve.