AYO Chat Agent v1

60-90 second application demo

A short narration that explains the value fast.

Use this as the voiceover for a LinkedIn post, job application follow-up, or portfolio walkthrough. It leads with the problem, then proves the software system.

Title

AYO Chat Agent v1 - Local AI Tool for Game Design Production Maps

Short Description

AYO Chat Agent v1 converts rough game design notes into structured production maps using a simple Python desktop app, Ollama, Phi-3, validation logic, Strategy Pattern categorization, tests, and executable packaging.

Narration

Hi, I am Matthew Mitchell, and this is AYO Chat Agent v1.

The problem I wanted to solve is simple: game design notes can get messy fast. A single document can mix character ideas, world lore, abilities, story beats, mechanics, and production tasks. That makes it harder for a developer or small team to turn raw creative notes into actionable work.

AYO is a local AI-assisted document organizer built in Python. It loads a design document in a simple desktop app, chunks the text, sends controlled prompts to a local Ollama and Phi-3 workflow, verifies the response, categorizes useful details with Strategy Pattern logic, and assembles the result into a Markdown production map.

What makes this more than a prompt demo is the software structure around the AI call. The project includes a desktop interface, loader, chunker, verifier, categorizer, production-map assembler, automated tests, UML diagrams, and a PyInstaller executable build.

For me, this shows the lane I work in: technical design, AI tooling, game production workflows, and practical software systems that help creative teams organize work.

The full case study, diagrams, test evidence, and milestone videos are available on the project page.

Visual Shot List

  • Open on the AYO landing page and highlight the problem statement.
  • Show the sample design document.
  • Open the desktop app and show the bundled sample loading into the interface.
  • Click Generate Map and show the output panel filling in.
  • Show the generated Markdown production map.
  • Cut to the sequence diagram and state chart.
  • Show the passing test suite.
  • End on the browser lab, video evidence page, and source-review request path.

LinkedIn Caption

I built AYO Chat Agent v1 as a local AI-assisted production-map tool for game design planning.

It takes rough design notes, runs them through a controlled Python/Ollama/Phi-3 workflow, validates responses, categorizes useful details, and outputs a Markdown production map.

The project includes a Python desktop interface, Strategy Pattern categorization, response verification, pytest coverage, UML diagrams, milestone videos, and an executable build.

Portfolio - Browser Lab - Request Source Review