Building an AI Teammate.

As AI reshapes how knowledge work gets done, I explored what it means to become an AI-native researcher. Rather than using AI as a chatbot, I built AI-powered workflows that organize knowledge, accelerate research, automate repetitive work, and transform years of research into reusable, searchable assets.

Under the Hood

    • Claude Code

    • VS Code

    • Git

    • GitHub

    • Markdown

    • Terminal / Command Line

    • ChatGPT

    • AI Workflow Design

    • Knowledge Management

    • Prompt Engineering

    • AI-Assisted Development

    • Documentation Systems

    • Version Control

    • Workflow Automation

    • Information Architecture

01
AI Knowledge Management

Designed a structured knowledge system that transforms resumes, portfolios, project decks, case studies, and research artifacts into searchable, reusable assets. Rather than repeatedly recreating work, the system enables AI to retrieve, connect, and synthesize knowledge across projects.

03
AI-Assisted Development

Used Claude Code, VS Code, Git, GitHub, Markdown, and command-line workflows to build and maintain AI-powered systems, version control changes, and collaborate with coding agents.

Metrics

  • 16 case studies documented

  • 45+ target companies tracked

  • 50+ documentation files created

  • 250+ Git commits

  • 40+ reusable prompt templates

  • 15+ automated workflows

  • 100+ AI-assisted research artifacts generated

02
AI Workflow Automation

Built automated workflows that reduce repetitive administrative work, including portfolio management, document generation, opportunity tracking, research organization, and content reuse.

04
Prompt & System Design

Designed operating principles, writing standards, reusable prompts, project structures, and documentation that enable AI agents to perform complex multi-step tasks consistently across research, writing, and case study development.