AI-Enabled Company Operating System
How I implemented ChatGPT across the company, built AI-assisted executive and product workflows, and enabled staff with training, source files, and practical operating patterns.
In a resource-constrained organization operating in a difficult market environment…, critical work was spread across meetings, email, SharePoint, Confluence, Jira, project documents, financial decisions, product decisions, policy work, and institutional memory. I led the rollout of ChatGPT across the company and created AI-assisted workflows, agents, source files, and training patterns that helped staff produce higher-quality work, improve data accuracy, preserve context, and move faster across finance, HR, product, governance, and operations. AI also created practical operating leverage during a period when the organization needed broader coverage, faster documentation, stronger analysis, and better continuity without adding headcount.
The Operating Problem
Executive and operational work was becoming increasingly fragmented across too many channels, tools, conversations, and decision points. Important commitments lived in email threads, meeting notes, vendor conversations, Confluence pages, Jira tickets, spreadsheets, project documents, and personal memory.
The organization needed better continuity and higher output without adding headcount. Staff needed practical ways to use AI safely and effectively, with access to curated source materials, reusable workflows, and clearer patterns for turning scattered information into decisions, documentation, analysis, tasks, and follow-through.
What Changed
The work gave the organization a more practical way to use AI across real operating needs, not just isolated experimentation. Staff had better access to context, clearer starting points, reusable workflows, and source-backed materials. Documentation improved. Data accuracy improved. Meeting outputs, task tracking, and project follow-through became easier to manage. Staff were able to produce more work at higher quality with better support. It also created practical operating leverage at a time when the organization needed broader coverage, faster documentation, stronger analysis, and better continuity without adding headcount.
The result was not AI for novelty. It was a practical operating layer that helped convert scattered institutional knowledge into usable documentation, clearer decisions, stronger analysis, and more confident execution during a difficult operating period.
What I Led
01 - Company-Wide ChatGPT Rollout
Implemented ChatGPT across the organization and helped establish practical AI use patterns for staff working across finance, HR, product, governance, operations, and documentation-heavy workflows.
02 - Executive Workspace & Operating System Design
Built my own AI-enabled executive workspace to manage finance, HR, product ownership, Scrum/product operations, vendor management, governance support, documentation, and cross-functional decision-making.
03 - Product + Modeling Team Enablement
Created a repeatable process to help a product and modeling team member build a similar AI-assisted workspace using GitHub Copilot in VS Code, supporting product, data and modeling workflows, documentation, task tracking, analysis, and operating continuity.
04 - Atlassian/Rovo + Confluence/Jira Knowledge Infrastructure
Used Atlassian tools, including Confluence as the knowledge base and Jira as the development workflow layer, to connect AI-assisted documentation, source materials, product decisions, tickets, and operating context.
05 - Training, Source Curation & Staff Leverage
Rolled out company-wide AI training and curated source files so staff could use AI with better context, stronger grounding, less rework, improved data accuracy, and higher-quality output.
What This Demonstrates
This case study demonstrates my ability to implement AI as operating infrastructure. I can identify where information, decisions, documentation, and follow-through are breaking down; design practical AI-enabled workflows; train staff; curate source materials; and connect tools like ChatGPT, Confluence, and Jira into a more usable company operating system.
Capabilities: AI implementation · Company enablement · Executive operating systems · AI workspace design · ChatGPT rollout · GitHub Copilot · VS Code workflows · Atlassian/Rovo workflows · Confluence knowledge management · Jira development workflows · Product operations · Scrum support · Source curation · Training · Documentation systems · Decision support · Data accuracy · Cross-functional operations · Change management
OPERATING PRINCIPLE
AI only creates leverage when people can trust the source material, understand the workflow, and use the output to make better decisions.