Allen

I built AI EnableOS to learn, hands-on, how companies take AI from a first idea to results they can prove. Most AI ideas stall after the pilot, so I focused on the parts that come after: sign-offs, adoption, and showing what it saved. I'm open to AI enablement roles in New York.

What I did

1. 1
   Studied real projects first

   More than 900 published AI projects: bank rollouts like BBVA, UK and US government AI records, and company case lists. The question each time: what did they do first, next, and last?

2. 2
   Turned that into 6 steps and 5 sign-offs

   Each step is named the way AI enablement job postings name the work. Risk, funding, pilot, results and scale each need a named person to sign.

3. 3
   Set the rules for the AI

   The AI recommends; a person decides. Before-numbers are locked before a pilot starts. Results count only when the owner and finance confirm them. Made-up numbers are always labeled.

4. 4
   Made the value math checkable

   Every saving is shown line by line, with the baseline, the assumptions, the period, and a cautious case that counts only half the time saved.

5. 5
   Built and tested the app

   Built with Claude Code as my AI coding partner. Inside the product, Claude writes the questions and the recommendations.