AI Enablement Lead
Teaching people to use a technology was my profession before I wrote code. Now the technology is AI, I build and run it myself, and I have had to write the guardrails for a system I depend on.
Why AI Enablement Lead, why now
Enablement is a teaching job with an engineering problem underneath it, and I have done both halves for a living. I spent five years as a professional coach before software paid me anything, running seminars, webinars and facilitated workshops and building a ten-week course. Then 12 years engineering, the last 4 of them owning product direction as part-time CTO at National Auto Service.
What makes this the right seat now is that I am not enabling a technology I read about. I build and operate agentic systems daily, and I have had to decide what they are allowed to touch, which model runs them, and how a change to an agent gets reviewed before it ships. Adoption fails on the second month, not the first, and the reason is usually that nobody wrote the rules or stayed around to answer questions.
Enablement needs three things at once: someone who can teach, someone the engineers take seriously, and someone willing to write the policy nobody wants to own. I have done all three, and I run the AI myself rather than advising from the outside.
Five years as a professional coach before I was a developer, and an ICI Advanced Practitioner of Executive and Leadership Coaching. I delivered in-person seminars, online webinars and facilitated workshops to rooms of people, and built a ten-week course run partly self-directed and partly one to one. At iGoMoon I ran the internal trainings that kept the development team current. Getting people to keep using something after the novelty wears off is the actual job, and it is the one I trained in.
A self-hosted agentic system I operate every day as a real dependency: my own MCP server, custom agents and skills that take real actions unattended on a schedule. I am not demonstrating a tool I evaluated. I am describing the one I depend on, which is a different kind of credibility in front of engineers.
I own the guardrails on that system: which tools an agent can reach, which model runs it, what is scoped away, and how a change to an agent definition gets reviewed before it takes effect. Writing rules that let something move quickly without breaking is a different exercise when you are the one it breaks for.
Product Owner and part-time CTO at National Auto Service for 4 years, driving product from idea to finished solution with a dev team I brought in and managed. Before that, five years running my own agency across 160+ projects as the person selling the work and the person building it. Translating what a business wants into what an engineer should do is the ordinary shape of my week, not a skill I would be learning here.
What translates into AI enablement
- Five years delivering seminars, webinars and workshops as a professional coach → running the training and workshops that make adoption land.
- A ten-week course, part self-directed and part one to one → building enablement material people finish rather than bookmark.
- Internal trainings at iGoMoon to keep a dev team current → an AI champions programme and day-to-day support inside an engineering org.
- Guardrails, tool scoping and change control on my own agentic system → usage policy, access rules and standards that survive contact with a deadline.
- Part-time CTO and Product Owner at National Auto Service → coordinating agent and internal-tool builds with engineers.
- Publishing my delivery method as a Claude Code skill anyone can run → turning what works into something the rest of the organisation can pick up.
This page is curated for the AI Enablement Lead role specifically.
Please note, this is only a summarised version of my full CV. For the full picture, the complete CV is one click away.
What I bring → What this role needs
Each line connects something I have done to something this role asks for.
Teaching adults a practice and keeping them at it was my profession before software. Enablement is that job with a different subject.
A production agentic system I run daily. Unattended scheduled runs, scoped tools, version-controlled agent definitions.
The governance half of enablement, written for a system where I am the one who pays if the rules are wrong.
Enablement inside an engineering org, including the unglamorous part where you build the thing people actually open.
Drove product from idea to finished solution, including custom requirements and backlog, with a dev team I brought in and managed.
Turned my own method into a skill anyone can use, and shipped low-code tooling that helps others build with AI.
Engagements, start to finish
The problem, what I did about it, and what came of it.
National Auto Service
- Problem
- Asset management workflows ran on paper and spreadsheets, forcing manual coordination between the internal team, contractors, and customers - and slowing cashflow.
- Solution
- A purpose-built internal platform with customer + contractor interaction layers, replacing the legacy workflow.
- Build
- Designed, built, and operated the system as part-time CTO since 2022 - full ownership of architecture, security, sprint delivery, and product strategy. Brought in a small temporary dev team for larger features.
- Outcome
- Cashflow improved, in the CEO's words. Customer relationship maintained over the full engagement.
HubSpot FieldsJS
- Problem
- Building HubSpot CMS modules required developers to author module field configuration as raw JSON - a slow, error-prone, repetitive process across customer projects.
- Solution
- A JavaScript-authored workflow that compiles to the JSON HubSpot expects, dropping cleanly into existing build pipelines.
- Build
- Co-built and open-sourced as
@iGoMoon/hubspot-fields-js. Refined the developer experience based on actual customer-project usage at iGoMoon. - Outcome
- Adopted by the HubSpot core team and referenced from their official Fields.JS documentation. Cross-vendor / partner-ecosystem credibility - a developer tool inside another vendor's platform that they ended up endorsing.
What carries over from everything else
The half of the job that is not code, and where I learnt it.
- Customer
- Customer-facing and pre-sales
- Architecture
- Owning the architecture
- Enterprise
- Architecture at enterprise scale
- Agentic AI
- Agentic AI in production
- Hands-on
- Hands-on engineering
- Leading
- Leading and coaching engineers
- Coaching Skills
5+ years guiding individuals and business owners to expand their internal map and drive performance through communication.
- Ability to Lead
Bridging cross-functional teams and motivating people to do their best work, informed by years of coaching.
- Project Management
Goal-based delivery on time and budget - clear goals, accurate estimates, agile iteration, reusable foundations.
- Customer Service
Under-promise, over-deliver - clear communication and exceeding expectations build lasting customer trust.
- Team Player
Adaptability, trust and shared goals - leading developers while collaborating with sales and design under deadline pressure.
Frankenverse: A Self-Hosted Agentic System
A production agentic system I built and run every day. My own knowledge base wired to Claude through a self-hosted MCP server, with custom skills and workflows that do the everyday work and run unattended on a schedule.
AI Skill: Create MVP
Productized my consulting methodology as a Claude Code skill - discovery → planning → implementation, resumable across sessions.
Lovable Prompt Builder
A web tool helping Lovable users craft better prompts - built using my own Create MVP methodology skill, demonstrating the enablement-first approach.
Lovable Output Analyser
A web tool created with Lovable that allows users to analyse a GitHub repository's codebase and rank it for maintainability and complexity.
National Auto Service
An internal asset-management platform for vehicle lifecycle tracking - customer portals, contractor coordination, and cashflow workflow automation. Built with Laravel and VueJS.
Certificate IV in Life CoachingThe International Coaching Institute (ICI)- Advanced Practitioner of Executive and Leadership CoachingThe International Coaching Institute (ICI)
- Practitioner of Neuro-Linguistic ProgrammingThe International Coaching Institute (ICI)
TestDome· Top 10%- TestDome· Top 10%
- TestDome· Top 10%
The technologies this role names
Cut down from the full list to what the job ads for this role ask for.
- Claude
- MCP (Model Context Protocol)
- AI Agents / Agentic Systems
- Prompt & Context Engineering
- OpenAI GPT
- Lovable
- Docker
- Ansible
- REST API
- GitHub