The Story
Behind The Code
I’m an AI customer success and systems specialist who started in programmatic advertising, fell in love with hands-on cybersecurity labs, and now builds interactive experiences that help non-technical teams adopt complex tools.
This is the longer story behind that work—how floppy disks, ad trading, psychology, and AI all turned into the way I help customers learn today.
Operator Profile: At A Glance
Former
Programmatic Ad Trader → Security Lab Builder
Fluent in
React/TypeScript, AI-assisted workflows, Interactive Labs
Focus
Helping teams adopt complex tools through better systems & stories
System Evolution
Tracing the logic from DOS commands to AI Agents.
DOS, Duke Nukem & Discovery
Started like most kids in the 90s—installing Duke Nukem from floppy disks using DOS commands. But I didn't just play; I broke things to see how they worked.
Outcome: This childhood tinkering was my first lesson in systems logic: inputs have consequences, and 'black boxes' can always be opened if you're curious enough.
Digital & Social Media Advertising
Spent years in the trenches of programmatic advertising. Learned what connects with people, what drives engagement, and how to optimize complex funnels.
Outcome: That's where I learned how to translate complexity into clear, persuasive messages—exactly what great customer onboarding and education require.
The Bridge to Engineering
Merged marketing instincts with technical fluency. Started building my own tools instead of just using others'. HTML, CSS, then deep into JavaScript and React.
Outcome: This is the bridge from 'I can explain things' to 'I can also build the systems and interfaces that make those explanations scalable.'
Building the Lab
Dove deep into cybersecurity. Not just reading about it, but simulating it. Built complex Red/Blue team labs to teach myself and others.
Outcome: Proved I can breakdown dense technical concepts (like ransomware staging) into interactive, gamified learning experiences that actually stick.
Living the Craft Daily
Now I build AI-assisted workflows, interactive labs, and documentation systems. I help non-technical teams adopt complex tools through better stories and software.
Outcome: Today that looks like building interactive docs and self-serve labs that help customers succeed without waiting on support tickets.
System Methodology
These principles are the backbone of how I run AI-assisted customer education and solutions work.
Outcomes Over Aesthetics
Beautiful interfaces mean nothing if customers can't succeed with the product.
I design for reduced friction, clearer workflows, and measurable adoption. Pretty is a bonus; usable is mandatory.
Test, Learn, Document
In AI CS, we must quickly test onboarding flows and collect real usage signals.
I crystallize what works into repeatable playbooks and labs. If it's not documented, it didn't happen.
Ship Fast, Improve Always
I share builds and drafts early with real users and teams, then iterate.
It's the same loop used to refine docs, labs, and training paths. Feedback loops are my fuel.
Human-First Systems
Technology should adapt to people, not the other way around.
I use psychology-driven UX to make complex AI tools feel intuitive and safe for non-technical users.
The Phil Factor
Phil is why I take shipping, customer support, and real business constraints seriously.
A CCIT graduate with distinction who immediately launched a PC business without a safety net. I learned hardware by watching him build; I learned business by watching him survive.
He proved that technical skill is just the baseline. The real skill is solving the customer's problem before they even know how to ask for it.
Generated
Operator Mindset & Execution
Technical excellence matters, but execution matters more
In AI CS, that means getting customers to 'first value' fast instead of chasing perfect architecture.
Start before you're "ready"
The market doesn't wait for you to feel prepared. Ship the prototype, get the feedback, iterate.
Scale comes from solving real problems consistently
Same logic as reducing churn: solve the recurring friction customers feel in your product, and growth follows.
Business constraints are real
Phil taught me that 'cool tech' that loses money is just a hobby. I build systems that drive ROI and adoption.
LESSON_SET_COMPLETE // APPLYING_TO_CURRENT_STACK
Need an Operator?
If you lead an AI or security product and need someone who can turn complexity into interactive labs, sales enablement, or customer education systemsthat actually convert—this is the work I'm looking to do next.