Automotive Technician | Building Toward Ownership
I fix what's broken and tell you the truth about it, and I'm building the technical, financial, and leadership skills to run that same standard as my own shop someday.
I don't guess at what's wrong with a car, I work through it methodically, ruling things out with real evidence instead of a hunch. It's the same instinct that shows up whether I'm tracing an intermittent electrical fault or working through an unfamiliar problem for the first time. As vehicles get more computerized, this is the skill that actually differentiates a technician: not owning the diagnostic tool, but knowing how to read what it's telling you.
Good work means treating the person on the other side of the repair like they deserve the truth, not just a bill. I quote fair prices before I start, I explain what I'm doing in plain language, and I don't take a shortcut just because it's more profitable. That standard is the reason customers come back, and it's the standard I want an entire shop to run on someday.
This is the skill I've had to build most deliberately. Modern vehicles are increasingly run by sensors, onboard computers, and software, and the technicians who keep pace with that shift are the ones who stay relevant. I've spent this semester closing that gap directly, through AI-assisted problem solving, prompt engineering, and data-driven forecasting, so the diagnostic instinct I already have doesn't get left behind by the tools around it.
"A scan tool can tell you a code. It can't tell you whether the person in front of you can afford the full repair this month."
Diagnostic work used to be almost entirely mechanical. Now, a growing share of what goes wrong on a modern vehicle lives in sensors, onboard computers, and software rather than a belt or a bolt. Research on the future of work backs this up directly, the World Economic Forum projects that 39 percent of current job skills will be transformed or become outdated by 2030, and AI literacy skills have grown 177 percent since 2023 according to LinkedIn's Economic Graph. That shift is already showing up in my own field, in diagnostic software, fleet telematics, and predictive maintenance tools that didn't exist a decade ago.
I don't think this makes hands-on technicians obsolete. I think it raises the floor on what "good" looks like. The technicians who differentiate themselves going forward will be the ones who can interpret what a machine tells them and still explain it honestly to a customer who can't verify it themselves, not just the ones who own the machine.
The Old Diagnostic
Listen to the engine. Check the obvious parts. Trust your hands and your years of experience.
The New Diagnostic
Read the data. Cross-check it against what your hands are telling you. Know when the computer is right and when it isn't.
I'm not waiting for an employer to teach me this. I'm building it now, on purpose, through hands-on AI and data practice I sought out myself, and next, through formal training in the diagnostic software and OBD systems already becoming standard in my field.
Instead of a traditional internship, I completed five Forage virtual job simulations. These are real, company-designed projects from Datacom, British Airways, and PwC, chosen deliberately to close two gaps I'd identified in my own skills assessment: technology and business reasoning. Every completion certificate is linked below.
01 / Datacom
Advised a fictional client on automating their timesheet-to-invoice process, working through AI-powered debugging, process flow design, and spec-driven development.
View certificate02 / Datacom
Practiced prompt engineering and AI collaboration, including using AI to help draft a client-facing presentation.
View certificate03 / British Airways
Diagnosed aircraft faults using technical logs and manuals, and worked through maintenance and parts-inventory forecasting, a near-direct parallel to the diagnostic work I already do on vehicles.
View certificate04 / British Airways
Built a model to forecast lounge eligibility and predict customer behavior, practicing applied data-driven decision making.
View certificate05 / PwC US
Built a multi-scenario financial model in Excel from unstructured client notes and summarized it in a client-ready email.
View certificateAI-assisted problem solving
hands-on practice with prompt engineering and AI-powered debugging, not just reading about it.
Diagnostic reasoning applied outside my usual field
proof that the fault-finding instinct I already have transfers to unfamiliar systems, not just engines.
Financial modeling and client communication
the business-facing skill I'll need the moment I'm not just fixing cars, but running the shop they're fixed in.
I believe people deserve to be treated honestly about their car and their money, especially when they can't afford for either to go wrong. I lead by doing the harder, slower work of doing right by people, even when a shortcut would be more profitable, because trust is worth more than any single repair bill. My goal is to build a shop where technical skill and technological fluency serve one purpose: giving people an honest, competent answer to a problem they can't diagnose themselves.
Where I Was
I spent months ignoring a back injury because slowing down felt like it would make me look weak. I treated a warning sign from my own body like an inconvenience instead of information, and it cost me more than it ever needed to.
Where I Am Now
I know now that taking care of myself honestly isn't the opposite of determination, it's what makes determination sustainable instead of self-destructive. That lesson now shapes how I think about my whole career, including why I'm building technology and business skills that don't rely on my body holding up forever.
Where I Was
My own skills assessment flagged Technology as my clearest gap. I was confident with a wrench and cautious with almost everything digital, and I didn't want that gap to be the reason I got left behind as my field kept changing.
Where I Am Now
I've built real, hands-on experience with AI tools, data modeling, and financial reasoning, not just exposure, but actual practice I can point to. I still have depth to build, but I'm no longer starting from zero, and I know exactly what to build next.
This is one version of my future, built out of my own skills, my own values, and a semester of honest work. Thank you for reading it.