Lalo Adrian Morales was hired in 2021 as employee number thirteen at a tiny startup called Waltham Clinic. His official title was "medical assistant," but that was more of a polite suggestion than a job description. In reality, he was a medical assistant / data entry guy / insurance verification specialist / behavioral health assistant — the person who handled anything no one else knew how to do.

The company was scrappy. A handful of people trying to build a new model of care, figuring out processes as they went, duct taping together healthcare, insurance, and software. Lalo sat at this weird intersection of clinical work and paperwork — talking to patients and providers on one side, dealing with insurance companies, forms, and endless spreadsheets on the other.

Then the company rebranded to Lightyear Health. Funding came in. The team grew from thirteen to over a hundred. New CEO. Departments. Org charts. Acronyms for everything.

And there was Lalo, still technically a medical assistant, but doing work that had almost nothing to do with taking vitals or rooming patients. Billing and coding. Claims auditing. Prior authorizations. Payment requests. His little corner of the company — the insurance team — was five people: him and four amazing ladies who knew the insurance grind inside out.

That's where things got interesting. Because while his title said medical assistant, his brain was acting like a systems engineer. He couldn't stop seeing patterns in the chaos. The same steps repeated manually, across twenty tabs and three different systems. Every prior auth, every verification, every claim felt like a workflow begging to be automated.

And sitting right next to them — virtually — were the software engineers.

So he started talking to them. Not in fancy tech language. Just describing their day, step by step: "First we log into this portal. Then we copy this ID. Then we check eligibility here. Then we paste it there. Then we screenshot for proof. Then we manually type the result into our internal notes."

The engineers listened. They asked questions. And then they started building.

What came out was the "grey dashboard" — an internal backend tool for the insurance team. It wasn't pretty. But for them, it was magic. Data flowed in from APIs. They could see what they needed without logging in and out of a dozen portals. One big win: integrating an API to automate insurance verification. What used to take several minutes per patient could be pulled in seconds.

It was a huge win. It was also the beginning of the end for his job.

Because what was he really doing for the company? Manually executing workflows that he was simultaneously helping to automate. Every improvement to that backend dashboard quietly made his own role less necessary. He was helping build the machine that would eventually do his work better, faster, and cheaper.

Then things shifted. Markets got weird. Priorities changed. The team shrank from over a hundred to around fifty. Leadership changed. Projects got cut. Suddenly every role had a giant invisible question floating over it: "Is this critical to the new version of the company?"

One day in September 2023, he found out the answer for his role.

They let him go. Not because he was bad at his job. Not because people didn't like working with him. But because, in their eyes, there just "wasn't anything else for me to do." The workflows he had helped streamline and automate were working. The dashboard was built. The API was plugged in. And without a bachelor's degree in computer science, he didn't fit neatly into any of the higher-paying technical roles that survived.

On paper, he was still just a medical assistant.

After getting fired, he didn't rush into another job. He went back to school to finish his computer science degree. He went deep into AI — not as a casual user, but as someone who tests the limits every single day. He started learning to code properly. He stopped just "talking to the engineers" and started becoming one.

Here's the wild part: the grey backend dashboard they spent months designing at Lightyear? Today, he can build something better — more polished, with a real database, cleaner UI, and smarter automation — in a weekend with AI as his co-pilot.

"I joke that AI took my job," he says, "but really, my job was always destined to evolve into something more automated. I just got to watch it happen up close. And I'm glad I did, because it forced me to level up."

"Today, I'm not the guy who gets handed a grey dashboard and told, 'Use this.' I'm the guy who can sit down with AI, sketch out the workflows, and actually build the dashboard."