Welcome to Hello Engineer, your weekly guide to becoming a better software engineer! No fluff. Pure engineering insights.
Matthew Gallagher is not a startup founder in the traditional sense.
No VC money. No 50 person team. No office. Just a house in Los Angeles, a dozen AI tools, $20,000 and two months of relentless building.
The result? Medvi, a telehealth company that did $401 million in revenue in its first full year and is on track for $1.8 billion this year. With two employees: Matthew, and his younger brother Elliot.
This is not a fluke. This is the blueprint for a new class of company. As engineers, we need to understand exactly how it was built.
The Stack: What He Actually Used
Here is the part most articles gloss over. Let us go layer by layer.
Layer 1: AI Tools (~$20,000 total spend)
Matthew did not hire a team. He assembled a toolset.
ChatGPT, Claude and Grok handled writing the code, website copy and building AI agents that glued his software systems together. Midjourney and Runway generated images and videos for ads and the website. ElevenLabs powered AI voice tools to communicate with customers.
That is it. Code, content, visuals, voice — all AI generated.
Layer 2: Telehealth Platforms (the outsourced backend)
Matthew did not build the hard stuff. He plugged into two platforms that already existed.
CareValidate provided the doctor network, prescription compliance and a telehealth in a box infrastructure. OpenLoop Health handled pharmacy fulfillment, shipping and patient management.
His insight was simple: do not build what has already been built. Use it as an API.
Layer 3: The Product (Medvi)
On top of this stack, he built a clean consumer brand selling GLP1 weight loss drugs at $179 per month, cheaper than competitors, smoother checkout and no doctor’s office visit required.
The market was ready. He just got there faster.
The Engineering Decisions That Mattered
A few things stand out from a pure systems thinking perspective.
He treated every dependency as a service, not a hire.
Doctors? A service via CareValidate. Shipping? A service via OpenLoop. Legal? LegalZoom first, then a law firm. Accounting? AI tools first, then an accounting firm. Marketing? Media agencies on contract.
His mental model was essentially microservices applied to a whole business. Every function was a composable, replaceable module.
He built AI agents before it was widely adopted.
When his disparate software systems could not talk to each other, he did not hire an integration engineer. He built custom AI agents to bridge the gaps. In 2024, that was still niche thinking.
He felt the cost of over hiring viscerally.
At his previous startup Watch Gang, he had 60 employees and never turned a profit. He described it clearly: more people meant higher costs and slower decisions. With Medvi, every hire had to justify itself against that experience.
The One Failure That Explains Everything
In March 2025, Matthew made a minor website change and went hiking. His media agency called. Zero orders for the last hour. He had broken something in production with no one to fix it.
He sprinted home.
That single incident, losing around 200 customers in one hour, is a forcing function most founders never face so cleanly. No on call rotation. No SRE team. No incident management runbook. Just him, running.
His fix? He hired two engineers on contract. Not full time. Contract. Still avoiding headcount.
What This Means for Engineers
This story is not about replacing engineers. It is about what one determined engineer can do when they stop waiting for permission, budget or a team.
Three takeaways worth sitting with.
1. The leverage point has shifted. The bottleneck used to be execution capacity. You needed people to build things. Now the bottleneck is judgment — knowing what to build, which tools to assemble and when to stop. That is a very different skill set from what most CS curriculums prepare you for.
2. Outsource the solved problems. It is a real architecture principle. Matthew did not reinvent prescription fulfillment. He plugged into CareValidate. As engineers, we spend a lot of time building infrastructure that already exists. The better question is always: what layer is actually novel here?
3. A one person company worth $1 billion was Sam Altman’s 2024 prediction. It happened in 9 months. The compression of time between prediction and reality in AI is accelerating. Whatever you think is 3 years away is probably 6 months away.
The Lonely Part Nobody Talks About
Matthew admitted he is considering hiring more people mostly because he is lonely.
There is something very human in that. Maximum efficiency and isolation often come bundled together. He created an AI clone of his own voice to handle personal scheduling calls. He works basically every waking hour.
He also donated $1 million to a foundation, supports LA cat rescue organisations and is emotionally moved by the financial security he now has, given a childhood spent in motels and cars.
The technology made the company possible. The rest of it is still just a person trying to figure out what to do with what they have built.
Loved this breakdown?
Hit a like ❤️ For more simple explanations, useful insights on coding, system design and tech trends, Subscribe To My Newsletter! 🚀
See you next week with more exciting content!
Signing Off, Scortier