I saw a lot of deals over my venture investing career. Early stage to later stage, consumer to hard tech and everything in between. I sat across the table from a lot of founders. And the pattern I kept noticing was not which companies were raising money — it was which ones were not.
The companies raising money were almost always building for people who look like the people writing the checks. Knowledge workers. White-collar professionals. People who spend their days in front of a screen in a climate-controlled office. That is the world venture capital understands because it is the world venture capital inhabits.
The companies that were not raising money, or raising it slowly, painfully, against enormous skepticism, were building for everyone else. I kept thinking about who is building for the real economy — the workers using their hands and brawn under the blazing sun outside or underground, the unglamorous trades that the AI elite now look down on as menial work that should be automated and replaced by robots. The electricians, plumbers, mechanics, construction workers and all the skilled technicians who enjoy building and fixing instead of sitting in front of the computer taking useless zoom meetings all day. They were forgotten and ignored by a tech industry obsessed with CRMs and podcasts.
The 80% Nobody Is Building For
Here is a number that should reframe how you think about the AI opportunity: approximately 80% of the global workforce does not sit at a desk.
Electricians. Plumbers. HVAC technicians. Construction foremen. Healthcare aides. Logistics operators. Agricultural workers. Manufacturing floor supervisors. The people who keep the physical world running.
These workers represent trillions of dollars of economic output. Their industries are massive, their labor is expensive, their margins are thin, and their technology stack remains very basic. Most of them are still running on clipboards, phone calls, and tribal knowledge passed down through apprenticeships.
The AI revolution has barely touched them.
Not because the opportunity is not there. The opportunity is enormous. But because the people funding technology companies do not know these circles and do not speak their languages. You won't meet them at hacker houses or demo days. They do not know what a licensed technician's day actually looks like, what slows them down, what keeps them up at night, what a 10% productivity gain would mean for a contractor running a 40-person crew. They cannot pattern-match on a problem they have never seen up close.
So the money goes elsewhere. And the 80% wait.
12% use it in any capacity
What Blue Collar AI Actually Means
When I talk about Blue Collar AI, I am not talking about robots replacing workers on a factory floor. That is a different conversation entirely.
I am talking about something more immediate and more valuable: giving the skilled worker a cognitive partner that makes them dramatically better at what they already do.
Think about what an experienced tradesperson carries in their head — a plumber who knows every code variation by jurisdiction, an HVAC tech who can diagnose a system by sound, an electrician who can spot the blueprint problem the engineer missed. They know which materials work in which environments. They know how to estimate a job, manage a crew, talk to a general contractor, and handle an inspection.
That knowledge took fifteen years to accumulate. And right now, none of it is augmented by anything smarter than a calculator and a Google search.
What happens when you give that electrician an AI that knows the entire code, can read blueprints, can generate estimates in minutes, can handle job documentation, can flag safety issues before they happen, and learns the specific preferences of each general contractor they work with?
You do not replace the technician. You make one technician capable of doing the work of two. You let the foreman spend less time on paperwork and more time on the job site. You let the business owner take on more projects with the same crew. You compress margins upward across an industry that has been running on thin margins for decades.
That is the value creation I am interested in. That is where the next generation of durable, defensible technology companies is being built.
Why This Moment
The question I get asked most often is: why now? These industries have existed for a hundred years. Why has no one built for them before?
Three things are true simultaneously in 2026 that were not true before.
The technology is finally ready. Large language models can now understand domain-specific knowledge at a level that was not possible two years ago. You can train a model on the entire knowledge base, on thousands of project blueprints, on years of job documentation, and it actually understands the material in a way that is useful in the field. The gap between what AI can do and what a skilled worker needs has collapsed.
The cost of building has collapsed. A two-person team can now build and deploy a production-grade AI application in weeks that would have required a twenty-person engineering team two years ago. This changes the economics of building for verticalized, specialized markets. You no longer need to raise $10 million before you have a product. You can get to revenue with a fraction of that and build from a position of strength.
The workforce is in crisis. The skilled trades are facing a generational knowledge transfer problem. Millions of experienced tradespeople are retiring. The apprentices coming up behind them are inheriting the work but not the decades of accumulated knowledge. AI is the most practical bridge across that gap. It is not replacing the retiring master electrician — it is helping the next generation learn faster and work smarter.
These three forces together create a window that is open right now and will not stay open forever.
The Build + Invest Model
At Untamed Ventures we believe the best way to fund companies in this category is not to sit on the sidelines and write checks. It is to get in the room.
We call our model Build + Invest. For our earliest stage companies — the ones we incubate from zero to one — we work alongside a technical co-founder in the earliest months. Setting strategy. Helping build products. Finding the first customers. Preparing for institutional capital.
This is not typical for a venture fund. Most funds at our stage write a check and move on to the next one. If it gets traction then do a victory lap about how early and value-added they were in the trenches. We show up every day because we believe the impact we can make is highest at the moment of maximum ambiguity — before there is a product, before there is revenue, before there is consensus that this is a good idea.
One of our current incubations is doing exactly this: an AI copilot built for the trades. We do not just write checks into this thesis. We are actively building in it and around it. The companies we are building are not building for the C suite. They are building for the foreman on a job site who has been doing this work for twenty years and has never had a tool that actually understands what he does.
Where Do We Go From Here
If you are building or interested in investing in Blue Collar AI — or in any category where AI meets the physical world and the workforce that runs it — I want to hear from you.
Not because the category is trendy. It is not.
Because the companies that get built in the next three years in this space will be operating in markets that remain wide open, serving customers who have been underserved for decades, with products that create real and measurable value in people's working lives.
That is where durable companies get built. That is where generational companies will be.
Trillion dollars of value is sitting there. Most venture capital is too comfortable to go get it.