The case for starting early, with the numbers attached.

The jobs are here, and they pay.

The Bureau of Labor Statistics projects about 280,000 openings a year in computer and information technology occupations from 2025 to 2035. These are not only jobs at famous companies. They are jobs at hospitals, logistics firms, school districts, banks, and the field-service businesses Vertex works with every day.

The pay is the part that changes a family. The median annual wage for these occupations was $109,470 in May 2025. The median for all occupations was $50,980. A young person who gets into this field early does not just get a job. They get a different starting line.

AI is pushing demand toward people who can build.

The same federal projections show where growth concentrates: data scientists up 33.5 percent from 2024 to 2034, information security analysts up 28.5 percent, software developers up 15.8 percent. At the same time, AI is expected to dampen demand for administrative and support roles.

That is the curve. Work that follows a script is being automated. Work that decides what to build, checks whether it is right, and ships it is growing. We want young people on the growing side of that line before it is obvious to everyone.

Work that follows a script is being automated. Work that decides what to build is growing.

The door is not open evenly.

In 2022, Black workers were 7.4 percent of the high-tech workforce but 11.6 percent of all workers. Hispanic workers were 9.9 percent of high tech and 18.7 percent of all workers. Those are the federal numbers, from the Equal Employment Opportunity Commission.

The gap starts well before the first job. Only 60 percent of U.S. public high schools offer an introductory computer science course, and Black, Hispanic or Latino, and Native American students are less likely to attend one that does. Young women were 33 percent of enrollment even where the course existed.

None of this is about ability. It is about access: a machine at home, a course that is paid for, someone who has done it before and will pick up the phone. Those are things money can buy, which is why this program exists.

The tools changed what a beginner needs first.

In the 2025 Stack Overflow Developer Survey, 84 percent of developers said they use or plan to use AI tools in their work, and 51 percent of professional developers use them daily. The same survey found that trust in those tools is low. That combination is the whole lesson.

A beginner today does not need to memorize syntax before building something real. They need to know what they are trying to make, how to ask for it, and how to tell when the answer is wrong. That is judgment, and it is learnable. Human intelligence with artificial intelligence is the Vertex idea, and it is the first thing we teach.

Why these five levers.

A device, because nothing happens on a borrowed phone. A paid course, because a clear path beats a pile of free videos. A mentor, because the questions that stall people are the ones a search engine cannot answer. Paid first work, because a finished project for a real business is the line on a resume that opens the next door. School partnerships, because teachers already have the students and need the gear and the hands.

Each lever unlocks the next. We fund them in that order, in order of need and budget, and we say plainly when the budget is the limit.

Why now, and why here.

Vertex Acquisitions is a Georgia company. We start where we can show up in person: a workshop in a room we can drive to, a laptop handed over face to face, a mentor who lives close enough to meet for coffee.

The window is now because the tools are new enough that early movers still get the advantage. In a few years, building with AI will be the baseline. Young people who start today will be the ones teaching it.