For most of my career, running multiple software projects in parallel was something typically reserved for full teams or for people willing to sacrifice a significant portion of their free time.

It was never just about writing code. There was architecture to design, interfaces to build, infrastructure to configure, deployments to manage, documentation to write, bugs to fix, and countless small decisions to make every day.

Each new project added a considerable cognitive load.

As a result, most of us naturally gravitated toward a single primary initiative. Even when we had dozens of ideas, creativity was rarely the limiting factor. Execution was.

Over the past few months, I’ve found myself in a situation that has made me rethink that assumption. Alongside my main job, I’ve been building several projects at the same time. Some are becoming real products. Others are experiments. Some were created to solve specific problems. Others simply started as ideas that seemed interesting enough to explore.

If someone had asked me three years ago whether it was realistic for a single person to make meaningful progress on multiple products simultaneously, I probably would have said no.

Today, I’m not so sure.

The main reason is not that I’ve learned to work longer hours or that I’ve somehow become dramatically more productive. In fact, I try to avoid both.

What has changed is the emergence of AI assistants that can meaningfully contribute to many of the tasks that used to consume a large portion of the available time.

They do not build products on their own. They do not eliminate the need for judgment. They do not make decisions for me.

What they do is reduce the execution cost of many activities.

When I need to create a new page, write documentation, generate tests, review code, draft content, explore implementation options, or troubleshoot a technical problem, I can often move much faster than I could a few years ago.

The most interesting difference is not the speed of any individual task. The difference becomes visible when hundreds of small tasks accumulate.

Every project contains an enormous amount of supporting work. Building the core feature is often only a fraction of the effort. The rest consists of documentation, maintenance, operational details, content creation, testing, deployment work, and all the small tasks that quietly consume weeks of effort.

AI does not remove that work, but it significantly reduces the friction involved in getting it done.

At the same time, I’ve discovered a new source of tension.

The ability to execute more projects does not automatically mean that I should.

In many ways, the bottleneck is no longer construction. It is attention.

I can make technical progress on several applications during the same week. What is much harder is maintaining clarity about which ones deserve continued investment of time, energy, and focus.

AI helps with building.

It helps much less with prioritizing.

Someone still has to decide which ideas are worth pursuing, which products have the potential to solve meaningful problems, and which experiments should remain exactly that—experiments.

In a sense, the constraint is shifting.

For many years, the question was:

“Do I have the capacity to build this?”

Increasingly, the more important question seems to be:

“Is this worth building?”

For those of us who enjoy creating software, that is a fascinating change.

Building is becoming more accessible. The scarce resource is becoming judgment.

I don’t know yet what will happen with all the projects I’m exploring. Some will likely evolve into something larger. Others will remain side projects. A few may never find users at all.

What I do know is that something feels fundamentally different from a few years ago.

For the first time in my career, it feels realistic for a single person to keep several meaningful projects moving forward at the same time without needing a team behind them.

Not because the work has disappeared.

But because a significant portion of that work now has assistance.

And for builders who enjoy creating things outside their primary job, that changes the equation quite a bit.