Building things used to be hard. Having ideas was the easy part.
That equation is flipping.
This is Part 2 of a 4-part series on AI and the future of work. Read Part 1.
When Building Becomes Trivial
I can describe an application to an AI, and it will write functional code. I can sketch a concept, and AI will generate designs. I can outline a process, and AI will create documentation, workflows, and implementation plans.
The craft of building, the technical skill of turning an idea into reality, is becoming commoditized. Not worthless, but no longer the differentiator it used to be.
Which means the differentiator is shifting upstream. To the idea itself.
If everyone can build, the question becomes: what should we build? The person who answers that question well just became the most valuable person in the room.
Your Thoughts Are Your IP
Here's where it gets uncomfortable.
If your value is your ideas, and AI makes it trivially easy to execute on ideas, then sharing your ideas becomes a risk calculation you've never had to make before.
In the old world, you could share a concept freely because execution was the hard part. You needed capital, teams, time, and expertise to turn an idea into something real. The idea alone wasn't worth stealing because the thief still had to do all that work.
Now? Someone can take your concept and extrapolate it to a whole new level in moments. The moat around your idea just disappeared.
This is going to change how people behave. We'll see more people holding back, being vague, protecting their thinking. The open collaboration that drives innovation will face new friction.
The Legal Vacuum
The law hasn't caught up.
In March 2025, the U.S. Court of Appeals affirmed in Thaler v. Perlmutter that copyright requires human authorship. AI can't be an author. But that ruling creates more questions than it answers.
If I give an AI my idea and it generates the execution, who owns the result? The courts say AI can't own it. But did I create it? The AI determined the expressive elements. According to the Copyright Office, that means the generated material isn't the product of human authorship.
We're in a gray zone. You might own your idea. You might own your modifications to what AI produces. But the line between your creative contribution and the AI's output is blurry, contested, and varies by jurisdiction.
Some platforms address this contractually. OpenAI's terms assign IP rights to the user. But those are terms of service, not law. They could change. And they don't address what happens when your idea, executed by AI, gets copied and re-executed by someone else's AI.
The Company IP Problem
This gets even more complicated inside organizations.
Your company's IP used to be protected by trade secrets, patents, and non-competes. But if the real IP is now in people's heads, in their unique ability to generate valuable ideas, then IP protection means retention.
If you don't want that person rebuilding your competitive advantage somewhere else, you have to keep them. Non-competes are already weakening legally. And practically speaking, you can't prevent someone from having ideas after they leave.
Meanwhile, every time your employees use AI tools, there's a question about where that information goes. If your team's unique insights flow into a central repository at OpenAI or Anthropic, are you training your future competitors?
This is why the conversation about on-premise AI is heating up. Companies are realizing that the information flowing to external AI providers might be their actual competitive advantage walking out the door.
How Do You Titrate Information?
This is the question I keep coming back to: how do you share ideas effectively without giving away the store?
In the past, you could share freely at the concept level because execution was the moat. Now you need a new strategy.
Maybe it's about timing. Share ideas only when you're ready to execute immediately.
Maybe it's about depth. Share the what, protect the why and how.
Maybe it's about relationships. Share with trusted partners, not public forums.
I don't have the answer. But I know that the old model of open ideation is going to face pressure. The people who figure out how to navigate this, how to collaborate without being commoditized, will have an edge.
Next in this series: Part 3 explores the K economy, AI skill scoring, and the scary division between "valuable" and "non-valuable" workers.
Sources: