Wall Street

In the 1987 film Wall Street, Gordon Gekko stands barefoot on a beach, talking into his enormous Motorola “brick” phone. The scene was meant to signal power and wealth so extreme it could bend geography. Deals no longer required boardrooms. Money, famously, never slept.

The scene captures a deeper idea that science-fiction author William Gibson later summarized perfectly:

“The future is already here—it’s just not evenly distributed.”

A device used exclusively by the rich and powerful in the 1980s would begin appearing in everyone’s pockets a decade later.

New technologies don’t arrive all at once. They show up early in small, niche groups of insiders, specialists, or the unusually curious before spreading to everyone else.

I had my own version of that moment this past week.

I was telling two friends about OpenClaw, a new open-source framework that lets people build and run their own AI agents. One friend works in corporate IT. He had heard of it, but hadn’t built anything himself. The other runs a medical practice. He hadn’t heard of it at all and barely uses AI.

That gap wasn’t surprising. Most of us fall into one of those categories when it comes to new innovations.

OpenClaw isn’t “bleeding edge” because the underlying AI is new. It’s bleeding edge because it provides a structure for how AI will ultimately interact with the rest of our world.

What OpenClaw Is

Most people experience AI through interfacing with LLMs (Large Language Models) like ChatGPT. You open a browser or app, type a question, and get an answer. Think of it like you’re directly interfacing with a brain, providing it inputs and receiving outputs.

If you’re not providing the input or doing something with the output, nothing happens.

OpenClaw is the robotic Ironman suit for AI. It can use any “brain” or LLM you prefer.

Instead of interacting with a single, centralized AI, OpenClaw lets you create your own agents—small, specialized pieces of intelligence that you control. They can run on your own infrastructure, connect directly to your own data, and talk to other systems without you being in the middle.

It’s a preview of how businesses will operate once intelligence stops being a destination and starts becoming infrastructure.

⚠️ Quick Warning Before You Look Up OpenClaw

OpenClaw isn’t plug-and-play.

You’re managing infrastructure, API keys, data access, and security yourself. These agents can connect to and act within real systems which means misconfiguration isn’t theoretical.

You should never install this on your main computer.

If you’re non-technical, proceed carefully or wait for more mature versions to be released.

How This Changes Business

Here are five shifts from agentic workflows that are coming faster than most companies realize.

1. Ownership Beats Intelligence

Raw intelligence is becoming cheap. High quality, proprietary data is not.

As AI capabilities commoditize, competitive advantage shifts to who owns, controls, and governs the underlying data. Businesses that rely on external tools without clear data boundaries will find themselves renting their own institutional knowledge back from someone else.

We’ve already seen a version of this movie.

When companies outsourced their e-commerce storefronts to Amazon, they gained distribution but lost customer ownership. Amazon kept the data. Over time, that data advantage became strategic leverage.

The same dynamic is now emerging with AI.

If your product conversations, internal documents, workflows, and customer interactions all live inside someone else’s framework, who compounds from that learning?

In the future, strategy won’t start with: “What AI should we use?”

It will start with:

“What data or processes do we truly own and how are we learning from it?”

2. Software Becomes a Network, Not a Product

In an agent-driven world, all tools must communicate.

Your product won’t just serve humans but agents as well. If your service can’t be accessed programmatically, orchestrated automatically, or composed into larger workflows, it will be invisible to the systems doing the actual work.

Stripe is a perfect example of this shift. It didn’t win because it had prettier dashboards. It won because it made payments programmable. A few lines of code unlocked global commerce.

That will be the minimum standard going forward.

APIs (Application Program Interfaces) aren’t a feature anymore. They’re just as much the front door as a well designed user interface.

3. Interfaces Disappear

In the film Her, Joaquin Phoenix’s character doesn’t open apps or navigate dashboards. He speaks and the system understands. It responds fluidly, contextually, invisibly.

That wasn’t simply a story about romance with an operating system. It was a story about the disappearance of the interface.

The best interface is no interface.

Users won’t click through dashboards to get things done. They’ll state intent, and systems will act. The mental model shifts from operating software to communicating and collaborating with it.

When intelligence moves into the background, friction becomes intolerable. Anything that requires excessive configuration, navigation, or explanation will feel broken even if it technically works.

4. Work Becomes Modular

Jobs won’t disappear, they will decompose.

Instead of hiring for broad roles, companies will assemble work from smaller units: human judgment, automated analysis, agent execution. Some tasks disappear. Others shrink to oversight and exception handling.

For my own work and the companies I advise, I’ve started pushing teams to evaluate job tasks instead of roles.

Instead of asking:

“What does our marketing manager do?”

Ask:

“What recurring tasks create value, and which of those require human judgment?”

You’ll often find that 30–50% of a role is structured information gathering, formatting, reconciliation, or reporting. Those tasks are modular. They can be separated from the identity of the job.

The org chart becomes less important than the workflow graph.

Companies that rethink work at the task level will scale faster than those defending job titles.

5. Strategy Becomes Continuous

The US Government still relies on monthly phone surveys to estimate employment and economic conditions while e-commerce platforms have real-time transaction data on millions of consumers.

When agents can monitor markets, customers, and operations continuously, strategy stops being an annual exercise. It becomes a living system updated weekly if not daily.

The companies that win won’t be the ones with the best five-year plans.

They’ll be the ones that adapt to a different way of processing and understanding information and work itself.

The Next Step

The large mobile brick phone didn’t change the world overnight. It just signaled where it was headed. Same as the printing press, the internet and every other major innovation in human history.

AI and the development of agents feels similar. Unevenly distributed and unfamiliar.

You don’t need to rebuild your company tomorrow. But you do need to start experimenting.

Open an API. Automate one workflow. Decompose one job into tasks. Connect one system to another.

If you’re not regularly using AI through a chat app or website you should make yourself familiar and learn how these models work.

The future spreads to the people who play with it first.

My goal with The Leap is to provide you each Saturday with the knowledge, tools and lessons learned to help you get started and keep going toward building your future. 

Whether you are making the leap to startups, solo-entrepreneurship, freelancing, side hustles or other creative ventures, the tools and strategies to succeed in each are similar.