From Co-Pilot to Auto-Pilot: AI Agents Are Taking Over

The One-Person Unicorn, Revisited 

I wrote in my 2024 AI predictions that we may soon see a one-person unicorn.

Looking at the references above, this should start to feel less and less hypothetical.

If an AI can autonomously figure out how to best do something, work with other agents, and direct itself, then scaled to 1,000s of them, a simple idea could turn into a billion-dollar company. 

But not just anyone will create that unicorn, I was reminded when I heard Loveable founder Anton Osika on Lenny’s Podcast. 

Loveable lets a user describe an app in plain language and have the AI instantly generate a working web application – effectively coding, testing, and deploying on the fly. 

On the podcast, the pair discussed that it’s becoming less about how to build something, more about what to build and why. In other words, the role of “Product Manager” may be a better lens to look at the future of work. 

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The emphasis is on guiding resources rather than personally executing every step and becoming a strategic director for hybrid teams of humans and AI agents.

To tap into the full benefits of AI agents, we all need to become AI orchestrators and set up the proper prompts, tools, and checkpoints. 

We need to know what they’re capable of and get them going, occasionally providing the strategic context that AI lacks. 

As The AI Daily Brief’s Nathaniel Whittemore explained in a terrific video essay, this will eventually evolve into the equivalent of Dr. Strange scanning through many multiverses.

Steering an AI agent organization like this, with thousands or millions of agents each better than the foremost human expert in their field – the one-person unicorn doesn’t seem so futuristic anymore. 

Getting on the Train Now

These developments and the far-reaching implications of truly agentic organizations create even more urgency for us all to get on the train.

Even if you don’t have any ambition to be the founder of a one-person billion dollar unicorn, you’ll want to be at least a SuperWorker, an “an individual who uses AI to dramatically enhance their productivity, performance, and creativity.”

In other words, someone who takes that ‘genius laser’ Sam Altman describes and points it at every objective and challenge in their role.

Here’s what you can do today:

• Determine which elements of your role are General, Error-Friendly, Digital, Recurring, and Toil. These “GED-RT” tasks are prime for AI to take over.
• Implement AI tools that work as a co-pilot or autopilot, with you or for you. From off-the-shelf products like Copilot for PowerPoint or Gamma AI to self-built AI automations and AI agents like Deep Research, Loveable, Operator or Manus. (See Build Your AI Team if you need help or check out these other AI courses.)
• Personalize and fine-tune each tool. Gamma and other AI websites are great, but works even better with your brand assets. ChatGPT and other AI models are excellent, but works way better when you program custom-trained GPTs. 

As Loveable’s founder said: “being extremely proficient with AI tools is now a superpower.”  Being in the top 1% or even 10% of AI tool users will dramatically set you apart. 

And that’s how you get to lead in the future of work.

Go!

Every week, I highlight a real-world AI use case to spark ideas and inspirations for how you can implement AI in your team and business. For this week:

AI Helps This Small Business Stay Lean & Smart

Daily Harvest is a small company that delivers plant-based meals across the U.S. while managing complex logistics with a lean team. They know how to apply AI to leverage their data, automate decision-making, and enhance customer interactions—all while maintaining operational agility.

They implemented AI in ways:

• Personalized product recommendations – AI analyzes customer orders and browsing behavior to suggest relevant products, keeping offerings fresh and engaging.
• Automated customer support – AI chatbots handle routine inquiries, while predictive models flag customers at risk of canceling, directing them to human agents for retention efforts.
• Optimized fulfillment & packaging – AI determines the right amount of dry ice based on order size and weather conditions, reducing waste and ensuring deliveries arrive in top condition.

By adopting specialized AI tools, Daily Harvest streamlined operations, improved customer satisfaction, and maximized cost savings—without needing a massive team.

>> Read more details here.

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News & Updates

I read dozens of AI newsletters weekly, so you don’t have to. Here are the top 3 insights worth your attention:

#1

OpenAI is reportedly launching a $20K/month “PhD-level” AI agent, with $10K and $2K versions for “developers” and “knowledge workers.”

While OpenAI has demonstrated strong AI benchmark performance, real-world accuracy and cost-effectiveness remain open questions.

Might it be the company’s push for high-end enterprise AI amid reported financial losses? What’s your take on this move?

#2

AI in fast food isn’t new, but McDonald’s just raised the stakes—rolling out AI-powered drive-throughs, smart kitchen sensors, and edge computing across 43,000 restaurants.

CIO Brian Rice is betting on tech to streamline operations, cut errors, and reduce worker stress. WSJ reported the details here.

#3

Microsoft's deep GPT integration and its recent $13B investment in OpenAI don’t guarantee exclusivity!

​Bloomberg recently reported that Microsoft has quietly developed its own AI models, MAI, which have been benchmarked as competitive with top-tier models from OpenAI and Anthropic.

High hopes?

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