📺 AI Agents…The New Netflix?

I canceled cable in 2011. 

Fifteen years later, I still stream everything.

Now more and more people tell me how they also cut cable to save money, yet we’re all signing up for Netflix, Hulu, Disney+, Paramount, Fox One, and HBO only to realize the monthly total surpassed what cable used to cost.

And most nights, we all still have no idea what we want to watch anyway.

Or in my case, I just replay National Treasure or Roman Empire for the 19th time.

AI is running that same play right now, except the apps show up faster and every one of them claims it can do it all.

The fix is not canceling everything…

And it is not adding a sixth tool that promises to replace the other five.

The fix is knowing exactly which job each subscription holds.

🔎 WHAT I FOUND

People rate AI as more valuable than their streaming services and still refuse to pay streaming prices for it, which tells you something about how they are buying.

Key Facts

• 💳 Almost nobody is paying yet - Only 3% of US households pay for AI for personal use, even with signups climbing (NPR)🔗
• 📊 Valued high, priced low - 35% of Americans say AI adds more to their life than most or all of their other subscriptions, and 40% of the people willing to pay cap it at $25 a month (Rev)🔗
• 🧾 The creep starts inside apps you already own - AI features keep arriving as a new paid tier inside software you were already paying for (Fast Company) 🔗

NPR followed a few people who pay, and the pattern was familiar.

• One woman runs two subscriptions at $40 a month and expects to add a third within the year.
• Another rotates between platforms depending on the task, because she thinks each model has its own personality and she wants to pick which one she is talking to.

That second habit is the interesting one, because she is doing something most people skip. 

She is matching the tool to the work.

Rev asked over 1,000 Americans what would make AI worth paying for. 

The top two answers tied at 18%:

• helping them avoid a costly mistake, and
• saving them a few hours a month (Rev) 🔗

Both answers describe an outcome, and neither one mentions a feature, a model number or a context window.

People buy access when what they want is a result, and that gap is where money leaks out of a stack. 💸

📌 WHAT IT MEANS FOR YOU

I get asked which AI tool someone should buy about four times a week.

But that’s like asking which power tool to buy before deciding if you are hanging a shelf or framing a house.

Here’s how to build your stack around the work you need to complete:

1) Write the jobs before you write the tools

Open a blank page and list what you need done every week. 

Maybe it’s writing in your voice, doing research you can trust, cleaning data, building images, answering customer questions, or helping you make decisions faster.

Those are the jobs.

Start there.

Most AI stacks get built the other way around. 

Somebody sees a new tool launch on X, subscribes on a Tuesday, and then spends the next month looking for a reason to use it.

That’s how you end up paying for five tools that can do three of the same things.

2) Give every job an owner, then cut the overlap

Go back to your list and assign one tool to each job. 

A single tool can own several jobs, but you shouldn’t have three tools doing the same job.

That’s where the streaming problem gets expensive $$$.

The overlap is easy to buy and hard to notice because it shows up as a handful of separate charges instead of one obvious bill.

The tools that stay are usually the ones doing several important jobs at a level you trust. 

The ones that go are usually the single-purpose apps you signed up for during launch week and forgot you were still paying for.

3) When the tools are tied, keep the one that knows you best

If two tools can do the same job at roughly the same level, keep the one that already knows your voice, your clients, your standards, and how you work. 

It’s time-intensive to set up all of that context somewhere else.

That is also the difference between using an AI tool and building a system with one. 

The leverage comes from having repeatable jobs, clear instructions, and standards the AI already knows how to follow. 

If you have to start from zero every time you open it, you still have a tool. You don't have much of a system.

That is the idea behind my Creator AI Skills Stack 🔗.

Teach AI your voice, map the workflows you want it to run, build a repeatable content system, and get a five-question filter for every new AI tool that comes across your screen. 

I also give you the exact toolkit I use with clients and a seven-day content plan, so you leave with a system you can actually use, not another folder of prompts.

👉 Three things to sit with, whatever industry you are in:

• Name the last AI tool you subscribed to and the job it was hired to do, in one sentence, without checking the website.
• Count how many of your tools could handle the single task you did most often last month.
• Decide which of your subscriptions holds enough of your context that switching away would cost you a full day.

✌️ YOUR TURN

Give this 15 minutes.

And do it with your bank statement open rather than from memory, because memory is generous.

Write down every AI subscription you pay for and the monthly cost, then write the one job each tool owns (or have chat/claude extract them).

Anywhere two tools share a job, mark it. Then hand the whole list to your AI with this:

"Here is every AI subscription I pay for, the monthly cost, and the job I use each one for. Find where two or more tools do the same job. For each overlap, tell me which one to keep based on where my saved context and instructions already live, what I would lose by canceling the other, and what job on my list has no tool assigned to it at all."

Cancel one thing before Friday, and give the money to the tool that already knows the most about how you work. Time to be bold, and time to level up.

Share your thoughts and tell me what your stack looked like once it was written down, because I would bet the overlap surprises you more than the total does (it did for me, and I build these for a living).

P.S. Your next customer isn’t human, and your next employee shouldn't be human either. My client, and good friend Callan Faulkner runs a company with 36 humans and 150+ AI employees handling the repeatable work across marketing, sales, operations, customer success, and finance. Her AI Employee Bootcamp 🔗 helps you build two of your own. It’s incredible. Build your first AI employees here. 🔗