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@tjrobertson52

2026-05-24

Stop building complex AI workflows for things that'll be easy in 3 months. Wait until it's easy, then go HARD and don't look back...

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So you know you should be doing more with AI. You know there's work you're doing right now that AI could do better, but you also know what it feels like to spend a week figuring out how to hand something over to AI, only for some new feature or tool to come out and completely replace your process. Or maybe to just give up after a week because it was too hard.

I'm gonna talk about the framework I used to determine when it's the right time to hand something over to AI.

In short, my philosophy is: wait until it's easy, then go hard.

Whatever you're trying to do with AI, if it's worth doing, it's a pretty safe bet that it's going to be easy to do pretty soon. One of the most common mistakes people make, and I've made it myself, is you see something that you could do if you just strung these three tools together and you bolted a few features on. AI could totally do this task.

Well, before you start building that custom solution, just ask yourself, is this something that would be valuable to other people? Because if so, it's a pretty safe bet that Google or Anthropic or OpenAI are just going to add this as a feature to one of their existing platforms.

Now there is one caveat to this rule. Sometimes things are hard to give her to AI for structural reasons. For example, for AI to do meaningful work inside your business, it needs to have access to all the information about your business.

Gathering and organizing all that information is hard. The difference is that's always gonna be hard.

I mean, don't get me wrong, AI already makes that a lot easier, but you probably have a lot of information that just exists on someone's hard drive or in the heads of your team members. Getting all of that information into structured documentation that AI can access is just gonna take some time. If AI is not coming to save you and it's always gonna be hard, just eat the frog, do the hard work.

But otherwise, wait until it's easy.

Things are moving too fast right now for you to be wasting your time on something that's going to be easy soon. But as soon as it is easy, you need to go hard.

As soon as one of the major AI platforms releases a new capability or feature that makes some task easy, there's a limited window of opportunity. Depending on your industry, you may have six months or a year from that point before it's just standard practice. All your competitors are gonna start turning that task over to AI, or at least your serious competitors that aren't destined to be disrupted by AI in a few years.

So as soon as it's clear how to turn a task over to AI, go hard. Start testing, start putting together SOPs, start iterating on the process. Become the best business in your industry at using AI for that task.

And by the time your competitors getting around to testing it, they'll be discouraged by how much better you are.

Source Intelligence

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AI work is worth doing early when the difficulty is structural, such as organizing business knowledge for AI access.

AI workflow timing · asserts

  • Prioritize structured business documentation now, and wait on custom AI workflows that major platforms are likely to make easy soon.

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What is this source mainly about?

AI work is worth doing early when the difficulty is structural, such as organizing business knowledge for AI access.

What should an operator take from it?

Prioritize structured business documentation now, and wait on custom AI workflows that major platforms are likely to make easy soon.

Which topics does it connect to?

This source is connected to AI workflow timing.

What public evidence supports the record?

So you know you should be doing more with AI. You know there's work you're doing right now that AI could do better, but you also know what it feels like to spend a week figuring out how to hand something over to AI, only for some new feature or tool to come out and completely replace your process...