Not every AI idea is worth pursuing. Most of them are distractions dressed up as opportunities. The challenge is telling the difference fast enough that you don't waste weeks on low-leverage experiments.
I use a simple test I call the Leverage Test. It has three questions:
The Three Questions
1. Does this reduce a recurring cost? If it only saves time once, it's not leverage. Real leverage eliminates a cost you'd pay repeatedly — weekly content creation, daily data processing, ongoing client communication.
2. Does the output improve with repetition? If you run the same process 100 times, does it get better? Systems with feedback loops compound. Static automations don't.
3. Can someone else run it? If only you can operate the system, it's not leverage — it's just work with extra steps. True leverage is transferable.
If an AI idea passes all three, it's worth building. If it passes two, it might be worth a small experiment. If it passes one or zero, skip it.
Key Takeaways
- 1Apply the three-question Leverage Test before committing to any AI idea
- 2Real leverage reduces recurring costs, compounds over time, and is transferable
- 3Most AI opportunities fail at least two of these criteria
