Flip AI Development on Its Head

Most people have AI development backwards.

The conventional approach is seductive: throw your problem at AI and let it figure everything out. Feed it the idea, step back, and wait for the magic.

But this is exactly wrong.

The Real Approach: Granularity First, AI Second

What I truly believe is that we need to get granular on tasks first, then create automated systems that—in many cases—don't even need AI to accomplish them. Or, when they do need AI, the AI augments specific steps rather than replacing the entire process.

Consider the task of writing a blog post. It seems like one thing, but it's actually a step-by-step process:

1. Come up with an idea — What am I going to write about?
2. Write it out and structure my thoughts — Get the ideas down, organize them
3. Create different sections — Break it into digestible chunks
4. Log into the system — Upload the blog post to the internet
5. Create and upload an image — Either make one or select from existing images

This granular understanding is everything. If you understand each individual step of the process, then AI can actually call the tools that accomplish each step.

This Pattern Is Everywhere

The same principle applies across every business function.

Grocery shopping by an employee:

• Get in the car
• Drive to the grocery store
• Pay for the groceries
• Pick them up
• Drive back
• Unpack
• Cook the food

Sales workflows:

• Reach out to 20 new people a day
• Do 5-10 calls
• Track conversion rates
• Report results back to the CEO in compact format so they can say "Yes, that was done right" or "No, we need to adjust"

Why Granularity Unlocks AI

When processes are granular, two things become possible:

1. You can automate without AI — Many steps are just deterministic: log in, upload, navigate. No intelligence required.
2. AI becomes a precision tool — Instead of hoping AI will "figure out" your vague problem, you apply AI to the specific steps where it adds value. AI can help with ideation. AI can help structure thoughts. AI can draft outreach messages. But you control which steps get AI augmentation.

The difference between hoping AI will figure it out and designing precisely how AI will help is the difference between magic thinking and engineering thinking.

The Uncomfortable Truth

To use AI effectively, you must first become an expert at the very thing you want AI to do.

You must earn the right to delegate.

This seems counterintuitive—shouldn't AI save us from having to understand things? But the reality is: you cannot automate what you do not understand at a granular level.

The people who will thrive in the AI era aren't those with access to better models. They're those who understand their own work at atomic resolution.

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AI doesn't solve problems. It executes steps within processes understood by humans who bothered to do the work of knowing their work.