Hi Reader,

Everyone’s talking about “AI agents” right now.

But most people are confused about where automation stops and agents begin.

Here’s the truth: they’re not as distinct as the charts make them seem.

Automation: If this happens, do that. Boolean logic. Predefined rules. Fast, reliable, but rigid.

AI automation: Same structure, but now you’re calling an LLM for one or more steps. Still deterministic overall, but with flexibility where you need it.

AI agent: Non-deterministic. Adaptive. Makes decisions autonomously. Simulates human-like reasoning.

But here’s the thing.

Most of what we’re building right now sits somewhere in the middle. And that’s exactly what you want.

The Real Problem

The hard part isn’t understanding the taxonomy.

The hard part is knowing what to build in the first place.

Smart founders get so caught up in what’s possible that they lose sight of what’s valuable.

“I could build an agent for that.”
“I could automate this entire process.”

Sure. You could. But should you?

Last month I talked to a founder who spent three weeks building an AI agent to manage his calendar. It was sophisticated. It could read emails, understand context, make scheduling decisions.

It was also completely unnecessary.

What he actually needed was a simple automation. Twenty minutes of setup. Done.

He’d confused technical sophistication with business value.

Here’s what I see happening.

We’re building solutions looking for problems. We see a new capability and immediately start thinking about where we can apply it.

That’s innovation theater, not business strategy.

Real innovation starts with the problem. The thing that’s actually costing you time, money, or sanity.

And we’re asking the wrong questions.

The question isn’t “what’s an automation vs. an agent?”

The real questions are: - “What actually moves the needle?” - “What do I need?” - “What does my team need?”

Start there and work backwards.

The Framework

Here’s how to think about this:

Step 1: Identify the actual problem

Not “I need AI for my business.” That’s a solution looking for a problem.

Instead: “Our sales team spends 4 hours a week manually entering data from discovery calls.”

That’s a problem. Specific. Measurable. Costly.

Step 2: Define what success looks like

“Sales team spends zero time on manual data entry. Call notes automatically populate CRM fields with 95%+ accuracy.”

Now you have a target.

Step 3: Choose the simplest solution

Do you need an agent? A workflow? A workflow with an agent in it?

It doesn’t matter. What you need is a solution to a problem.

For the CRM example? AI automation. A workflow that transcribes the call, extracts key data points, populates CRM fields.

Simple. Effective. Done.

Step 4: Build the minimum viable solution

Don’t build the enterprise-grade, handles-every-edge-case version.

Build the version that solves the core problem for 80% of cases. Then iterate.

The Deeper Truth

Here’s what I’ve learned after helping dozens of founders implement AI:

Bad thinking: “I need to understand every AI capability so I can figure out where to apply it.”

Good thinking: “I need to understand my business problems so I can figure out which AI capabilities might help.”

Bad thinking: “More sophisticated = better.”

Good thinking: “Solves the problem reliably = better.”

Bad thinking: “I should build this because I can.”

Good thinking: “I should build this because it creates measurable value.”

The best AI systems aren’t the most sophisticated. They’re the ones that solve real problems.

Sophistication is not the goal. Value is the goal.

Your Next Steps

Here’s what I want you to do this week:

1. List your top 3 time-consuming tasks

Things that actually drain your time or your team’s time every single week.

2. Define what success looks like

Be specific. “Save 2 hours per week” is better than “make it easier.”

3. What’s the simplest solution?

Maybe it’s automation. Maybe it’s AI automation. Maybe it’s just better documentation.

Don’t start with the technology. Start with the problem.

4. Build one thing this week

One solution to one problem. Make it work. Then make it better.

The Real Question

Do you need an “agent”? Or do you just need a workflow? Or do you need a workflow with an agent in it?

It doesn’t matter.

Stop building because you can. Start building because you should.

What are you building right now? Hit reply and tell me:

- What problem are you actually trying to solve?
- What solution are you considering?
- What’s stopping you from starting?

I read every reply. And if you’re stuck, I’ll help you figure out the right approach.

If you want help building AI systems that actually move the needle, that’s exactly what we do in the AI Mastery Cohort. We don’t teach you about agents vs. automation. We help you identify your highest-value problems and build solutions that create measurable impact.

Next cohort starts in just over a month. Reply if you want details.

-Dan