Decision Logic Is a Bigger Competitive Moat Than Data

Someone asked me last night on LinkedIn, when everyone should be sleeping, where the decisions were made in an agentic workflow that I built. Great question. And it made me think about how little we talk about this part.

I’ve been building agentic workflows for over a year. And the hard part is never the model. It’s the decisions. What context does the agent need? What rules apply? What triggers an escalation? What runs autonomously and what needs a human? I spend more time on this than on prompts. By far.

Here’s my opinion: Decision logic is a bigger competitive moat than data. Everyone has data. Most of it is commoditised. But your decision layer is unique. And here’s the shift that matters: this isn’t about documenting how things are currently done. It’s about designing how they should be done, now that the old constraints of headcount, skills and time have been removed.

That’s the real opportunity. When you remove those barriers, every process in the business can be rewired from first principles. The way you price, approve, escalate, allocate. All of it.

And when you codify that into agentic workflows, you’re creating intellectual property. Not a process map. Not a handbook. A living, versioned, auditable asset that compounds with every decision it makes.

We need better tooling for this. The GitHub of decision management. Version control for decision logic, prompts, and workflows. Track changes, roll back, compare, improve. The same rigour software engineering brought to code needs to exist for AI decision architecture.

This is business process reengineering for the AI era. Rewire. Document. Audit. Improve. Repeat.

I’m still learning. But the companies that build this discipline will be very hard to catch.