Introduction

AI agents are rising, but companies still need one clear place where truth lives. This piece explains why systems of record still matter more than ever.

What's the problem it solves?

Many people say AI agents, workflows, or data layers will replace systems of record. The problem is that without one clear source of truth, automation breaks fast. Agents can move quickly, but if they use wrong or mixed data, they automate mistakes at scale.

Quick Summary

Jamin Ball argues that systems of record are not dying. What really matters is not the app, but where the truth lives. When an agent runs a workflow, it must know which number or record is the correct one.

In real companies, even simple metrics like ARR mean different things to sales, finance, and legal. Humans can debate and align. Agents cannot. They need clear rules, clear owners, and clear data definitions.

Warehouses, lakehouses, and operational systems are becoming the backbone of truth. Agents sit on top of them, reading and writing data. The UI changes, but the need for strong data contracts and ownership only grows.

Key Takeaways

• Systems of record are about truth, not software categories
• AI agents make bad data more dangerous, not less
• Warehouses are turning into truth registries, not just reporting tools
• Agents need explicit rules, not human judgment
• Operational systems will shift to API first, not UI first

What to do

• Define one canonical source for each key metric
• Document which system owns which truth
• Build clear metric definitions agents can follow
• Treat data governance as core infrastructure, not overhead
• Design AI workflows around existing sources of truth, not around hype

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