When the obvious next step is the wrong one.
The natural extension of the integration work pointed toward a bank feed — automatically reconciling income data against actual payments, removing the last manual thread from the reporting cycle. We scoped it. And we decided not to build it.
Bank feed integrations for custom-built projects carry a level of compliance overhead that sits well outside the scope of a reporting tool. More importantly, the reconciliation UI required to communicate what an automated process has done — the edge cases, the mismatches, the exceptions — would have taken the project somewhere neither of us wanted it to go. We would have spent months building something that made the process more complicated to audit, not less.
Instead, we experimented with something smaller and more interesting. As we had started building AI-powered tools internally, we saw a different kind of opportunity — not a full automated reconciliation pipeline, but an agent-based approach that could handle the messy, judgment-heavy parts of reconciliation without requiring a complex UI to surface it. We built a Reconciliation Agent as an internal experiment: a lightweight, composable tool that could do meaningful lifting in a fraction of the time.
— Codemyriad on the Aire Spaces engagement”It was not just about using agents to get work done smarter. It was about finding ways to get something valuable into the client’s hands quickly — something that would have taken months to build properly as a traditional UI.”
The Reconciliation Agent is an ongoing internal experiment. A write-up is in progress.