Automate the Boring Stuff
A Python book changed how I thought about finance work. Lumera is what I wished existed back then.
Circa 2015, when I was working a weekend on year-end close, I was deep in a gigantic Excel workbook. 10+ tabs, fancy colors and formatting, nested IF statements, chains of VLOOKUPs. You know those workbooks. It was formula kung-fu. My husband walked past my desk and stopped.
He’s a software engineer. He watched for a minute, then said “you should read this” and sent me a link to Automate the Boring Stuff with Python.
I loved this book because it had practical, real life things you could automate by coding in Python. I learned Python and Ruby, shipped some small apps, and started thinking like a builder. But more than coding, that book changed how I looked at my own work. I started pausing before diving into a task. Not just to get it done, but to ask different questions. Why is this manual? What upstream system is producing data in a format that forces me to clean it every time? If I fix this step, what does that unlock downstream?
That shift in perspective ended up mattering more than any individual thing I built. I could see the inefficiencies clearly. I could even prototype solutions. But I couldn’t get any of it into production at work. I could build a script and run it locally on my laptop, but deploying it into an actual workflow with the right controls, integrations, and approvals was a completely different problem. And that gap, between seeing what should change and having the infrastructure to actually change it, is where everything stalled.
What’s different now
Coding agents can take a description of what you need and produce working software. The learning curve that used to take months has compressed dramatically. But I think the narrative around this moment is slightly off. The technology is impressive, but it was never really the bottleneck. The bottleneck was always access. The people who understand finance workflows deeply enough to know what should change are the same people who historically didn’t have the tools to act on it.
Why we’re building Lumera
I started Lumera because I lived this arc. From that Excel workbook to learning to code to seeing the bigger picture to wanting infrastructure that could actually take these ideas to production. The thesis is straightforward. The people who understand finance workflows should be able to build and deploy real automations. Not prototypes that live on a laptop. Production-grade applications with the controls, integrations, and audit trails that the work actually demands.
You can now go from identifying a broken process to deploying a fix without a six-month IT project in between.
The learning curve isn’t gone, though. You still need to think carefully about controls, about what should be automated versus what needs a human in the loop, about how things fail gracefully when the data is messy. There’s a real layer of auditability, approvals, and compliance that matters here and that most of the AI conversation glosses over. But the learning curve is a domain curve now, not a technical one. And that’s a curve you’re already up.
A renaissance for finance teams
Coding agents paired with production-grade infrastructure to ship real solutions have unlocked a level of creativity and possibility that I don’t think most people in finance have fully grasped yet.
This week, we shipped an app template on Lumera for an AI agent that monitors a team’s shared AP inbox. The agent reads inbound emails, categorizes them based on the nature of the email (invoice, vendor payment inquiry, new vendor onboarding, etc.), assigns a priority level for your review based on email context, checks if the vendor or invoice already exists in your AP system, and drafts a response for you keeping all of your business context in mind.
I’m amazed that this app only took a few hours of focused building on our part, and is now ready for our users to clone into their accounts, further customize by chatting with our coding agent, and then deploy those changes within minutes to their team.
The spirit of “automate the boring stuff” is alive and well. The difference is that now, when you pause and see the process clearly and think “this could be better,” you can do something about it.
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Sowmya is the CEO and co-founder of Lumera, AI infrastructure for finance teams. She was previously Controller at OpenAI and Rippling, and led Corporate Accounting at Square.