Living in Germany with financial ties to Ukraine means three bank accounts, two countries, two currencies, and a lot of monthly bookkeeping nobody wants to do.

For years I’ve tracked every transaction in plain text files — think of it as a spreadsheet, but stored in simple text that I can search, version, and back up like any other document. The system works great. The data entry? Not so much.

Every month: log into three banks, download statements, match each transaction to a category, update the books, file expense reports. An hour of tedious work that I kept postponing until the weekend.

So I automated the whole thing with an AI assistant.

What It Does Now

Every night at 10 PM, the AI:

1. Connects to all three banks and downloads the latest transactions
2. Categorizes each transaction — groceries, insurance, school fees, subscriptions — using rules I’ve taught it over time
3. Saves everything to my accounting files and backs them up
4. Sends me a summary on Discord: balances, new transactions, anything it couldn’t categorize

When it finds a new merchant it hasn’t seen before, it flags it. I reply with the category — “that’s a pharmacy” — and it remembers forever.

The Expense Report Part

Here’s what I’m most proud of. Some of my bank charges are business-related and need to be filed as expense reports. Cloud services, work tools, that kind of thing.

The AI now does this automatically:

1. Sees the charge on my bank statement
2. Looks up the amount in local currency
3. Creates an expense claim in the accounting software
4. Done

What used to be: download statement → open accounting app → fill in the form → save → forget for three months and do them all at once. Now it just happens.

What Surprised Me

Teaching is faster than doing. The first month, I had to categorize about 30 merchants. The second month, maybe 5 new ones. By the third month, almost everything is automatic. Each correction makes the system smarter.

The AI handles the boring parts, not the decisions. It doesn’t decide how to categorize a new restaurant. It asks me. It doesn’t file expense claims without permission. It asks first. But it never forgets to download statements, never fat-fingers an amount, and never procrastinates until Sunday evening.

Three banks, two countries, one conversation. German bank, PayPal, Ukrainian bank — the AI talks to all three using their respective interfaces. I just see the summary.

The Monthly Effort Now

Before: ~1 hour of manual bookkeeping per month, usually done reluctantly.

Now: maybe 5 minutes categorizing a few new merchants in a chat message. Everything else runs on autopilot.

The books are always up to date. Expense claims get filed on time. And I stopped dreading the last Saturday of the month.

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If you’re curious about the technical setup: the system uses ledger-cli for accounting, connects to German banks via the FinTS protocol, and talks to Manager.io for company expense claims. The AI orchestration runs on OpenClaw. Everything is version-controlled in Git.

I’ve been managing an SRE team at Billie for about 15 months. A month ago, I set up an AI assistant. It’s an open-source gateway called OpenClaw that connects Claude to my tools, and I talk to it through Telegram.

Let me just walk you through last Wednesday.

Before my first meeting, the assistant checked my inbox. Found an invoice from my old tax advisor, a service I’d already cancelled. It drafted a reply asking about formal termination steps and sent it. The email bounced because of a wrong reply-to address. It caught that, resent. By lunch, the advisor had replied with three PDFs to sign. I signed them, the assistant sent them back. Done. That whole thing would’ve sat in my inbox for a week if I’m honest.

Between meetings, I needed to contact my daughter’s English teacher about a bad test score. I emailed the wrong teacher. Turns out there’s an “Elab” teacher and a regular English teacher at her school, and I mixed them up. The assistant dug through my inbox, found the right name from an old email, drafted an apology to teacher #1, wrote a proper message to teacher #2, CC’d my wife. Two emails, right tone, maybe five minutes total.

In the afternoon I had an ADR review at work. The assistant didn’t help with that. It was a room full of engineers debating tradeoffs, and my actual challenge was figuring out when to drive the conversation and when to shut up and let someone else present. That’s a leadership problem. There’s no API for it.

After work, I’d noticed a new community center opening near my apartment while out walking. The assistant looked up their website, I wrote an intro email offering IT help as a neighbor.

Evening: LinkedIn post about a Claude Code plugin. Some journaling about how the day went. Set a reminder to try meditation the next morning.

Tax paperwork, parenting logistics, architecture reviews, community outreach, writing, self-reflection. One Telegram chat, one day.

What I think after a month

The value is in not switching contexts. Each individual thing the assistant did was small. Draft an email, search an inbox, look up a website. But I didn’t bounce between seven apps and three mental modes to get it all done. It happened in one thread, and that thread has memory.

The boring stuff actually gets done now. I still read every email before it goes out. I still decide everything. But the distance between “I should handle this” and “it’s handled” got very short. That tax thing is a perfect example. It’s not hard. It’s not important enough to do right now. So it festers. Except this time it didn’t.

Where it matters most, it’s useless. The ADR meeting, the 1:1s with my reports, the gut feeling that someone on the team is burning out. That’s me. AI clears the admin noise so I can spend more time on those things. It doesn’t make me better at them.

Work and life are in the same stream. My daughter’s teacher and my ADR review happened in the same chat, same afternoon. I know some people find that messy. For me it means fewer things slip through because everything lives in one place.

I don’t have conclusions yet. It’s been a month. I have no productivity metrics, no hours-saved calculations. I just notice that things that used to linger are getting done. Whether that’s genuinely useful or I’m just building a new dependency, I honestly don’t know. Check back in six months.