Cloudron makes this even easier. Well worth 1.00 a day! Handles the entire stack (backups , monitoring , dns , ssl , updates ).
Readit Newsreachableceo commented on CLI agents make self-hosting on a home server easier and fun fulghum.io/self-hosting... · Posted by u/websku
Why not use Vaultwatden for this ? It has a built in dead man switch recovery system.
I’m planning to add Cursor and Cline in the next major release, will try to get in out in Jan
Please also add qwen cli support
reachableceo commented on Tell HN: AI coding is sexy, but accounting is the real low-hanging target · Posted by u/bmadduma
I should say upfront I don’t hate humans or CPAs.
What I’m working on is the opposite of that. I want to free humans from boring, repetitive finance work so they can use their time for higher-value and more creative things.
While building an “AI CFO” for small businesses (LayerNext), I’ve learned a few things that changed how I see bookkeeping:
Most of bookkeeping is repetitive and under-optimized. Everyone says “90% of the work is repetitive,” but we still hire bookkeepers and bookkeeping firms. Most small businesses I talk to pay around $300–$800 per month just for bookkeeping. Even after paying that, I really doubt every single transaction is recorded in the most tax-optimized way. There are hundreds of transactions, constant government tax rule changes, and limited time.
Current automation is stuck at rules you manually define. Tools like QuickBooks can categorize transactions based on rules you create. That’s it. As soon as something new comes up, you still need a human to either, create a new rule, or manually enter and categorize it.
And even when you hire a human bookkeeper, you still end up doing half the work anyway: sending receipts, answering clarification emails, chasing missing information.
Invoice and expense capture can be 100% automated, even with edge cases In practice, invoice and expense capture is the easy part. With decent models, you can get 100% accurate capture from receipts, PDFs, emails, etc. Edge cases are solvable with better parsing and validation, not more humans.
Reconciliation is the hard part, but reasoning models are getting very good. This is where things get tricky: - multiple invoices paid in a single payment - partial payments - refunds, chargebacks, etc.
For example, imagine a consulting company issuing several invoices to the same customer and receiving one lump-sum payment. We’ve had success using deep research like reasoning to match payments to invoices and handle those cases automatically.
AI can sometimes care more about details than a human. One moment that surprised me.We had a credit card transaction with no receipt.
The question was whether it should be classified as “office expense” or “meals and entertainment” (in Canada these have different tax treatments). When I checked trace of the agent, it looked up the vendor online to understand what they actually sell, checked CRA tax rules and then picked the GL account that maximized the tax benefit for the company.
I’m not sure many manual bookkeepers consistently do that level of research when they’re trying to reconcile 500+ transactions and half the receipts are missing.
My goal is to build a fully automated financial assistant that can close the books without a CPA or bookkeeper, with ~99% accuracy across all transactions, and with the explicit goal of maximizing tax benefits within the rules.
Other outcome is accurate rea-time books can generate good insights to grow the business.
So I don’t see a good reason why small businesses should pay hundreds of dollars per month for humans to do mechanical work that machines can now do, often more consistently and with better attention to tax details.
Curious how others see this, especially CPAs and engineers who have built accounting tools. Is there a fundamental reason we need humans in the loop for the majority of small business bookkeeping, or is it mostly inertia and habit?
What you are talking about is called financial operations.
And yes , automating that , very valuable.
Really you want an AI interface to a rules engine / system.
Embed with some companies finops teams if you can. Especially the software engineers who are in finops.
Sorry, isn't this running an open-source OS? The header has a link to a github with a non-commercial license[0].
If so, couldn't you just use the OS on non-premium-priced mini-PC hardware and never have to worry about them locking you out of your box? I guess maybe it's concerning if you're being forced to update by the OS? I've never actually run a system like that, but was considering umbrel OS (didn't actually know about the hardware until this post), so if I'm being naive about something, it's in earnest.
I run umbrel in a VM . For non fiat finops stuff.
I also run Cloudron on a VPS.
I wish both of those solutions had more mindshare. They save me so much time and effort. Especially Cloudron!
reachableceo commented on RoboCrop: Teaching robots how to pick tomatoes phys.org/news/2025-12-rob... · Posted by u/smurda
I understand the desire of academics to help agriculture, but they really need to check in with the field before coming up with prototypes like this, because they are duplicating existing things (ag companies already do this), making hardware that would never survive the field (ag companies already solved this), and obscenely expensive (ag companies come up with better cheaper solutions).
Really? Can you link to those solutions please ?
Hey everyone, I work on PGlite. Excited to see this on HN again.
If you have any questions I'll be sure to answer them.
We recently crossed a massive usage milestone with over 3M weekly downloads (we're nearly at 4M!) - see https://www.npmjs.com/package/@electric-sql/pglite
While we originally built this for embedding into web apps, we have seen enormous growth in devtools and developer environments - both Google Firebase and Prisma have embedded PGlite into their CLIs to emulate their server products.
Well downloads doesn’t equal usage does it ?
How do you know how many deployments you actually have in the wild?
reachableceo commented on Building the largest known Kubernetes cluster cloud.google.com/blog/pro... · Posted by u/TangerineDream
K8S clusters on VMs strike me as odd.
I see the appeal of K8s in dividing raw, stateful hardware to run multiple parallel workloads, but if you're dealing with stateless cloud VMs, why would you need K8S and its overhead when the VM hypervisor already gives you all that functionality?
And if you insist anyway, run a few big VMs rather than many small ones, since K8s overhead is per-node.
VMs are a standardized system primitive. The “bare metal” bit with RBAC etc through the management layer / hypervisor.
K8s is pallets Vms are shipping containers
Systems / storage / network team can present a standardized set of primitives for any vm to consume that are more or less independent of the underlying bare metal.
Then the VMs can be live migrated when the inevitable hardware maintenance is needed (microcode patching , storage driver upgrades , etc etc etc). With no downtime for the vm itself
reachableceo commented on Restaurant Shift Scheduling via Linear Optimization and Staff Constraints · Posted by u/emmahexa
This is super helpful — thank you. Here's how I think they can be solved:
1. Flagging special events by pulling from the booking system so the schedule doesn’t assume a “normal” Monday.
2. Tagging staff by skillset (large parties, wine, expo, etc.) so the optimizer doesn’t just fill slots but matches people to the right shifts.
3. Flexible availability instead of binary availability — things like “prefer not,” “can pick up if needed,” “no doubles,” “no clopens,” or “I already have a cover lined up.”
4. Transparent fairness — showing why someone got (or didn’t get) a shift, how hours were distributed, and what trade-offs were made so it’s not a black box.
5. Built-in shift-swap handling, since FOH often sorts coverage themselves before the manager ever touches it.
How do you compare to When To work? Or Hot Schedules ?
So we decided to build a tool that WE would actually use, and once we succeeded with that, we open-sourced it. Since then we've received a lot of feedback on where to take this product - some use cases Anthropic will probably never do, like integrating Codex or adding other z.ai GLM subscription.
We're just trying to ship something we use ourselves, and maybe it could be useful to others, and see where it goes.