These models are open and there are tons of western providers offering it at comparable rates.

I can not find a description of how it works on the site, magic hands daemons !

Cool story, but what runs when?

tl;dr : https://charlielabs.ai/how-it-works/ and https://docs.charlielabs.ai/daemons

to get started, look at https://docs.charlielabs.ai/installation, but essentially

1) signup with your github login

2) install the CharlieCreates GitHub App on the repos you want Charlie to work in

3) create an issue, tag @CharlieHelps to help you create your first daemon!

the daemon will run on the charlie runtime and follow the watch / schedule conditions you set in your DAEMON.md file

full disclosure: i am part of the engineering team behind this.

Fix them if needed, the OP’s point is that for a lot of applications it is not needed.

For most cases you will still be comfortably in the JVM/golang performance window.

Rust is great language, fighting the borrow checker sucks, don’t do it if you don’t need to.

Do you not value your time? Paying a 100 bucks for a Claude max subscription is well worth it

Opportunity costs: Would you rather pay 100 bucks for making more money or for your foss projects?

The same can be said of your time, but here we're talking about scale benefits due to LLMs (i.e. lots of SaaSs dying due to lots of "full featured f/oss projects").

AI is pretty good at following existing patterns in a codebase. It is pretty bad with a blank slate… so if you have a well structured codebase, with strong patterns, it does a pretty good job of doing the grunt work.

The read-only hesitation seems overcautious. If you’re genuinely using it read-only, what’s the failure mode? The tool crashes or returns bad data - same risks as the AWS CLI or console.

The “middleware layer” concern doesn’t hold up. This is just a better interface for exploring AWS resources, same as k9s is for Kubernetes. If you trust k9s (which clearly works, given how widely it’s used), the same logic applies here.

If you’re enforcing infrastructure changes through IaC, having a visual way to explore your AWS resources makes sense. The AWS console is clunky for this.

> what’s the failure mode?

The tool misrepresents what is in AWS, and you make a decision based on the bad info.

FWIW I agree with you it doesn’t seem that bad, but this is what came to mind when I read GPs comment

Fair. Best use might be to double check on the proper UI before making any big decisions, and just use it as a general monitor

I mean sure… but to me that is as likely as the official ui misrepresenting the info.

The fakes vs mocks distinction here feels like a terminology debate masking violent agreement. What you’re describing as a “fake” is just a well-designed mock. The problem isn’t mocks as a concept, it’s mocking at the wrong layer. The rule: mock what you own, at the boundaries you control. The chaos you describe comes from mocking infrastructure directly. Verifying “deleteUserById was called exactly once with these params” is testing implementation, not behavior. Your HashMap-backed fake tests the right thing: is the user gone after the operation? Who cares how. The issue is finding the correct layers to validate behavior, not the implementation detail of mocks or fakes… that’s like complaining a hammer smashed a hole in the wall.

Google had a good 10 year run, where the ads were genuinely useful, until the need of the public markets required and lack of competition allowed them to enshitify the experience to the current state.

I hope the same fate does not await ChatGPT but in the mean time I expect it to be a pretty good experience at first.

Comments it seems taken in bad faith

It's a legitimate concern.