Tip:
LLMs are very good at following conventions (this is actually what is happening when it writes code).
If you create a .md file with a list of entries of the following structure:
# <identifier>
<description block>
<blank space>
# <identifier>
...
where an <identifier> is a stable and concise sequence of tokens that identifies some "thing" and seed it with 5 entries describing abstract stuff, the LLM will latch on and reference this. I call this a PCL (Project Concept List). I just tell it:
> consume tmp/pcl-init.md pcl.md
The pcl-init.md describes what PCL is and pcl.md is the actual list.
I have pcl.md file for each independent component in the code (logging, http, auth, etc).
This works very very well.
The LLM seems to "know" what you're talking about.
You can ask questions and give instructions like "add a PCL entry about this".
It will ask if should add a PCL entry about xyz.
If the description block tends to be high information-to-token ratio, it will follow that convention (which is a very good convention BTW).
However, there is a caveat. LLMs resist ambiguity about authority. So the "PCL" or whatever you want to call it, needs to be the ONE authoritative place for everything. If you have the same stuff in 3 different files, it won't work nearly as well.
Bonus Tip:
I find long prompt input with example code fragments and thoughtful descriptions work best at getting an LLM to produce good output. But there will always be holes (resource leaks, vulnerabilities, concurrency flaws, etc). So then I update my original prompt input (keep it in a separate file PROMPT.txt as a scratch pad) to add context about those things maybe asking questions along the way to figure out how to fix the holes. Then I /rewind back to the prompt and re-enter the updated prompt. This feedback loop advances the conversation without expending tokens.
Ultimately Kerberos is used to authenticated basically everything in a Windows on-prem environment and in a way that is largely transparent to the user. Silent SSO is a very nice feature.
Even if you're doing OIDC or SAML, those protocols do not define what is actually performing authentication at the IdP which, again, ultimately ends up being Kerberos if you're people are on-prem.
So whatever your feelings are about Kerberos as a protocol, it doesn't matter if that's what Windows uses.
And again, it cannot be obsoleted by other protocols.
Even if you're using a newer fido thing like passkeys or client certs or whatever, ultimately the device has to be authenticated to get that passkey or cert or whatever it is installed into the authenticator app of the device. So Kerberos is king on prem.
MIT Kerberos on Linux is not really compatible with Windows Kerberos in ways that cause problems that are not solved by re-writing Kerberos in another language. More important issues have to do with sharing credentials and getting trust info and other such things.
I use the bemis bidet adapter. It's $50 US on amzn and requires no power (splices into the feed). Only wish the knob would spring back to the off position. Was going to give it to my parent with dementia but because it does not auto-off, I ended up using it myself. Great item. There are many other similar ones but I can only speak to the bemis one.
Writing code is easy.
Knowing /what/ to write is hard.
I know how to write English.
But that doesn't mean I can write a book (that someone would want to read).
AI can write code.
But it still has to be told what to write.
However, there is a caveat. LLMs resist ambiguity about authority. So the "PCL" or whatever you want to call it, needs to be the ONE authoritative place for everything. If you have the same stuff in 3 different files, it won't work nearly as well.
Bonus Tip: I find long prompt input with example code fragments and thoughtful descriptions work best at getting an LLM to produce good output. But there will always be holes (resource leaks, vulnerabilities, concurrency flaws, etc). So then I update my original prompt input (keep it in a separate file PROMPT.txt as a scratch pad) to add context about those things maybe asking questions along the way to figure out how to fix the holes. Then I /rewind back to the prompt and re-enter the updated prompt. This feedback loop advances the conversation without expending tokens.