This makes sense, although it's not well described here.
Formal methods, as in proof of correctness, have been around for decades (I was doing that stuff in the 1980s) but pushing the proofs through was too laborious. The seL4 verification effort reportedly used over a decade of people time.
The idea is that if you have a formal specification of what you want to happen, you can get a LLM to do the struggling with the proof system to get it right. It's a good task for an LLM, because there's feedback from the prover.
I'd like to see more non-trivial examples of this. People keep republishing verifications of greatest common divisor or stack algorithms, which was done decades ago.
This is a very interesting introduction to a blog post, but... I'm somehow missing the actual blog post. How does this stuff work in practice? What are some concrete examples? How does one get from JavaScript tokenizing things in a commit hook to validating that the LLM didn't disable tests it didn't agree with, or any other helpful property?
I am the author. I am trying to limit one post to one page. Most people here are reading reasoning all day, I am afraid. Might get tired.
I also aspire to make one post a day. To be continued.
Makes sense, I have had the biggest wins with AI by attacking nondeterminism whenever possible.
BTW, you should probably fix the Beagle link on your homepage: https://replicated.live/beagle/
Basically what I’ve been saying since OldJob forced LLMs down our throats and pegging performance to usage metrics: why the fuck are we handing deterministic processes to probabilistic systems when it should be the other way around (using probabilistic systems to design deterministic ones)?
LLMS should be abstracted out of a process as soon as practicable, replaced with deterministic processes or procedures. Otherwise you’ve built the world’s most fragile process at the mercy of token cost, vendor hostility, geopolitics, and model deprecation.
Thats the best description I have heard of the problem so far. I ran into this recently where I automated a ton of stuff and got essentially threatened by leadership for not using AI. My system produces the same output 100% of the time, is free, and scales plus is reliable. Doing what they wanted with an LLM was fragile, didn't always produce the same output and was subject to costs. I don't think they could wrap their brains around it.
I love the way you put this. Are there any sites or forums or places where people discuss/hash this out?
I've genuinely never considered it from this angle before.
Humans aren't deterministic. Determinism is a red herring. There are lots of other problems with agentic programming, but this is not at the top of the list.