crustycoder

6 ms·

1.
by crustycoder 2mo ago
Heartening to see so many "This is an apple, that is an orange" comments. Spot on folks!
2.
by crustycoder 4mo ago
Yes, exactly. The issue detection step isn't particularly well-suited to a LLM, as it will tell you itself. The issues can be established deterministically by examining the Cloud resource data with a set of relatively simple rules, and
3.
by crustycoder 4mo ago
It's not that sophisticated ;-) There's command editing using readline, result pagination using less and I output links to the reports and the Cloud console using ANSI HTTP link escapes. Primitive but sufficient.
4.
by crustycoder 4mo ago
I think in many real-life cases it's a mix - for example impure code that deals with the outside world to set up the data needed for the pure "core" of the app to run over.
5.
by crustycoder 4mo ago
You could always read the docs? https://www.swi-prolog.org/pldoc/man?section=clpfd-integer-a... https://www.swi-prolog.org/pldoc/doc_for?object=!/0
6.
by crustycoder 4mo ago
I've just rolled out an internal SWI Prolog app that is similar to one linked to elsewhere in the thread [1]. We have a large Cloud estate with 10s of thousands of resources in it. Detecting unused or misconfigured resources manually i
7.
by crustycoder 4mo ago
I get what he's saying but I think it's overstated. I'd categorise his list as "Things to be careful with" not "Coding horrors". For example, "The primary means to make your programs defective in this
8.
by crustycoder 4mo ago
Mostly overblown.
9.
by crustycoder 5mo ago
Name me a new bit of tech that hasn't been hyped beyond reasonable bounds. And yes, this is one of the worst examples. But saying it doesn't have its uses isn't reasonable either.
10.
by crustycoder 5mo ago
Go figure it out, it will be a useful challenge for you.
11.
by crustycoder 5mo ago
I'd tell you to read it again, but you seem to be struggling.
12.
by crustycoder 5mo ago
I'm not going to repeat myself, I've already explained the context to you - funny how you seem to have ignored that. If you want to find out, do the experiment yourself.
13.
by crustycoder 5mo ago
You clearly missed the "The truth is somewhere in between" bit.
14.
by crustycoder 5mo ago
Picking phrases from what I said and deliberately misquoting them out of context does not make you right.
15.
by crustycoder 5mo ago
"exactly this inspection" != "what does it exactly do"
16.
by crustycoder 5mo ago
Nicely put. I haven't seen anyone say that the introspection abilities of LLMs are up to much, but claiming that it's completely impossible to get a glimpse behind the curtain is untrue.
17.
by crustycoder 5mo ago
Yes of course there's a risk it may still be incorrect but querying the LLM with the limited facilities it provides for introspection is more likely to have at least some connection with facts than the alternative that some people use,
18.
by crustycoder 5mo ago
I don't owe you anything. If you want to go find out, go do it yourself. You could even ask a LLM to help you if you,like...
19.
by crustycoder 5mo ago
People have applied "think" to the actions of software for decades. Of course it LLM's don't "think" in the human sense, but "What the output of the model indicates in an approximate way about its current
20.
by crustycoder 5mo ago
"Not in the slightest" is an overreach, the paper the second level down from that link doesn't really support the conclusion in the blog post - the paper is much more nuanced. Are they going to fib to you sometimes? Yes of co
21.
by crustycoder 5mo ago
> It would be interesting to see one of these evals and how it generated the score, to work out whether it is in fact arbitrary or based on some scale of points. So go repeat the exercise yourself. I've already said this was a short
22.
by crustycoder 5mo ago
Is that based on your "deep understanding" of how LLMs work or have you actually tried it? If you watch the execution trace of a Skill in action, you can see that it's doing exactly this inspection when the skill runs - how c
23.
by crustycoder 5mo ago
They aren't arbitrary, as I said earlier I got the LLM to de a detailed analysis first, then summarise. If I was doing this "properly" for something I was doing myself I'd go through the LLM summary point by point and ch
24.
by crustycoder 5mo ago
No of course you wouldn't because LLMs are nondeterministic. But the scores would likely be in the same ballpark. The scores I posted are the result of a much more detailed analysis done by the LLM, which was far too long to post. I ey
25.
by crustycoder 5mo ago
I wouldn't go that far but the only way I've found so far of getting a reasonable insight into why a LLM has chosen to do something is to ask it.
26.
by crustycoder 5mo ago
Because he's asking the LLM to interpret those instructions to drive his process. If the skills are poorly defined or incomplete then the process will be as well, and the LLM may misinterpret, choose to ignore, or add its own parts. Sk
27.
by crustycoder 5mo ago
LLMs work OK for "Mostly iterative and mostly one-off" tasks like codegen, where you can effectively "review the result into existence", and that's where most of the buzz is at the moment. Where they don't work
28.
by crustycoder 5mo ago
He's also missed a major step, which is to feed your skill into the LLM and ask it to critique it - after all, it's the LLM that's going to act on it, so asking it to assess first is kinda important. I've done that for h
29.
by crustycoder 6mo ago
So it's the relative and not the absolute diff that matters - thanks.
30.
by crustycoder 6mo ago
A timely link - I've just spent the last week failing to get a ChatGPT Skill to produce a reproducible management reporting workflow. I've figured out why and this article pretty much confirms my conclusions about the strengths &a

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