271–280 of 318 posts
> Treating harnesses as solved, or even inconsequential, is very short-sighted Is it possible that burning extra tokens is the point, since they get paid more?
That doesn't make sense with subscriptions.
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how do you make them?
On macOS, Option+Shift+- and Option+- insert an em dash (—) and en dash (–), respectively. On Linux, you can hit the Compose Key and type --- (three hyphens) to get an em dash, or --. (hyphen hyphen period) for an en dash. Windows has some dumb incantation that you'll never remember.
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> “replace line 2:f1, replace range 1:a3 through 3:0e, insert after 3:0e.” Not sure what they're calculating, but this seems to me like it could be many times more efficient than 20%.
So i just build this - with a few changes to the approach and usable as a simple pi-extention without having to use what-the-pi. It seems to work pretty well so far. https://github.com/offline-ant/pi-hh-read
Great post. A few choice quotes: > Often the model isn’t flaky at understanding the task. It’s flaky at expressing itself. You’re blaming the pilot for the landing gear. > The model is the moat. The harness is the bridge. Burning bridges just means fewer people bother to cross. Treating harnesses as solved, or even inconsequential, is very short-sighted. > The gap between “cool demo” and “reliable tool” isn’t model m…
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So i just build this - with a few changes to the approach and usable as a simple pi-extention without having to use what-the-pi. It seems to work pretty well so far. https://github.com/offline-ant/pi-hh-read
Why do we need a hash for every line. Why cant we mark every fifth line (or get smarter and calculate entropy of lines and jump longer for empty boilerplate)? I feel adding a random 3 char header to every line while making the edit tool smarter will make the overall understandability of the content dumber.
I suspect doing it only ever 5th line would make it less clear for the llm.
I'm just experimenting, I wouldn't suggest you use this by default unless you're looking to experiment.
I really enjoyed this article. I think the author is precisely right and I've been saying this for a long time. There's a ton of extremely interesting low hanging fruit that can vastly improve the effectiveness of even currently existing models hiding in how we design our agent harnesses; enough to — at least until we hit diminishing returns — make as much or more of a difference than training new models! I think one…
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Em dashes are used often by LLMs, because humans use them often. On mac keyboards its easily typed. I know this is oversimplifying the situation, but I don't see the usefulness of the constant witch-hunting for allegedly LLM-generated text. For text we are long beyond the point, where we can differenciate between human generated and machine generated. We're even at the point, where it gets somewhat hard to identify m…
I might not be able to spot ALL AI generated text, but I can definitely spot some. It's still kind of quirky.