181–190 of 318 posts
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Does your friend have an iPhone? The default iOS keyboard has automatically converted double dashes into an emdash for at least seven years now.
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…
2026 is the year of the harness.
Seems like a very cool technique, but also very oversold. He's seeing a 5% improvement on a find and replace benchmark of his own devising and saying stuff like this in the blog post: > Here is why that is backwards. I just showed that a different edit format improves their own models by 5 to 14 points while cutting output tokens by ~20%. That’s not a threat. It’s free R&D. He makes it sounds like he got a 5-14% boos…
Not sure what they're calculating, but this seems to me like it could be many times more efficient than 20%.
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Once you begin to see the “model” as only part of the stack, you begin to realize that you can draw the line of the system to include the user as well. That’s when the future really starts hitting you.
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Precisely. This is why I use Zed and the Zed Agent. It's near-unparalleled for live, mind-meld pair programming with an agent, thanks to CRDTs, DeltaDB, etc. I can elaborate if anyone is interested.
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…
My Weird Hill is that we should be building things with GPT-4. I can say unironically that we haven't even tapped the full potential of GPT-4. The original one, from 2023. With no reasoning, no RL, no tool calling, no structured outputs, etc. (No MCP, ye gods!) Yes, it's possible to build coding agents with it! I say this because I did! Forcing yourself to make things work with older models forces you to keep things…
Hahaha yeah. This is very true. I find myself making ad hoc versions of this in static markdown files to get around it. Just another example of the kind of low hanging fruit harnesses are leaving on the table. A version of this that uses tree sitter grammars to map a codebase, and does it on every startup of an agent, would be awesome.
> My Weird Hill is that we should be building things with GPT-4.
I disagree, IMO using the best models we have is a good way to avoid wasting time, but that doesn't mean we shouldn't also be frugal and clever with our harnesses!
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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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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On recent versions Shift+Win+- also work, and Win+- produces en dash.
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tilth isn’t trying to replace grep for raw text search — for that, it wraps ripgrep internally so perf is comparable. It’s about reducing round-trips and giving the agent a verified edit workflow, not faster search. Instead of cat + grep + manual line counting, one tool call returns a structural outline of a large file, lets you drill into sections, and since this last update also returns hashline-anchored output tha…
well yah, that's what I mean how better is it versus cat + grep + manual line counting. Agents tend to perform worse with niche tools