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But like, what is it? Odd that this reached #1 on HN. The README is pretty bare outside of installation instructions and a link to "Cordis", which is "A Meta-Framework of Spatiotemporal Composability." and "under active development. The API is not yet stable and may change without notice.".
I have read the underlying paper, and found it may be useful, but not that useful. For those who want to know what it achieves: it adds hot-reload and dynamic enable/dispose capabilities to a plugin system, like the one in Pi agents, though they push the boundaries further, to the UI components and so on. For those who want to know what it does: if you have some PLT knowledge, ask your agent to explain the algebra to…
Uh, it’s big idea is a destructor? This is considered significant in 2026 and the era of vibe coding?
Is there a comparison of harness somewhere? Like, the same prompt to the same model, but with different harnesses, and comparing the quality of the results. I am trying to run as much as possible only on free software, so I always only used Zed plugged with anthropic models, but I am wondering what is the quality of Zed harness compared to the one of claude code or pi or others... I would love some feedback.
The landing page provides more context than GitHub: https://deepseek.com/harness/en/ The documentation, built from repo, is available here: https://deepseek-harness.github.io/deepseek-harness/en/guide... (I find the development and reference sections easier to read and navigate)
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VSCode at least is a GUI
Which it’s kind of strange VSCode ghcp lacks basic attributes like context % used compared to some TUIs where it’s default.
Tangential but, are there benchmarks out there on how languages affect latent spaces and performance of these models? This other day I was looking at that “caveman” skill, and was shocked to see it evolved to become a company, and, in one of its modes, the highest form of compression seems to be “Wenyan” which is Classical Chinese. Should I get started on learning Chinese?
Also, "less tokens" is not always straight forward. I doubt it's a coincidence that the cavemen skill (or now proxy, I guess) has lots of numbers, but not a single benchmark on model performance or actual per-task token savings
For example one paper I remember found that without CoT, just stating your prompt twice increases model performance. With CoT, the same function is served by the CoT restating the important parts of your question. Something about which tokens can affect which other tokens in attention implementations
if it's not better than omp im not trying it
But like, what is it? Odd that this reached #1 on HN. The README is pretty bare outside of installation instructions and a link to "Cordis", which is "A Meta-Framework of Spatiotemporal Composability." and "under active development. The API is not yet stable and may change without notice.".
Good to know I was not the only one confused. Reads like word salad!
Every product relying on "community plugins" for their features implies it works fine the 6 first months, then it's a nightmare of incompatible, deprecated, incompatible plugins, with no consistency and no governance.
I understand how attractive it can be to companies to think, hey, let's make a very small product and rely on other people to make features, and I hope it works, but I'm personally staying away from that.
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An additional benefit of interpreted, I think, is to make plugins easier to distribute and incorporate. With a compiled language you’d need message passing or something.
dynamic linking was invented pretty long time ago