MadBoar

[MadBoar @livetoevil]

@Lucasmiiu @Clapton_Free 始终无法理解你这种人的脑回路，就这段话而言，前半段且不论我同不同意这个观点，但至少感觉好像是带了一些思考和认知的，然后到最后忽然来这么一句，我甚至不知道该说你蠢的可笑还是单纯的可爱，又或者是坏的可怕

[MadBoar @livetoevil]

@lidangzzz 我侄子刚断奶，用ai学了半年量化，现在赚了10个亿

[MadBoar @livetoevil]

@WuMao426Killer @Amelia181672271 因为台湾还有你这种人在，因为种种原因，大陆不合适一炮轰死你这种人，至少尽可能保持一个合适中间状态

[Peter Pang @intuitiveml]

https://t.co/oWr2pTk4Hu

[WquGuru @wquguru]

这��本书把Claude Code和Codex的Harness工程吃透了，对于Claude Code和Codex源码解析和对比都入木三分，文科生也能读的津津有味：

《Harness Engineering——Claude Code 设计指南》：不是源码注释汇编，也不是产品功能介绍。它关注的是 Claude Code 如何把不稳定模 型收束进可持续运行的工程秩序，让控制面、主循环、工具权限、上下文治理、恢复路 ��、多代理验证与团队制度长成一套完整骨架

《Claude Code 和 Codex 的 Harness 设计哲学——殊途同归，还是各表一枝》：比较两套 AI coding harness，最容易犯的错误，是拿一张功能对照表当作思想史。左边写“有技能”，右边也写“有技能”；左边写“有沙箱”，右边也写“有沙箱”；左边写“能开子代理”，右边也写“能开子代理”。这样写的好处是省事，坏处是几乎什么也没说。因为工具中的名词相同，不代表系统的骨架相同。就像两个城市都修了桥，不能说明它们是按同一条河设计的。

Github仓库：https://t.co/qVWdzLJP72
在线阅读：https://t.co/PoyAGfZHDA

[Bytebytego @bytebytego]

12 Claude Code Features Every Engineer Should Know

[BuBBliK @k1rallik]

Solo dev reverse-engineered Google's billion-dollar algorithm in 7 days

Google published the paper that crashed memory stocks worldwide. Then shipped zero code.

Tom Turney read the math, opened his terminal, and built the whole thing with Claude - then made it faster than Google promised.

Day 1-3: Core algorithms, 141 tests, Python prototype
Day 3-5: C port into llama.cpp, Metal GPU kernels
Day 5-7: Speed optimization from 739 to 2747 tok/s

That's a 3.7x speedup through pure engineering:
> fp32 → fp16 WHT
> half4 vectorized butterfly ops
> graph-side rotation
> block-32 storage layout

Then he added his own research on top:

> Sparse V: skip 90% of value decompressions at long context
> Asymmetric K/V: keep keys precise, compress values harder
> Temporal decay: old tokens get lower precision automatically

Result: 35B model running on a MacBook with 4.6x compressed cache.
613 GitHub stars in a week. Google still hasn't released their own code.

[美酱AI @meijiangAI]

🚨重磅：一位Anthropic前研究员泄露了Claude内部提示词手册。

不是猜测，直接来自建造者。

你正在浪费Claude 35%的推理能力，因为一个常见错误。

以下是Anthropic外无人知晓的10个提示词：

[Dan McAteer @daniel_mac8]

Harness engineering is as important as model capability scaling.

AI Agents are 50% a harness story.

"Natural-Language Agent Harnesses" proposes moving harness logic out of code and into the native language of LLMs:

Natural Language.

Turns the agent harness into a portable artifact that you can experiment with, improve and execute in a shared runtime.

Agent harnesses will mature into a first class citizen of the AI Agent ecosystem.

We will have people who are Agent Harness engineers and experts.

[MadBoar @livetoevil]

@chen66800 瞅瞅怎么个事

[MadBoar @livetoevil]

@torontobigface 过于离谱的谣言是没法传播开的

[MadBoar @livetoevil]

@torontobigface 真就连一点现实都不管直接胡说八道是吧

[MadBoar @livetoevil]

@wshngknshji1 你这蠢得我都无奈的笑了

[MadBoar @livetoevil]

@lydia488144315 @someonelikeu66 稍微学点经济学吧

[MadBoar @livetoevil]

@lydia488144315 你是怎么产生这种幼稚的想法的

[MadBoar @livetoevil]

@lydia488144315 这就是皈依者狂热是吧

[MadBoar @livetoevil]

@nvpp66 11111

[MadBoar @livetoevil]

@lidangzzz 就一个小小的疑惑，模型是靠什么训练出来的

[MadBoar @livetoevil]

@bobokeai1 @lidangzzz @shipinbot