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100 tweets · 45 sources账号:全部mattpocockukbchernydair_aifelixriesebergtrq212simonw0xblacklightadocompletedexhorthydani_avila7ryancarsonGeminiAppgarrytankarpathymckaywrigleynummanaliomarsar00xPauliusAnthropicAIDanielMiesslerGoogleDeepMindRaillyHugoaidenybaiasynkimocgtwtsctatedevdemishassabisdillon_mulroydoodlesteinelithrarjarredsumnerjoshalbrechtjpschroederlennysanlexruslogancyangpetergyangrohanpaul_aisawyerhoodservasyy_aithdxrthorstenballycombinatoryiliushzarazhangrui
@0xblacklight·5d agoFor You
codexbros is this normal
buddy had is brain fried in the RL torment nexus
wouldn't even TRY reading outside the project directory (it could bc custom harness) https://t.co/sVOLqqLmET
Codex 用户们，这正常吗？ 这家伙的大脑被 RL 训练折磨坏了——连尝试都不肯去读项目目录以外的文件（其实它是可以的，因为用的是自定义 harness）。
@0xblacklight·6d agoFor You
the first search result for 'install claude code' on google is a (very convincing) clone of the claude code docs site that is distributing malware btw https://t.co/TeCZ4j4DAY
顺便说一句，Google 搜索「install claude code」的第一条结果是一个（极具迷惑性的）claude code 文档仿冒站点，正在分发恶意软件 [截图链接]
@0xblacklight·3月26日For You
Indeed
If you start with bad patterns you will never escape them due to LLMs auto-regressive nature
We saw this working on a brownfield codebase and it heavily influenced our new workflow
Nailing down good patterns for the agent to follow is an incredibly high-leverage point for humans
@dexhorthy
When @0xblacklight started working on the codelayer rewrite, he spent 2 weeks in vscode plumbing every pattern by hand so the clankers could be productive later - definitely paying off
确实如此。 如果你从糟糕的模式起步，由于 LLM 自回归的本质，你永远无法逃脱它们。 我们在一个存量 codebase 上工作时深有体会，这也深刻影响了我们新的工作流。 为 agent 奠定良好的模式，是人类能做的杠杆最高的事情之一。 【引用 @dexhorthy】：当 @0xblacklight 开始做 codelayer 的重写时，他花了两周时间在 vscode 里手工铺设好每一个模式，这样后续的 clanker 才能高效工作——显然很值得。
@0xblacklight·3月24日For You
building something where you spent a lot of time thinking about the right abstractions and nailed them is amazing
it's dramatically easier to ship if you nail this
the temptation is to worry about all your abstractions up front
the right thing to do though actually is to optimize for learning, ship things, and then refactor after patterns emerge from hitting the same problems 10 times
花了大量时间思考正确的抽象层次并最终钉住它，这种感觉太棒了 如果抽象做对了，交付速度会快得惊人 很多人的误区是一开始就担心所有抽象的问题 但正确的做法其实是：优先优化学习，先把东西发出去，等同一个问题撞墙 10 次之后，模式自然浮现，再重构
100 tweets · 45 sources