这个模型有点东西,也是个里程碑,我在 zcode 里体验丝滑,有第一次用 Opus5.5 的畅快感。几个长程任务都圆满完成,对 flash 模型刮目相看
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
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Lefts retweeted
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
1/4
pstack 还是很厉害的,但是这个只适合 SOTA 模型,GLM5.3 这种完全没有这个效果。Astra 和 Opus5.5 效果都很好
it's easy to fall into the trap of micromanaging your agents instead of correcting the environment that shapes its behavior.
pstack 0.15.9 now ships a new /correct skill: if you keep correcting agents for the same mistakes, it finds the pattern and fixes it with architecture, types, and checks.
i like to imagine that commits rapidly flowing into the codebase are like a bonsai tree rapidly growing in whatever direction it pleases. what you want to do is not to give in to the chaos, but tame it intentionally with the right constraints
0.15.9 also has improvements to:
• /architect: now includes instructions on designing agent friendly architecture
• a new /benchmark-checklist skill based on @brendangregg's benchmarking checklist
here's a prompt you can give to grok bot to start architecting a better codebase with pstack:
/poteto-mode create a new Project agent to refactor and rearchitect my repo so that our architecture is more agent friendly. it should use both the /correct and /architect skill to look through past commits and find the most common pitfalls that agents fall into, whether its with code quality, performance, or bugs. if relevant you can also use the /recall skill to find past conversations for context. it should make a high level plan for me to review. it should also answer its own open questions by prototyping rather than defer to me. come back to me with a plan backed by real data. once i approve the plan, use either the stack or full autopilot playbook (ask me which i want) to execute
代码是否需要人工 review,取决于你在做什么,允不允许犯错。从当下的实践来看,互联网 APP 级别的可以完全不用,可以快速迭代,你还在 review 代码的时候,对手已经根据用户反馈已经发了两个版本了,你做不到快速迭代需要查看下自己的 CI 系统和测试覆盖率
如果你是在做一个比较严肃的系统,建议还是要人工 review,现在 AI 已经能辅助 review 了,能缩减 review 时间,以我的经验需要 review 是因为:1. AI 可能会误解你的意思 2. AI 在复杂多线程并发时候会犯错
tmux + git worktree is all you need.
tmux 本身 C/S 结构,自带 IPC,可以很方便通过 send key ,set-buffer 在各个窗口传递信息
worktree 用来做工作区的隔离,避免 git stash ,git clone, 所有工作区都是独立目录,但是共享.git 新开一个工作区 秒级完成
一个复杂任务一个 session,一个 session 可以多个窗口,每个窗口一个 agent,每个 Agent 可以根据工作内容选择是否用独立 worktree
多个任务并行,天然通过 session 隔离,tmux session 可以很方便的 attach,detach






