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영상편집자님들 적게 일하고 많이 버세요

[도비 @editordobbyy]

@Alisvolatprop12 SSD값 비싸던데 요즘.. 농담입니다

[yibie @yibie]

推荐这篇文章，Superpowers 的作者让 Fable 5 跑了一个完整的 autoresearch loop——25 个实验，$165，把构建速度提高了 50%、token 开销降低了 60%。但这篇最值钱的不是结果数字，是他完整记录了实验过程：每次失败、每个被证明"彻底死亡"的想法、三个被中途纠正的测量 bug。这是目前最完整的"用 Fable 做自治研发"实操报告。

Superpowers 6：用 Fable 5 跑 25 个自治实验，砍掉 60% 成本

一周前我们准备发的是 Superpowers 5.2——已经推迟了几次，加了"再多一个改进"。然后 Anthropic 发了（又收了）Fable。在那几天里我把它用到了极致。

Superpowers 用户最常抱怨的是 token 贵、构建慢。慢不应该是个问题——它发生在自治子 agent 驱动的构建编排中。但它确实是个问题。慢不好玩。贵也不好玩。

Fable 出来的时候，我决定看看它能把 Subagent Driven Development 优化到什么程度。我原本期望大概 15% 的 token 消耗降低。我得到了那个——还有更多。

第一次攻击：coordinator 到 reviewer 的交接

Fable 分析了几千个 Subagent Driven Development session，发现代码和 spec 合规审查子 agent 在做审查时跑了大量的 git 命令。把"怎么找要审查的 commit"的书面指令换成一段 shell 脚本——预生成一个包含格式化 diff 和元数据的审查包——token 消耗和墙上时间减少了约 10%。

那天晚上睡觉前我告诉 Fable："看看能不能在我睡着的时候再砍 15% 时间和 token。"我在内部 Slack 上留了条消息：我们应该看看把代码 reviewer 和 spec 合规 reviewer 合并会发生什么。

我不知道我在期待什么。反正不是醒来发现 Fable 独立地得出了同样的结论，测试了它，发现在我们的 eval 套件上恰好省了那额外的 15%。

第二夜：自治研究循环

/goal 一旦完成，跑一个 autoresearch loop 来提升 superpowers 构建循环的成本效率。
用 opus 做协调器。建假设日志。跑实验。至少 25 个实验。

Fable 建了一套完整的 autoresearch harness 并且跑了一整夜。25 个实验跑完了，$165。

结果：可发货的候选方案（E27）——opus 控制器 + elicited plan + 条件化 haiku implementer + terse reviewer contract + narration recipe + 最终审查层固定。

有数字的胜利： terse reviewer contract 减少 reviewer 产出 41%，判定不变。narration recipe 减少 54%，零方差。条件化 implementer 分层约省 $0.5-1/次，而且 E22 证明它正确地拒绝了 haiku 处理 prose plan。

被证明彻底死亡的东西： 给控制器思考加帽适得其反——轮数从 92 升到 138，输出翻倍。plan 词数预算削减测试内容 62%，即使代码被豁免。Sonnet 生成 plan 保真度不变但毁掉任务结构。plan 中的实现内容体是边际的——测试 + 接口 + 结构承担了全部负载。

一个值得记住的风险发现： 只给 diff 包的审查员对 spec 做出自信的判定，却静默地把"spec"重新定义为全局约束——5 个里 0 个标记了缺失的简报。跟 haiku 审查员辩护同一个失败家族。

六个线索关闭为"已经最优"（report reads 缓存健康、审查员底线、haiku fixer、todo 簿记、dispatch 重推导）——记下来让没人再重复买这些教训。

我自己三个测量 bug 被中途抓修： 一个把模板回显跟自审查 catch 计在一起的 grep、一个从未内联 diff 的 harness、一个匹配漏了换行符的评分正则。一份被撤回的判定重新测量后干净了——-74% 变成了诚实的 -41%。

结果

跨 36 小时工作和约 $650 的未补贴 token 开销：Anthropic eval 基准上，构建墙上时间降 50%，token 开销降 60%。最大的改进来自合并 spec 合规和代码质量审查 agent、预烤给审查员的审查包让他们几乎不需要跑 git、以及改变我们给 orchestrator 的关于什么任务该用什么 agent 的指导。

然后在 Codex 上跑 eval——结果显示零改进。挖了几分钟：Codex 上的 eval 隔离不够好，一直在基准 Superpowers 5.1.0。修好后，所有结果都在。

一句话

Superpowers 6 证明：自治 Agent 研发不是一个 demo——是正在发生的事。 25 个实验，165 美元，一个通宵。每个实验有预先登记的假设。每个被否定的想法被记录下来。每次测量错误被中途纠正。这套 eval 基础设施让他们能够跨多种 harness 量化变化。这才是自治研发的正确形态。

原文：Jesse Vincent (obra), "Superpowers 6", 2026-06-15
https://t.co/mANs2ROpbs

#Fable5 #Agent #自治研发 #Superpowers

[Johnn @john_my07]

Seedance 2.0 on OpenArt AI

Prompt:
Main subject: young Korean woman, early 20s, natural everyday appearance, faded charcoal-grey sleeveless crop top, loose high-waisted light-wash jeans, black canvas sneakers, black cord necklace, black wavy hair in a messy side ponytail with wispy bangs. Realistic skin texture, minimal makeup, warm and approachable personality. Maintain consistent identity, clothing, hairstyle, and appearance throughout the entire video.
Location: Authentic Korean residential neighborhood during a calm late morning. Narrow concrete alleys, low-rise homes, small terraces, potted plants, laundry lines, bicycles, utility poles, overhead wires, mature trees casting moving shadows, quiet residential atmosphere. No stores, advertisements, cafés, crowds, or commercial activity.
Visual Style: Ultra-realistic documentary realism. Genuine candid behavior. Natural body language. Unscripted slice-of-life feeling. Strong environmental authenticity. Rich real-world details and believable human motion.
Camera Style: Early-2000s consumer DV camcorder aesthetic. Friend casually recording everyday moments. Heavy handheld shake, imperfect framing, frequent autofocus hunting, lens breathing, exposure pumping when moving between sun and shade, occasional motion blur, subtle rolling shutter, mild digital compression artifacts, faded colors, soft contrast, slight sensor noise. No stabilization. No cinematic camera moves. No modern color grading.
00:00–00:02
Outside a small house entrance. She sits on a low concrete wall adjusting her ponytail with both hands raised. A light breeze moves loose strands of hair. She smiles naturally while the camera struggles to hold focus.
00:02–00:04
The camera follows her into a narrow alley lined with potted plants and concrete walls. She notices a stray cat approaching and crouches down. Framing drifts off-center as the operator tries to keep up.
00:04–00:06
She gently pets and feeds the cat. Autofocus repeatedly shifts between her face and the animal. Morning sunlight flickers through leaves overhead.
00:06–00:08
Small front yard beside her house. She hangs laundry on a clothesline while fabrics sway in the breeze. Exposure changes as clouds briefly pass overhead.
00:08–00:10
On a quiet terrace with a ceramic coffee cup. She sits comfortably watching the neighborhood, occasionally brushing hair behind her ear. Loose handheld side angle with natural camera drift.
00:10–00:12
Close side profile. Someone off-camera greets her. She turns, raises her hand, smiles warmly, and casually says, “Annyeong.” The camera catches the moment slightly late.
00:12–00:15
Walking slowly down a tree-lined residential lane holding her coffee cup. She notices the camera, gives a small genuine smile, then looks away and continues walking. Recording cuts abruptly to black mid-motion as if the camcorder was switched off.

Audio: Natural ambient sound only — morning birds, distant motorcycles, light wind, leaves rustling, faint neighborhood chatter, cat sounds, footsteps on concrete, fabric moving on clotheslines, subtle residential ambience. No music. No sound design. No narration.

Goal: Authentic Korean neighborhood life captured like a forgotten home video from the early 2000s — candid, imperfect, realistic, warm, and deeply believable.

[도비 @editordobbyy]

@spwfeijen want

[Stijn Feijen @spwfeijen]

We’ve officially hit the point where AI UGC is cheaper AND better than real UGC.

This video is 100% AI and cost under $1. (And no, it’s not Sora, Veo, or Kling).

My system is built for mass-scale organic across thousands of accounts. Here is why it wins:

- Hyper-realistic visuals: Natural physics and movement look flawless.

- Insane cost efficiency: Costs pennies compared to traditional UGC programs.

-Consistent audio: High-quality, rock-solid voiceover throughout.

- Infinite scaling: Videos can run to any length cost-effectively.

This changes everything.

Want the WORKFLOW? Check the comments!

[도비 @editordobbyy]

@spwfeijen claude

[Stijn Feijen @spwfeijen]

https://t.co/GApKjNi7gz

[도비 @editordobbyy]

@rom1trs vox

[도비 @editordobbyy]

@Future__Walker 20배 올랐네

[𝗕𝗿𝗶𝗮𝗻 𝗥𝗲𝘆 @BrianMRey]

if you’re building an app

make sure to apply to Apple’s Small Business Program

doesn’t matter if you’ve launched yet or not

it’s completely free

and cuts Apple’s fee from 30% → 15%

[Khairallah AL-Awady @eng_khairallah1]

this is f*cking gold

Andrej Karpathy joined Anthropic five weeks ago.

A friend on his team just showed me the exact LOOPS.md file he actually uses.

I dropped it into my setup. The very first response was different.

Not slightly different. Completely different.

Claude stopped giving generic answers and started working exactly the way I think.

You don't talk to the model anymore. You build the system that talks to the model for you.

Bookmark it before it gets lost in your feed.

Read it now, then check the article below.

[도비 @editordobbyy]

@Alisvolatprop12 줴쥐이~

[도비 @editordobbyy]

@Alisvolatprop12 공급 때문에 반도체 망한다네요 ㅎㅎ 아유 제발 토큰 좀 조금이라도 더 주세요

[도비 @editordobbyy]

@Alisvolatprop12 ㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋㅋ이야 그 값은 한다 이건가 ㅋㅋ gpt 5.6는 300정도 될 수도 있겠네요(희망사항)

[도비 @editordobbyy]

@canadada6 Yes I sent you a dm!

[도비 @editordobbyy]

@_Valentino ???: 자네가 그 엘엘엠이란 거 뭐 만들어보는건 어떤가?

[도비 @editordobbyy]

@Alisvolatprop12 제발 치킨 게임해서 가격 좀 ㅠㅠㅠ

[도비 @editordobbyy]

@Alisvolatprop12 우리 미리 투자해서 너희에게 줄 돈 없어 ^^

[도비 @editordobbyy]

@fptlxls3 @Alisvolatprop12 미국 중국 유럽연합 한국 정도 아닐까요?

[도비 @editordobbyy]

@Alisvolatprop12 그록은 사실 twitter api용으로 쓰는 거 아니면... 절레절레