Wizard

👨‍💻 前阿里技术专家 | AI Builder
✨ 分享 AI 工具/架构、工作流和产品构建，少聊玄学，多讲实测

[Wizard @wizardly_ai]

https://t.co/RjPUbhav7g

[Wizard @wizardly_ai]

@NoraX2026 @elonmusk 纳尼？不过现在确实有点营销号成疯

[Wizard @wizardly_ai]

年轻真的是热泪盈眶啊🥹

[Wizard @wizardly_ai]

@liangbff1m 是的，走进 2026 年，大模型的竞争早就不再是单纯的“参数大力出奇迹”，而是演变成了“认知架构与工程克制”的较量。

[Wizard @wizardly_ai]

https://t.co/RjPUbhav7g

[Wizard @wizardly_ai]

GPT 自己生成的前端 UI 一直拉胯？😂
结果有人直接用 LazyCodex + Stitch 让 Agent 自主把专业级落地页卷出来了！

[Wizard @wizardly_ai]

Funny thing is: most marketers also don’t know what a clean schema, good tracking plan, or basic experimentation design is — and those have been around for years.

Knowing MCP / agents is a massive edge, but the real moat is the combo:
understanding the boring fundamentals of marketing + wiring them into AI-native workflows so you’re not just automating chaos at scale.

[Wizard @wizardly_ai]

Love this workflow — “cheap model for breadth, strong model for depth” feels like the right pattern for a lot of product teams now.

6 parallel variations also solves a very real trap: spending hours fighting one prompt/layout instead of exploring the design space. Recast looks like it turns GLM 5.2 into a proper idea generator and a shippable code generator, not just a pretty mockup factory.

[Wizard @wizardly_ai]

I like how this thread is basically “don’t get greedy, don’t get cute, don’t get shady” distilled into a checklist.

Most people only realize these are real risks after they’ve already triggered a review, a warning, or a ban. Hard paywalls + aggressive pricing + sketchy growth tactics might look great in a spreadsheet, but they destroy trust, spike refunds, and put a target on your back with App Review.

Playing the long game with fair pricing, honest UX, and clean growth feels slower month to month, but it’s probably the only way an indie actually survives long enough to hit meaningful ARR.

[Wizard @wizardly_ai]

You forgot the chaos option: “both, badly” 😄

Jokes aside, starting on the web has been a game changer for me — faster iteration, easier debugging, and way less time fighting Xcode/provisioning. Once the core UX and retention feel right in a browser, then it finally makes sense to pour effort into a polished iOS build.

[Wizard @wizardly_ai]

@jxnlco 那个朋友就是你吗？

[Wizard @wizardly_ai]

https://t.co/WB5rIYnEFw

[Wizard @wizardly_ai]

🚀发现一个神器：任意 GitHub Repo 一键转 Prompt，就能重建整个项目

[Wizard @wizardly_ai]

这个好像也可以
https://t.co/HQy45Tc4Zx

[Wizard @wizardly_ai]

分享1个iOS免费小火箭(Shadowrocket)共享ID站:
https://t.co/qmzQVIJLsP

[Wizard @wizardly_ai]

@Hp2ai 并没有啊

[Wizard @wizardly_ai]

@AYi_AInotes 来了就对了，一两天粉就翻翻

[Wizard @wizardly_ai]

@weichen_ink 记得先办理领取失业金

[Wizard @wizardly_ai]

@rionaifantasy 感谢🙏

[Wizard @wizardly_ai]

是的，这确实是当前主动 Agent 落地最大的卡点之一——不是模型不够聪明，而是团队流程的「隐性共识」太多了。
Claude Tag 在视频里也特别强调了两个缓解机制：
• Channel-level 的持久记忆 + 指令：可以明确告诉它「PR 必须符合我们这个 channel 的模板，缺少 X/Y 字段就别乱 ping 所有人，先私信 owner」
• 持续纠正 + 轻量 classifier：它会根据你的反馈逐步收敛（“以后 reviewer 永远 tag 我”这类指令），不像早期 bot 那么死板。

[Wizard @wizardly_ai]

大家觉得这个方向会成为主流吗？还是更看好其他形态的团队 Agent？

[Wizard @wizardly_ai]

🚀 Claude Tag ，这可能是目前最接近「团队级 AI 同事」的形态。
从 Claude Code 的「单人单机」模式，进化到多人主动式 + 带记忆 + 有身份的团队 Agent。
它不再等你呼叫，而是主动住在 Slack 频道里：
• 监听 PR 评论、自动修 CI/CD、告诉你什么时候能 merge
• 每天自动总结「昨天 main 上了什么」
• 甚至帮你找会议空档…
官方 6 分半深度视频把「新原语（Proactive + Memory + Identity + Multiplayer）」讲得非常清楚，信息密度拉满。
对所有在做 multi-agent 系统、agent memory、团队协作工具 的人来说，这期内容值得反复看。