Mr PandaRun

Mr Panda | Former 10x engineer, now AI-native. Learning in public, shipping practical projects, and sharing what actually works.

[Mr PandaRun @MrPandaRun]

From optimizing code speed to optimizing human-AI execution. Follow for practical workflows, not hype.

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[沐阳 @yyyole]

学到了！！把“第一性原理”写进Claude.md里，会发现惊喜！

可以加上这么一段话：

运用第一性原理 思考，拒绝经验主义和路径盲从，不要假设我完全清楚目标，保持审慎，从原始需求和问题出发，若目标模糊请停下和我讨论，若目标清晰但路径非最优，请直接建议更短、更低成本的办法。

所有回答必须分为两个部分：
• ​直接执行：按照我当前的要求和逻辑，直接给出任务结果。
• ​深度交互：基于底层逻辑对我的原始需求进行“审慎挑战”。包括但不限于：质疑我的动机是否偏离目标（XY问题）、分析当前路径的弊端、并给出更优雅的替代方案。

[李韭二 @li9292]

https://t.co/UQmLRQlW3v

[Mr PandaRun @MrPandaRun]

@yyyole 马上试试

[Mr PandaRun @MrPandaRun]

曾经我把 10 万行代码塞进 context 里问 AI 怎么改 README。
Token 爆了，钱包哭了，AI 也懵了。
Less is more，这是用钱买来的教训。
https://t.co/AkbK5fjMDQ

[Mr PandaRun @MrPandaRun]

@MetaT1ng 从来不会平权

[Mr PandaRun @MrPandaRun]

So this rename was not about AgentDock being weak.
It was about admitting that it was no longer precise enough.

[Mr PandaRun @MrPandaRun]

I renamed AgentDock to AgentClaw. This was not just a branding change. It was a correction in product direction. https://t.co/N39e2D44Cb

[Mr PandaRun @MrPandaRun]

Another big reason was the influence of openclaw.
Not just because claw is becoming a hotter word,
but because that project helped me see the product posture behind the word more clearly.

[Mr PandaRun @MrPandaRun]

That is where Dock started to feel too static.
It sounds like a port, a container, a thread hub.
Good language for management.
Weaker language for action.
Claw feels different.
It implies movement, force, and intent.

[Mr PandaRun @MrPandaRun]

But as the project evolved, I realized I no longer wanted to build just a place where agents dock.
I want something more active:
a system that grabs tasks, routes tasks, orchestrates work, and moves execution forward.

[Mr PandaRun @MrPandaRun]

Dock was never a bad name.
If the product is mainly about unifying accounts, configs, MCP servers, skills, and thread history across multiple agents, then AgentDock is actually very accurate.

[Citrini @citrini]

JUNE 2028.

The S&P is down 38% from its highs. Unemployment just printed 10.2%. Private credit is unraveling. Prime mortgages are cracking. AI didn’t disappoint. It exceeded every expectation.

What happened?​​​​​​​​​​​​​​​​

https://t.co/JzzwCrbJgS

[Elvis @elvissun]

https://t.co/DotZ3V6XhJ

[Andrej Karpathy @karpathy]

Very interested in what the coming era of highly bespoke software might look like.

Example from this morning - I've become a bit loosy goosy with my cardio recently so I decided to do a more srs, regimented experiment to try to lower my Resting Heart Rate from 50 -> 45, over experiment duration of 8 weeks. The primary way to do this is to aspire to a certain sum total minute goals in Zone 2 cardio and 1 HIIT/week.

1 hour later I vibe coded this super custom dashboard for this very specific experiment that shows me how I'm tracking. Claude had to reverse engineer the Woodway treadmill cloud API to pull raw data, process, filter, debug it and create a web UI frontend to track the experiment. It wasn't a fully smooth experience and I had to notice and ask to fix bugs e.g. it screwed up metric vs. imperial system units and it screwed up on the calendar matching up days to dates etc.

But I still feel like the overall direction is clear:
1) There will never be (and shouldn't be) a specific app on the app store for this kind of thing. I shouldn't have to look for, download and use some kind of a "Cardio experiment tracker", when this thing is ~300 lines of code that an LLM agent will give you in seconds. The idea of an "app store" of a long tail of discrete set of apps you choose from feels somehow wrong and outdated when LLM agents can improvise the app on the spot and just for you.
2) Second, the industry has to reconfigure into a set of services of sensors and actuators with agent native ergonomics. My Woodway treadmill is a sensor - it turns physical state into digital knowledge. It shouldn't maintain some human-readable frontend and my LLM agent shouldn't have to reverse engineer it, it should be an API/CLI easily usable by my agent. I'm a little bit disappointed (and my timelines are correspondingly slower) with how slowly this progression is happening in the industry overall. 99% of products/services still don't have an AI-native CLI yet. 99% of products/services maintain .html/.css docs like I won't immediately look for how to copy paste the whole thing to my agent to get something done. They give you a list of instructions on a webpage to open this or that url and click here or there to do a thing. In 2026. What am I a computer? You do it. Or have my agent do it.

So anyway today I am impressed that this random thing took 1 hour (it would have been ~10 hours 2 years ago). But what excites me more is thinking through how this really should have been 1 minute tops. What has to be in place so that it would be 1 minute? So that I could simply say "Hi can you help me track my cardio over the next 8 weeks", and after a very brief Q&A the app would be up. The AI would already have a lot personal context, it would gather the extra needed data, it would reference and search related skill libraries, and maintain all my little apps/automations.

TLDR the "app store" of a set of discrete apps that you choose from is an increasingly outdated concept all by itself. The future are services of AI-native sensors & actuators orchestrated via LLM glue into highly custom, ephemeral apps. It's just not here yet.

[Mr PandaRun @MrPandaRun]

AgentDock (Alpha): a local-first workspace for Codex / Claude Code / OpenCode. Unified threads, project grouping, terminal resume. Built for real dev workflows. Feedback welcome 👇https://t.co/KIc28jYnde

[Alex Prompter @alex_prompter]

R.I.P McKinsey.

You don’t need a $1,200/hr consultant anymore.

You can now run full competitive market analysis using Claude.

Here are the 10 prompts I use instead of hiring consultants:

[Mr PandaRun @MrPandaRun]

以后你雇的不只是人，还是一群“会收款的AI���。
身份+钱包=AI可验证、可结算，能像人一样接活赚钱。
https://t.co/5RwRBMLzSl

[0xGasless @0xGasless]

ERC-8004 Gives AI Identity. A2A Payments Give It Power🧵

[Mr PandaRun @MrPandaRun]

hello clawdbot