Evan Payne

AI Developer | 21 |

[Evan Payne @evan_payne30133]

Codex Team is an adaptive collaboration plugin for Codex: dynamic native multi-agent sessions, preserved context, bounded authority, human oversight, and verified delivery.Explore the project: https://t.co/eeyFNeRPLw #MultiAgent

[Evan Payne @evan_payne30133]

@ldxhjxy 来浇来浇

[Evan Payne @evan_payne30133]

只要开个蓝 V ✌️✌️✌️
随意评论一下 🤯🤯
多少都会有人来关注你。

每天活跃一下，正常互动下
一天涨个 100～200 粉，真没想象中那么难。

你信不信？ #蓝v互关 #真诚交友 #创作者收益

[Evan Payne @evan_payne30133]

@Zhibin992 来了

[Evan Payne @evan_payne30133]

@Xiaoyuezo 来了

[Evan Payne @evan_payne30133]

@JustKeepGoing01 关注了，浇个朋友

[Evan Payne @evan_payne30133]

@JMkernt 来了

[Evan Payne @evan_payne30133]

@Linzuijia 来了

[Evan Payne @evan_payne30133]

@Aleksanderal2 来了

[Evan Payne @evan_payne30133]

@SwordXyj 神人

[Evan Payne @evan_payne30133]

@buyoutu 来来来

[Evan Payne @evan_payne30133]

@LsIands7r 来

[Evan Payne @evan_payne30133]

@WangDaWang123 浇朋友

[Evan Payne @evan_payne30133]

What's wrong?

[Tibo @thsottiaux]

Your ChatGPT subscription is now also a Devin subscription

[Evan Payne @evan_payne30133]

@vwycm 来交朋友吧

[Evan Payne @evan_payne30133]

@gFcbZDrLwvrhgey That means it's not a network environment issue.

[Evan Payne @evan_payne30133]

dot创建入口是不是出问题了，为什么我删掉旧的dot后没法创建新的，老显示"未能加载您的 dot"

[Evan Payne @evan_payne30133]

有没有大佬用AI做过比较惊艳的前端？

[Evan Payne @evan_payne30133]

@thsottiaux Maybe you should check out your email in person instead of let your dot to delete them all.

[Evan Payne @evan_payne30133]

用中文借鉴 ASD-STE100：
短句、明确主语、术语先解释。用逻辑短段落和具体例子讲清原因与机制，补全中间因果，保留关键条件，不用比喻代替原理。

[Andrej Karpathy @karpathy]

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:

Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:

Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:

Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:

Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!

In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.

[Andrej Karpathy @karpathy]

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:

Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:

Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:

Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:

Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!

In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.