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Peter Steinberger

别名:@steipete

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已跟踪 30 条高相关材料

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已收录 30 条与 Peter Steinberger 相关的内容,按评分排序。

科技爱好者周刊(第 398 期):Token 费用难以负担

Tech Enthusiast Weekly (Issue #398): Token Costs Are Unbearable

阮一峰的网络日志3982 字 (约 16 分钟)
87

An OpenAI employee consumed 603 billion tokens in one month—valued at $1.3M—revealing the true cost of AI programming; Uber burned through its $3.4B annual AI budget in four months, and Microsoft dropped Claude Code, proving unlimited top-model usage is financially unsustainable; domestic open-source models cost 1/30–1/50 of foreign flagship models, but strongest models remain closed-source and self-hosting incurs high hardware costs.

入选理由:OpenAI员工单月使用6030亿Token(≈130万美元),若按市场价折算,程序员年均Token成本达200万~1亿人民币。

FeaturedArticle#AI Cost#LLM#OpenAI#Enterprise AI#Open-Source Models中文
OpenClaw went viral. Meet the maintainers building and securing it.

OpenClaw went viral. Meet the maintainers building and securing it.

The GitHub Blog1744 字 (约 7 分钟)
85

OpenClaw项目因AI助手的快速普及面临维护挑战,维护者分享了处理贡献、安全和社区管理的实战经验。

入选理由:OpenClaw项目6个月内获得38.8万星标,8.1万次Fork

FeaturedArticle#OpenClaw#开源#AI助手#GitHub#软件维护英文
https://t.co/COWVOjkOrw

https://t.co/COWVOjkOrw

Augment Code(@augmentcode)1682 字 (约 7 分钟)
85

循环工程通过代理与人类协作重构软件开发流程,实现从触发到交付的全链路自动化。

入选理由:团队级循环工程需设计代理系统与人类判断点的协同机制

FeaturedTweet#软件工程#自动化#代理系统#团队协作英文
A New Generation Studies AI, Apple's Recipe for On-Device Models, GLM5.2 Tackles Open-Ended Problems

文章介绍了构建0到1产品的三种关键循环,包括代理编码循环、工程循环和开发者反馈循环,为AI代理开发提供了实践指导。

入选理由:代理编码循环使AI代理能独立编写、测试和迭代代码,减少人工干预。

FeaturedArticle#AI代理#软件开发#工程循环#产品设计英文
[AINews] Loopcraft: The Art of Stacking Loops

[AINews] Loopcraft: The Art of Stacking Loops

Latent Space2019 字 (约 9 分钟)
85

文章强调了通过设计自主循环系统来提升AI代理效率,而非依赖人工干预。

入选理由:Andrej Karpathy认为,要最大化模型的token吞吐量,必须将自身排除在循环之外。

FeaturedArticle#AI代理#循环系统#Autoresearch#AI优化英文
Loop Engineering

Loop Engineering

Elevate2518 字 (约 11 分钟)
85

Loop Engineering 是一种通过设计系统来替代人工提示 AI 代理的新方法,未来可能成为与 AI 协作的主要方式。

入选理由:Loop Engineering 通过设计系统替代人工提示 AI 代理,包含五个核心组件和一个记忆模块。

FeaturedArticle#AI#Loop Engineering#Codex#Claude Code#系统设计英文
用Codex并行调试验证修复

Parallel Debugging and Fix Verification with Codex

AI HOT 精选171 字 (约 1 分钟)
85

Developers use Codex to debug and verify fixes in temporary sandboxes, improving efficiency and avoiding local environment pollution.

入选理由:Codex可重建精确状态进行调试

FeaturedArticle#Codex#Debugging#AI Tools中文
“五类人AI替代不了,企业做第二名最稳妥” | 昆仑万维方汉@AIGC2026

At AIGC2026, Fang Han stated that in the age of AI, experience is no longer a moat; token consumption has become a new indicator of AI capability.

入选理由:Token消耗量正成为AI时代新的硬核实力指标,普通用户与重度用户差距可达数个数量级。

FeaturedArticle#AI#AIGC#Token#Career#Enterprise Strategy中文
FeaturedTweet#QA测试#自动化#Codex#OpenClaw英文
OpenClaw’s Peter Steinberger envisions a world where anyone — and everyone — can create AI agents

Peter Steinberger of OpenClaw discusses his vision for a future where anyone can create AI agents, sharing insights from the development of OpenClaw and how AI agents differ from chatbots, potentially reshaping work, creation, and technology.

入选理由:OpenClaw's Peter Steinberger envisions universal access to AI agent creation.

FeaturedVideo#AI Agents#OpenClaw#Peter Steinberger#TED Talk#Open Source中文
Been running codex all day to do massive parallel QA in prep of the next release. Sol got insanely good at really understanding intent and is finding complex behavior issues.

In the past such workflow did fell apart at compaction boundaries and/or the model started cheating.

使用Codex进行大规模并行QA能发现复杂问题,但需解决模型在压缩边界处的崩溃和作弊风险。

入选理由:Codex在并行QA中能发现复杂行为问题,但存在压缩边界崩溃风险

FeaturedTweet#Codex#AI测试#模型优化#QA实践英文
bolt.new(@boltdotnew) 图标

"Don't Slop Yourself into a Corner" - Peter Steinberger on Lex Fridman Podcast

bolt.new(@boltdotnew)115 字 (约 1 分钟)
65

Refactoring maintains app functionality while improving internal structure, increasing development speed and enabling better handling by tools like Bolt. This article demonstrates how through a practical tutorial.

入选理由:重构可提升代码可维护性,使 Bolt 更高效地处理应用逻辑。

FeaturedTweet#Refactoring#Bolt#Code Quality#Frontend Development英文
mem0(@mem0ai) 图标

https://t.co/Cvv7bYHNuf

mem0(@mem0ai)63 字 (约 1 分钟)
60

文章讨论了在工程实践中如何通过设计循环来优化代理提示,而非直接提示编码代理。

入选理由:设计循环来提示代理,而非直接提示编码代理。

FeaturedTweet#工程实践#代理设计#提示优化英文
Peter Steinberger(@steipete) 图标

推文未提供技术细节,仅提及OpenAI DevDay 2026中关于团队协作的代理应用,缺乏可执行信息。

入选理由:推文未提供技术细节,仅提及OpenAI DevDay 2026中关于团队协作的代理应用,缺乏可执行信息

FeaturedTweet英文
Peter Steinberger(@steipete) 图标

not as clear-cut, but also yes

Peter Steinberger(@steipete)60 字 (约 1 分钟)
50

推文讨论了AI时代团队结构的演变,但内容碎片化且缺乏技术细节,难以提供实质性工程指导。

入选理由:传统'Two-pizza团队'模式在AI时代面临挑战

FeaturedTweet#团队管理#AI时代#组织架构英文
Peter Steinberger(@steipete) 图标

推文讨论个人代理单位经济模型的生存困境,强调依赖资本或实验室资源的必要性,但缺乏技术细节和实践指导。

入选理由:个人代理单位难以独立生存,需依赖资本或实验室资源

FeaturedTweet#AI经济模型#创业#技术经济英文
RT @AdamHoltererer: Oh, thaaat's why they use a logarithmic scale!

RT @AdamHoltererer: Oh, thaaat's why they use a logarithmic scale!

Peter Steinberger(@steipete)65 字 (约 1 分钟)
50

推文内容被登录页面遮挡,未提供有效技术信息,无法判断文章价值。

入选理由:推文内容被登录页面遮挡,未提供有效技术信息,无法判断文章价值

FeaturedTweet中英混合

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