#codexcli — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #codexcli, aggregated by home.social.
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From the Leanpub Blog: The Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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From the Leanpub Blog: The Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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From the Leanpub Blog: The Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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From the Leanpub Blog: The Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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Check out the Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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Check out the Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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Check out the Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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Check out the Leanpub Podcast 🎙 Feat. Daniel Vaughan, Author of Codex CLI: Agentic Engineering from First Principles
#books #leanpublishing #selfpublishing #codexcli #ai #programming
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터미널 AI 3대장, 뭐가 다를까?
AI 채팅창이 아닌 터미널에서 직접 코딩하는 시대가 열렸습니다. Anthropic·OpenAI·Google이 내놓은 터미널 AI 도구 3가지를 비교하고, 각각의 강점과 나에게 맞는 선택법을 알려드립니다.
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"Description technique détaillée du fonctionnement interne de l'agent de codage d' #OpenAI #CodexCLI, un outil de codage #IA qui écrit du code, exécute des tests et corrige des bogues"
Intéressant de voir un peu la technique derrière les belles paroles.
Et bien je ne suis pas près de laisser les rênes de mon PC à ce genre de programme!!!
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"Description technique détaillée du fonctionnement interne de l'agent de codage d' #OpenAI #CodexCLI, un outil de codage #IA qui écrit du code, exécute des tests et corrige des bogues"
Intéressant de voir un peu la technique derrière les belles paroles.
Et bien je ne suis pas près de laisser les rênes de mon PC à ce genre de programme!!!
-
"Description technique détaillée du fonctionnement interne de l'agent de codage d' #OpenAI #CodexCLI, un outil de codage #IA qui écrit du code, exécute des tests et corrige des bogues"
Intéressant de voir un peu la technique derrière les belles paroles.
Et bien je ne suis pas près de laisser les rênes de mon PC à ce genre de programme!!!
-
"Description technique détaillée du fonctionnement interne de l'agent de codage d' #OpenAI #CodexCLI, un outil de codage #IA qui écrit du code, exécute des tests et corrige des bogues"
Intéressant de voir un peu la technique derrière les belles paroles.
Et bien je ne suis pas près de laisser les rênes de mon PC à ce genre de programme!!!
-
"Description technique détaillée du fonctionnement interne de l'agent de codage d' #OpenAI #CodexCLI, un outil de codage #IA qui écrit du code, exécute des tests et corrige des bogues"
Intéressant de voir un peu la technique derrière les belles paroles.
Et bien je ne suis pas près de laisser les rênes de mon PC à ce genre de programme!!!
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AI 에이전트의 엔진룸, OpenAI가 공개한 Agent Loop의 비밀
OpenAI가 Codex CLI의 핵심 작동 원리인 agent loop를 공개했습니다. AI 에이전트가 어떻게 대화하고 작업하는지, 프롬프트 캐싱과 컨텍스트 관리 전략을 실제 코드와 함께 설명합니다. -
AI 에이전트의 엔진룸, OpenAI가 공개한 Agent Loop의 비밀
OpenAI가 Codex CLI의 핵심 작동 원리인 agent loop를 공개했습니다. AI 에이전트가 어떻게 대화하고 작업하는지, 프롬프트 캐싱과 컨텍스트 관리 전략을 실제 코드와 함께 설명합니다. -
AI 에이전트의 엔진룸, OpenAI가 공개한 Agent Loop의 비밀
OpenAI가 Codex CLI의 핵심 작동 원리인 agent loop를 공개했습니다. AI 에이전트가 어떻게 대화하고 작업하는지, 프롬프트 캐싱과 컨텍스트 관리 전략을 실제 코드와 함께 설명합니다. -
AI 에이전트의 엔진룸, OpenAI가 공개한 Agent Loop의 비밀
OpenAI가 Codex CLI의 핵심 작동 원리인 agent loop를 공개했습니다. AI 에이전트가 어떻게 대화하고 작업하는지, 프롬프트 캐싱과 컨텍스트 관리 전략을 실제 코드와 함께 설명합니다. -
AI 에이전트의 엔진룸, OpenAI가 공개한 Agent Loop의 비밀
OpenAI가 Codex CLI의 핵심 작동 원리인 agent loop를 공개했습니다. AI 에이전트가 어떻게 대화하고 작업하는지, 프롬프트 캐싱과 컨텍스트 관리 전략을 실제 코드와 함께 설명합니다. -
"Codex CLI is our cross-platform local software agent, designed to produce high-quality, reliable software changes while operating safely and efficiently on your machine. We’ve learned a tremendous amount about how to build a world-class software agent since we first launched the CLI in April. To unpack those insights, this is the first post in an ongoing series where we’ll explore various aspects of how Codex works, as well as hard-earned lessons. (For an even more granular view on how the Codex CLI is built, check out our open source repository at https://github.com/openai/codex. Many of the finer details of our design decisions are memorialized in GitHub issues and pull requests if you’d like to learn more.)
To kick off, we’ll focus on the agent loop, which is the core logic in Codex CLI that is responsible for orchestrating the interaction between the user, the model, and the tools the model invokes to perform meaningful software work. We hope this post gives you a good view into the role our agent (or “harness”) plays in making use of an LLM.
Before we dive in, a quick note on terminology: at OpenAI, “Codex” encompasses a suite of software agent offerings, including Codex CLI, Codex Cloud, and the Codex VS Code extension. This post focuses on the Codex harness, which provides the core agent loop and execution logic that underlies all Codex experiences and is surfaced through the Codex CLI. For ease here, we’ll use the terms “Codex” and “Codex CLI” interchangeably."
https://openai.com/index/unrolling-the-codex-agent-loop/
#AI #GenerativeAI #LLMs #OpenAI #CodexCLI #Codex #AIAgents #AgenticAI #Programming #SoftwareDevelopment
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"Codex CLI is our cross-platform local software agent, designed to produce high-quality, reliable software changes while operating safely and efficiently on your machine. We’ve learned a tremendous amount about how to build a world-class software agent since we first launched the CLI in April. To unpack those insights, this is the first post in an ongoing series where we’ll explore various aspects of how Codex works, as well as hard-earned lessons. (For an even more granular view on how the Codex CLI is built, check out our open source repository at https://github.com/openai/codex. Many of the finer details of our design decisions are memorialized in GitHub issues and pull requests if you’d like to learn more.)
To kick off, we’ll focus on the agent loop, which is the core logic in Codex CLI that is responsible for orchestrating the interaction between the user, the model, and the tools the model invokes to perform meaningful software work. We hope this post gives you a good view into the role our agent (or “harness”) plays in making use of an LLM.
Before we dive in, a quick note on terminology: at OpenAI, “Codex” encompasses a suite of software agent offerings, including Codex CLI, Codex Cloud, and the Codex VS Code extension. This post focuses on the Codex harness, which provides the core agent loop and execution logic that underlies all Codex experiences and is surfaced through the Codex CLI. For ease here, we’ll use the terms “Codex” and “Codex CLI” interchangeably."
https://openai.com/index/unrolling-the-codex-agent-loop/
#AI #GenerativeAI #LLMs #OpenAI #CodexCLI #Codex #AIAgents #AgenticAI #Programming #SoftwareDevelopment
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"Codex CLI is our cross-platform local software agent, designed to produce high-quality, reliable software changes while operating safely and efficiently on your machine. We’ve learned a tremendous amount about how to build a world-class software agent since we first launched the CLI in April. To unpack those insights, this is the first post in an ongoing series where we’ll explore various aspects of how Codex works, as well as hard-earned lessons. (For an even more granular view on how the Codex CLI is built, check out our open source repository at https://github.com/openai/codex. Many of the finer details of our design decisions are memorialized in GitHub issues and pull requests if you’d like to learn more.)
To kick off, we’ll focus on the agent loop, which is the core logic in Codex CLI that is responsible for orchestrating the interaction between the user, the model, and the tools the model invokes to perform meaningful software work. We hope this post gives you a good view into the role our agent (or “harness”) plays in making use of an LLM.
Before we dive in, a quick note on terminology: at OpenAI, “Codex” encompasses a suite of software agent offerings, including Codex CLI, Codex Cloud, and the Codex VS Code extension. This post focuses on the Codex harness, which provides the core agent loop and execution logic that underlies all Codex experiences and is surfaced through the Codex CLI. For ease here, we’ll use the terms “Codex” and “Codex CLI” interchangeably."
https://openai.com/index/unrolling-the-codex-agent-loop/
#AI #GenerativeAI #LLMs #OpenAI #CodexCLI #Codex #AIAgents #AgenticAI #Programming #SoftwareDevelopment
-
"Codex CLI is our cross-platform local software agent, designed to produce high-quality, reliable software changes while operating safely and efficiently on your machine. We’ve learned a tremendous amount about how to build a world-class software agent since we first launched the CLI in April. To unpack those insights, this is the first post in an ongoing series where we’ll explore various aspects of how Codex works, as well as hard-earned lessons. (For an even more granular view on how the Codex CLI is built, check out our open source repository at https://github.com/openai/codex. Many of the finer details of our design decisions are memorialized in GitHub issues and pull requests if you’d like to learn more.)
To kick off, we’ll focus on the agent loop, which is the core logic in Codex CLI that is responsible for orchestrating the interaction between the user, the model, and the tools the model invokes to perform meaningful software work. We hope this post gives you a good view into the role our agent (or “harness”) plays in making use of an LLM.
Before we dive in, a quick note on terminology: at OpenAI, “Codex” encompasses a suite of software agent offerings, including Codex CLI, Codex Cloud, and the Codex VS Code extension. This post focuses on the Codex harness, which provides the core agent loop and execution logic that underlies all Codex experiences and is surfaced through the Codex CLI. For ease here, we’ll use the terms “Codex” and “Codex CLI” interchangeably."
https://openai.com/index/unrolling-the-codex-agent-loop/
#AI #GenerativeAI #LLMs #OpenAI #CodexCLI #Codex #AIAgents #AgenticAI #Programming #SoftwareDevelopment
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"Codex CLI is our cross-platform local software agent, designed to produce high-quality, reliable software changes while operating safely and efficiently on your machine. We’ve learned a tremendous amount about how to build a world-class software agent since we first launched the CLI in April. To unpack those insights, this is the first post in an ongoing series where we’ll explore various aspects of how Codex works, as well as hard-earned lessons. (For an even more granular view on how the Codex CLI is built, check out our open source repository at https://github.com/openai/codex. Many of the finer details of our design decisions are memorialized in GitHub issues and pull requests if you’d like to learn more.)
To kick off, we’ll focus on the agent loop, which is the core logic in Codex CLI that is responsible for orchestrating the interaction between the user, the model, and the tools the model invokes to perform meaningful software work. We hope this post gives you a good view into the role our agent (or “harness”) plays in making use of an LLM.
Before we dive in, a quick note on terminology: at OpenAI, “Codex” encompasses a suite of software agent offerings, including Codex CLI, Codex Cloud, and the Codex VS Code extension. This post focuses on the Codex harness, which provides the core agent loop and execution logic that underlies all Codex experiences and is surfaced through the Codex CLI. For ease here, we’ll use the terms “Codex” and “Codex CLI” interchangeably."
https://openai.com/index/unrolling-the-codex-agent-loop/
#AI #GenerativeAI #LLMs #OpenAI #CodexCLI #Codex #AIAgents #AgenticAI #Programming #SoftwareDevelopment
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Công cụ CLI aichat giúp tìm kiếm toàn văn nhanh và tiếp tục phiên làm việc với Claude-Code/Codex mà không cần nén nội dung. Hỗ trợ tìm kiếm bằng giao diện TUI siêu nhanh (Rust/Tantivy), sao chép phiên, cắt bỏ thông minh hoặc chuyển tiếp sang phiên mới có tích hợp lịch sử (lineage). Dễ dàng tìm lại ngữ cảnh cũ qua lệnh `>resume` hoặc `aichat search`. Hữu ích cho phát triển AI agent và làm việc dài hạn. #aichat #ClaudeCode #CodexCLI #AI #Productivity #công_cụ #trí_tuệ_nhân_tạo #hiệu_suất
https://
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レビューしやすい設計書を作ってくれるエージェント決定戦！ cc-sddで設計書作って比べてみた
https://qiita.com/kaaaichi_i/items/7083543acaad53c39b30?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items -
OpenAI Adds ‘Skills’ Framework to ChatGPT and Codex CLI, Mirroring Anthropic’s Agent Standard
#AI #OpenAI #ChatGPT #CodexCLI #AIAgents #DeveloperTools #SoftwareEngineering #Anthropic #MCP #Programming #GPT52 #GenAI
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OpenAI Adds ‘Skills’ Framework to ChatGPT and Codex CLI, Mirroring Anthropic’s Agent Standard
#AI #OpenAI #ChatGPT #CodexCLI #AIAgents #DeveloperTools #SoftwareEngineering #Anthropic #MCP #Programming #GPT52 #GenAI
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OpenAI Adds ‘Skills’ Framework to ChatGPT and Codex CLI, Mirroring Anthropic’s Agent Standard
#AI #OpenAI #ChatGPT #CodexCLI #AIAgents #DeveloperTools #SoftwareEngineering #Anthropic #MCP #Programming #GPT52 #GenAI
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OpenAI Adds ‘Skills’ Framework to ChatGPT and Codex CLI, Mirroring Anthropic’s Agent Standard
#AI #OpenAI #ChatGPT #CodexCLI #AIAgents #DeveloperTools #SoftwareEngineering #Anthropic #MCP #Programming #GPT52 #GenAI
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OpenAI Adds ‘Skills’ Framework to ChatGPT and Codex CLI, Mirroring Anthropic’s Agent Standard
#AI #OpenAI #ChatGPT #CodexCLI #AIAgents #DeveloperTools #SoftwareEngineering #Anthropic #MCP #Programming #GPT52 #GenAI
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#OpenAI has quietly implemented #skills support in both #ChatGPT and #CodexCLI. The skills, similar to #Anthropic’s implementation, are #folders containing a #Markdownfile and optional resources. This allows users to create #customfunctionalities, such as generating PDFs or writing Datasette plugins, by leveraging existing skills or creating their own. https://simonwillison.net/2025/Dec/12/openai-skills/?eicker.news #tech #media #news
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#OpenAI has quietly implemented #skills support in both #ChatGPT and #CodexCLI. The skills, similar to #Anthropic’s implementation, are #folders containing a #Markdownfile and optional resources. This allows users to create #customfunctionalities, such as generating PDFs or writing Datasette plugins, by leveraging existing skills or creating their own. https://simonwillison.net/2025/Dec/12/openai-skills/?eicker.news #tech #media #news
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#OpenAI has quietly implemented #skills support in both #ChatGPT and #CodexCLI. The skills, similar to #Anthropic’s implementation, are #folders containing a #Markdownfile and optional resources. This allows users to create #customfunctionalities, such as generating PDFs or writing Datasette plugins, by leveraging existing skills or creating their own. https://simonwillison.net/2025/Dec/12/openai-skills/?eicker.news #tech #media #news
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#OpenAI has quietly implemented #skills support in both #ChatGPT and #CodexCLI. The skills, similar to #Anthropic’s implementation, are #folders containing a #Markdownfile and optional resources. This allows users to create #customfunctionalities, such as generating PDFs or writing Datasette plugins, by leveraging existing skills or creating their own. https://simonwillison.net/2025/Dec/12/openai-skills/?eicker.news #tech #media #news
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#OpenAI has quietly implemented #skills support in both #ChatGPT and #CodexCLI. The skills, similar to #Anthropic’s implementation, are #folders containing a #Markdownfile and optional resources. This allows users to create #customfunctionalities, such as generating PDFs or writing Datasette plugins, by leveraging existing skills or creating their own. https://simonwillison.net/2025/Dec/12/openai-skills/?eicker.news #tech #media #news
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Codex CLI Silent RCE Flaw (CVE-2025-61260)
https://www.technadu.com/codex-cli-flaw-allowed-silent-remote-code-execution-through-malicious-repository-configurations/614994/• Repo configs auto-executed MCP commands
• Backdoors via commit/PR access
• CI & developer endpoints at risk
• Root cause: trusted repo-level config execution
• Patched in v0.23.0A critical reminder that AI-powered developer tools must adopt strict zero-trust defaults.
Follow us for ongoing security coverage.#Cybersecurity #CodexCLI #RCE #AIThreats #SupplyChainSecurity #DevSecOps #InfoSec
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Codex CLI Silent RCE Flaw (CVE-2025-61260)
https://www.technadu.com/codex-cli-flaw-allowed-silent-remote-code-execution-through-malicious-repository-configurations/614994/• Repo configs auto-executed MCP commands
• Backdoors via commit/PR access
• CI & developer endpoints at risk
• Root cause: trusted repo-level config execution
• Patched in v0.23.0A critical reminder that AI-powered developer tools must adopt strict zero-trust defaults.
Follow us for ongoing security coverage.#Cybersecurity #CodexCLI #RCE #AIThreats #SupplyChainSecurity #DevSecOps #InfoSec
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Codex CLI Silent RCE Flaw (CVE-2025-61260)
https://www.technadu.com/codex-cli-flaw-allowed-silent-remote-code-execution-through-malicious-repository-configurations/614994/• Repo configs auto-executed MCP commands
• Backdoors via commit/PR access
• CI & developer endpoints at risk
• Root cause: trusted repo-level config execution
• Patched in v0.23.0A critical reminder that AI-powered developer tools must adopt strict zero-trust defaults.
Follow us for ongoing security coverage.#Cybersecurity #CodexCLI #RCE #AIThreats #SupplyChainSecurity #DevSecOps #InfoSec
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Vulnerability in OpenAI Coding Agent Could Facilitate Attacks on Developers https://www.securityweek.com/vulnerability-in-openai-coding-agent-could-facilitate-attacks-on-developers/ #ArtificialIntelligence #vulnerability #CodexCLI #OpenAI #AI
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Vulnerability in OpenAI Coding Agent Could Facilitate Attacks on Developers https://www.securityweek.com/vulnerability-in-openai-coding-agent-could-facilitate-attacks-on-developers/ #ArtificialIntelligence #vulnerability #CodexCLI #OpenAI #AI
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Vulnerability in OpenAI Coding Agent Could Facilitate Attacks on Developers https://www.securityweek.com/vulnerability-in-openai-coding-agent-could-facilitate-attacks-on-developers/ #ArtificialIntelligence #vulnerability #CodexCLI #OpenAI #AI
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Vulnerability in OpenAI Coding Agent Could Facilitate Attacks on Developers https://www.securityweek.com/vulnerability-in-openai-coding-agent-could-facilitate-attacks-on-developers/ #ArtificialIntelligence #vulnerability #CodexCLI #OpenAI #AI
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OpenAI just rolled out GPT‑5.1‑Codex‑Max, a new Codex CLI that finishes a 24‑hour coding sprint on its own. With “thinking tokens” and autonomous debugging, it pushes LLM‑driven development to a new level. Curious how it works and what it means for open‑source tooling? Dive into the details. #GPT5_1CodexMax #CodexCLI #ThinkingTokens #AutonomousDebugging
🔗 https://aidailypost.com/news/openai-launches-gpt51codexmax-completes-24hour-coding-task-internally
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OpenAI just rolled out GPT‑5.1‑Codex‑Max, a new Codex CLI that finishes a 24‑hour coding sprint on its own. With “thinking tokens” and autonomous debugging, it pushes LLM‑driven development to a new level. Curious how it works and what it means for open‑source tooling? Dive into the details. #GPT5_1CodexMax #CodexCLI #ThinkingTokens #AutonomousDebugging
🔗 https://aidailypost.com/news/openai-launches-gpt51codexmax-completes-24hour-coding-task-internally
