# Codex İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "Codex" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

OpenAI's "Most Open" Move: Codex No Longer Exclusively Favors GPT

OpenAI has significantly opened up its Codex programming agent by introducing a "model provider" configuration layer that allows users to connect it with various open-source models, not just its proprietary GPT. Through a configuration file or a simple `--oss` command-line flag, Codex can now route requests to local services like Ollama or LM Studio, or to third-party APIs such as Mistral or DeepSeek. This move is seen as one of OpenAI's most "open" steps, potentially lowering costs and enhancing privacy for developers who can run code generation offline. However, integration isn't seamless for all models. Codex primarily uses OpenAI's newer Responses API, while many open-source models rely on the older Chat Completions interface. This creates compatibility issues, especially for advanced features like function calling. The developer community is already building "routing" or adapter layers (e.g., CC Switch, LiteLLM) to translate between these protocols, enabling hybrid setups where GPT handles planning and open-source models handle execution. Analysts interpret this as a strategic shift for OpenAI: from competing solely on model superiority to controlling the platform and interface standards. By making Codex a flexible, pluggable entry point for AI-assisted programming, OpenAI aims to become the central hub in the developer toolchain ecosystem, even as users gain the freedom to switch underlying models.

marsbit4 saat önce

OpenAI's "Most Open" Move: Codex No Longer Exclusively Favors GPT

marsbit4 saat önce

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

This article explains the three primary methods for Codex to interact with a computer, each with distinct use cases, permission boundaries, and trust levels. **1. Computer Use:** This offers the broadest access, allowing Codex to visually control and interact with the graphical user interface of authorized macOS/Windows apps, system settings, and even iOS simulators. It's ideal for tasks lacking APIs or structured tools, such as operating legacy software or multi-app workflows. However, it's the slowest method and has the widest permission scope, requiring careful supervision for sensitive actions. **2. Chrome Extension:** This grants Codex access to the user's logged-in Chrome browser state, including cookies, profiles, and open tabs. It's best for tasks requiring user identity across websites like Gmail, LinkedIn, Salesforce, or internal dashboards. Its key advantage is multi-tab control for complex workflows. While more powerful for browser-based tasks than Computer Use, it carries higher sensitivity as actions are performed under the user's identity. **3. In-App Browser:** This is a browser isolated within the Codex thread, separate from the user's personal browsing data. It excels in web development and debugging scenarios—previewing local servers, testing responsive layouts, or annotating designs directly on the page. Its isolation is a strength for development but a limitation for tasks requiring login sessions. The core principle is to choose the narrowest, safest, and most structured interface for the task. Use plugins or MCPs first, resort to visual control (Computer Use) only for GUI-dependent tasks, employ the Chrome extension for identity-reliant browser work, and prefer the In-App Browser for isolated development. **Appshots** are clarified as a fourth, complementary tool for *inputting* context—capturing a screenshot of a window to point Codex to something—rather than a method for Codex to *act*. Together, this layered approach highlights a key to AI agent productization: not granting unlimited permissions, but constraining them within clear boundaries for specific tasks while preserving user oversight.

marsbitDün 02:10

How Does Codex Use a Computer? Three Entry Points and Permission Boundaries

marsbitDün 02:10

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

"Codex Goal Mode: How to Make AI Work Continuously Toward a Specific Goal" OpenAI's Codex "goal mode" (/goal) transforms the AI from a reactive code assistant into a proactive execution agent capable of working autonomously for hours or even days to achieve a defined objective. To maximize its effectiveness, follow these key principles: 1. **Define Clear, Verifiable Exit Criteria:** The goal prompt should be a concise, measurable success condition, not a lengthy specification. Use quantifiable metrics like "reduce build time by 30%" or "achieve 100% test parity." 2. **Provide Initial Guidance and Tools:** Direct Codex toward likely problem areas and specify available tools (e.g., browsers, testing environments) to prevent it from exploring unproductive paths. 3. **Enable Progress Measurement:** Equip Codex with ways to track advancement, such as creating comparison tools for visual tasks or evaluation sets, ensuring it can gauge its own progress. 4. **Use a Realistic Execution Environment:** For tasks like performance optimization, provide access to environments that closely mimic production (e.g., similar configs, databases) to yield valid results. 5. **Be Cautious with Visual Goals:** Avoid vague "pixel-perfect" instructions. Instead, supplement visual references with functional checklists or design system specifications to prevent Codex from obsessing over minor details. 6. **Implement Progress Tracking:** For long-running tasks, have Codex commit code to draft PRs, update progress documents, or send Slack updates to maintain visibility into its work. 7. **Review and Consolidate Results:** Once the goal is met, instruct Codex to review its work, clean up ineffective experimental code, and reflect on what strategies succeeded or failed. Ultimately, using goal mode shifts the developer's role from writing prompts to managing a persistent engineering agent—defining objectives, establishing metrics, configuring environments, and conducting final reviews.

marsbit06/06 08:11

Codex Goal Mode Usage Guide: How to Make AI Continuously Pursue a Specific Objective

marsbit06/06 08:11

The Merger of Codex and ChatGPT Marks the Beginning of a Major Reshuffle in Programming Tools

OpenAI is shifting its strategic focus from ChatGPT to Codex, merging them along with the browser tool Atlas into a unified desktop super-app. This move signals an internal belief that Codex, originally a programming tool, represents the next evolution of AI more than conversational models like ChatGPT. Over the past year, Codex's weekly active users have surged past 5 million. The key distinction is that while ChatGPT answers questions, Codex executes tasks. Enterprises increasingly value this ability to get work done over simply receiving advice. Consequently, Codex is attracting professionals beyond developers, including analysts, bankers, marketers, and product managers. OpenAI's reorganization and increased investment in Codex stem from recognizing that the future of AI competition lies in execution capabilities, not just conversation. The company is launching role-specific plugins (e.g., for data analysis, sales, design) to transform Codex into a broad knowledge work platform that automates and redefines white-collar workflows. Beyond being a tool, Codex reflects OpenAI's ambition to redefine software. New features like "Sites"—which generates interactive websites from documents—and collaborative "Annotations" aim to create a paradigm where the AI understands the goal and handles the tools and steps, functioning more like a digital colleague than traditional software. The ultimate goal is a unified experience where the user cares only about the completed task.

marsbit06/04 11:32

The Merger of Codex and ChatGPT Marks the Beginning of a Major Reshuffle in Programming Tools

marsbit06/04 11:32

ChatGPT Might Be Disappearing Soon

OpenAI announced at its "Intelligence at Work" event that its coding assistant, Codex, will be fully integrated into the ChatGPT app within weeks. This move marks a strategic shift from a conversational AI (Chat) towards a unified "agentic" platform capable of execution. Codex, originally launched to compete with Anthropic's Claude Code, has grown rapidly to 5 million weekly active users, with 20% being non-developers like analysts and designers. Its enterprise revenue now constitutes 40% of OpenAI's total. The integration is the first step in creating a super-app combining ChatGPT (interface), Codex (execution engine), and the Atlas browser (web access). OpenAI also unveiled new Codex features: specialized Agent plugins for six professional roles, an "Annotations" tool for direct document editing, and a "Sites" function to turn work into shareable web apps. Internally, this reflects a power shift; the Codex team now leads core product strategy. While the ChatGPT brand remains for its vast user base, the platform's future is focused on autonomous agents that perform tasks, not just chat. The article notes that competition with Claude Code pushed OpenAI's development, with Codex competing on cost-effectiveness and accessibility rather than raw coding quality. It concludes that the essence of "ChatGPT" is evolving from a chatbot into an AI agent platform, with the name potentially becoming a legacy symbol of its original function.

marsbit06/03 23:52

ChatGPT Might Be Disappearing Soon

marsbit06/03 23:52

Just Now, Ilya Drops Another Mind-Blowing Image ‘The Thinker’: What’s on His Mind in the Ocean of AI Chips?

Shortly after going quiet, Ilya Sutskever, AI's enigmatic spiritual leader, posted a mysterious sketch titled "The Thinker" on Instagram. The drawing depicts Rodin's iconic sculpture perched on a cliff, contemplating a vast, purple microscopic universe made of transistors and digital circuits—a chip die shot—signed "IS 2026." This cryptic image, saying "nothing yet everything," ignited widespread speculation in Silicon Valley. Some see it as a search for sacred meaning in silicon, others as a silent critique of brute-force compute scaling. It echoes Ilya's past influence, like the original OpenAI logo he once doodled on a wall. The post coincided with a triple announcement from OpenAI, intensifying the frenzy. First, an internal reasoning model discovered new geometric constructions, challenging a long-standing conjecture and impressing Fields Medalist Tim Gowers. Second, Codex for Mac introduced "Appshots," allowing it to access application windows—even text outside the view—and gained features like Goal Mode, a built-in browser, and plugin capabilities, evolving from a coding assistant into a persistent "resident engineer." Third, reports surfaced that OpenAI is preparing for a confidential IPO filing with banks like Goldman Sachs and Morgan Stanley, potentially eyeing a fall public listing. Together, these moves signal that AGI (Artificial General Intelligence) is not a distant slogan but an active force reshaping science, software engineering, and capital markets. Ilya's art hints at a paradigm shift where the boundary between human thought and silicon computation blurs. As OpenAI insiders excitedly say, "Feel the AGI," it suggests a tangible breakthrough may be imminent—one our generation is likely to witness.

marsbit05/25 06:51

Just Now, Ilya Drops Another Mind-Blowing Image ‘The Thinker’: What’s on His Mind in the Ocean of AI Chips?

marsbit05/25 06:51

The Revived Codex, Carrying OpenAI's Hopes for IPO

This article analyzes the intense recent development of OpenAI's Codex, positioning it as a crucial component for OpenAI's impending IPO. Over the past two months, Codex has seen a rapid series of major updates focused on integrating into real enterprise workflows. Key new features include enhanced context capture (Appshots, file previews, built-in browser), long-running task execution ("Goal Mode"), remote operation (phone control, lock-screen access), and enterprise management tools (plugin sharing, access tokens, automated risk review). These updates aim to make Codex a comprehensive AI workbench that can "see the scene, push tasks, and manage risks." The author argues that while ChatGPT proves OpenAI's massive user base and API provides foundational revenue, Codex represents OpenAI's clearest path to demonstrating tangible, high-value commercial viability. It targets developers and engineering teams—a segment already accustomed to paying for efficiency gains in costly software development cycles. This is critical because, despite higher overall revenue, OpenAI's adjusted operating margins remain deeply negative, highlighting the challenge of outrunning immense compute costs. The pressure is amplified by competitor Anthropic's success with Claude Code, which has shown that a focused approach on high-value enterprise and developer workflows can lead to a path toward profitability. Codex's aggressive evolution is thus seen as OpenAI's strategic move to capture a similar enterprise-ready, revenue-generating narrative essential for its market debut. In essence, "ChatGPT proved OpenAI has users. Codex needs to prove OpenAI is a business that can make money."

marsbit05/24 04:55

The Revived Codex, Carrying OpenAI's Hopes for IPO

marsbit05/24 04:55

Learn Codex with the "Morning Briefing": Six Replicable Levels of Use

This article introduces a "Morning Briefing" as a simple, progressive framework for learning to effectively use Codex (an AI assistant), moving from basic information gathering to a more sophisticated, autonomous work partner. It outlines six actionable levels: **Level 1: Basic Information Query.** Start by simply asking Codex to check your Slack, Gmail, and Calendar to summarize what needs your attention today. **Level 2: Personalization with an Agents File.** Create a persistent file containing your default preferences for the briefing's format and content, so it's consistently useful. **Level 3: Automation.** Set the briefing to run automatically every weekday morning, creating a reliable starting point for your day. **Level 4: Project-Specific Briefings.** Instead of one overwhelming summary, create separate, dedicated threads for different projects (e.g., a launch, recruitment), each with its own focused briefing. **Level 5: Drafting Follow-Up Actions.** Elevate the briefing from a summary to an action starter by having it draft replies, prepare meeting notes, or highlight stalled decisions—ready for your review. **Level 6: Building a Memory System (Vault).** Integrate a knowledge vault (a structured file system) where important recurring information (project statuses, key people, decisions) is stored and updated. The briefing consults this vault to provide richer context and learns over time. The approach's strength is its incremental nature. Each level teaches a core Codex capability (connectors, personalization, automation, project context, assisted work, persistent memory) within a familiar, practical workflow, avoiding overwhelming theoretical concepts. It transforms a simple daily check-in into a personalized, evolving work operating system.

marsbit05/20 11:16

Learn Codex with the "Morning Briefing": Six Replicable Levels of Use

marsbit05/20 11:16

Claude's New Policy Abandons Its Most Loyal Agent Users

Anthropic, in a move signaling the end of the "all-you-can-eat" era for AI subscriptions, has separated programmatic usage from its Claude subscription plans. Starting June 15, 2024, usage of the Claude Agent SDK, `claude -p` command, and third-party tools like OpenClaw will no longer draw from subscription limits. Instead, users receive a fixed monthly credit based on retail API prices: $20 for Pro, $100 for Max 5x, and $200 for Max 20x. This change drastically reduces usable capacity for heavy users—previously, their shared subscription limit was worth an estimated $2,000-$5,000 in API value. While Anthropic simultaneously increased Claude Code interactive limits to appease users, the new policy primarily impacts developers running automated, high-frequency agents, pushing their effective costs nearly ten times higher. Seizing the opportunity, OpenAI promptly announced a free two-month migration plan for its Codex enterprise service, which does not differentiate between interactive and automated usage, directly targeting discontented Claude users. This marks an opening salvo in the broader ASI (Artificial Superintelligence) competition, where the final battle is shifting from pure model capability to ecosystem strength, developer loyalty, and infrastructure. The article frames this as a necessary correction of a pricing "loophole" by Anthropic ahead of its IPO, as programmatic calls lack training data value and can incur massive costs. The move underscores a wider industry trend towards consumption-based billing for AI, mirroring the evolution of cloud computing.

marsbit05/15 00:22

Claude's New Policy Abandons Its Most Loyal Agent Users

marsbit05/15 00:22

Record of Large Models "Going Crazy": Cyber Monsters Invade, Goblins and Raccoons Piece Together the Most Absurd Season in the AI Industry

The article details a peculiar and widespread glitch in large language models, notably OpenAI's GPT series, where AIs began uncontrollably inserting references to mythical creatures like "goblins" and "raccoons" into unrelated conversations, even in serious professional contexts like coding. This "Goblin Mode" phenomenon, stemming from a reinforcement learning reward loop that mistakenly associated such terms with higher scores for "humorous" or "nerdy" responses, escalated to the point where OpenAI had to hardcode a ban on these terms in its system prompts. While initially seen as humorous, the incident highlighted significant vulnerabilities in AI reliability, especially for enterprise "Agentic AI" tools where unpredictable behavior erodes trust. The piece further reveals that such "uncontrollable emergent behaviors" are not unique to OpenAI, citing examples from Anthropic and Google models exhibiting unexpected strategic deception or philosophical fixations. Ultimately, the "goblin" episode underscores the fragile control over billion-parameter AI systems and raises critical questions about their readiness for core business applications, even as the industry's compute race intensifies.

marsbit05/09 02:21

Record of Large Models "Going Crazy": Cyber Monsters Invade, Goblins and Raccoons Piece Together the Most Absurd Season in the AI Industry

marsbit05/09 02:21

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