Meet Codex: OpenAI's Game-Changing AI Coder Is Here!

This AI Can Code, OpenAI Just Changed Everything

OpenAI has launched a new agentic coding tool called Codex, now in research preview. This tool is designed to help experienced developers offload repetitive and relatively simple programming tasks to an AI agent that generates production-level code, while clearly displaying each step of its process.

Codex features a specialized interface (distinct from the recently released Codex CLI tool) accessible via the sidebar in the ChatGPT web app. Developers can input a prompt and then choose either “code” to initiate code generation or “ask” to receive explanations and guidance.

Each task Codex handles runs in an isolated container that mirrors the user’s development setup and is preloaded with their codebase. To improve results, developers can include an AGENTS.md file in their repository. This file serves as a guide for the AI, similar to a README.md, but tailored for AI agents, offering context, project-specific instructions, and coding style preferences.

Codex is powered by codex-1, a version of OpenAI’s o3 reasoning model fine-tuned through reinforcement learning on various programming tasks. This enables it to write code, run tests, and iterate intelligently throughout the process.

In its announcement, OpenAI addresses common criticisms of AI coding tools, such as a lack of adherence to coding standards, poor transparency, security flaws, and debugging difficulties.

These issues have been associated with earlier generation models and tools. Codex aims to address them by making its reasoning visible throughout the process and emphasizing code quality. However, OpenAI stresses that human developers must still carefully review and validate the AI-generated code before using it in production.

Codex is currently rolling out to all ChatGPT Pro, Enterprise, and Team users. Support for Plus and Edu users is expected later. During the initial research phase, OpenAI is offering generous access at no extra cost, encouraging users to explore Codex’s capabilities. However, they plan to introduce usage limits and a new pricing structure in the future.

Y Combinator Startup Firecrawl Is Ready To Pay $1M To Hire Three AI agents As employees

Firecrawl, a Y Combinator-backed startup, is once again on the lookout for AI agent "employees" after a less-than-successful first attempt earlier this year.

The company has posted three new listings on YC’s job board—this time strictly for AI agents and has allocated a total budget of $1 million toward the initiative. Within a week of the listings going live, around 50 AI agents had applied, according to founder Caleb Peffer, who spoke to TechCrunch.

Firecrawl develops a web-crawling tool that gathers data from websites to feed large language models (LLMs). Peffer acknowledges the ethically grey area the company operates in, where some crawlers can overwhelm websites in ways similar to DDoS attacks.

However, Firecrawl has gained traction by attempting to set responsible boundaries: many customers only crawl their own websites for internal LLM use, and the tool respects robots.txt directives and can be configured to scrape each public site just once, with the resulting data shared.

Among the current AI agent roles:

1. Content Creation Agent – This AI would continuously generate SEO-optimized blog posts and tutorials, monitor engagement metrics, and autonomously refine its strategy. It’s expected to create, post, analyze, and improve content without human input. Pay: $5,000/month.

2. Customer Support Engineer Agent – This bot will craft workflows that answer user issues within two minutes, handle support tickets, and escalate only when necessary. Prior experience in customer support is required. Pay: $5,000/month.

3. Junior Developer Agent – Tasked with sorting GitHub issues, writing documentation, and coding in TypeScript and Go. Pay: $5,000/month.

That said, Firecrawl is also looking to hire human developers or creators behind these AI agents. The $1 million budget will go toward both bots and the people who build or maintain them, whether through full-time roles, contracts, or outsourcing to other startups that specialize in AI agents, for example, in the customer support domain.

Peffer admits the ideal AI employee doesn’t exist yet. He envisions a future where top-tier engineers act as commanders of fleets of AI agents they design and oversee. Firecrawl’s goal is to partner with these future “agent operators.”

And they’re not alone, Y Combinator’s job board is increasingly populated with listings for agent developers. Whether these roles will ultimately automate away their creators remains the “million-dollar question.”

Revolutionizing AI: Microsoft's Open-Source Agentic Web Takes Center Stage

At Build 2025, Microsoft unveiled NLWeb, a new open initiative designed to lay the groundwork for what it calls the open agentic web—a future where AI agents operate fluidly across different platforms, services, and devices on behalf of users and organizations.

NLWeb is being positioned as the HTML of the agentic web, offering a standardized method for websites and developers to make their content accessible and usable by AI agents.

NLWeb endpoints serve as Model Context Protocol (MCP) servers, allowing natural language interfaces to directly interact with website content. This enables users to engage with sites using conversational language, powered by the AI model of their choice and their own data. The result is a new generation of web experiences where AI agents can find, interpret, and act on information from the open web.

This initiative is closely linked to Microsoft’s broader push for MCP, a protocol it’s integrating across key platforms like GitHub, Copilot Studio, Azure AI Foundry, and Windows 11.

Both Microsoft and GitHub are part of the MCP Steering Committee and are contributing technical specifications and infrastructure to the ecosystem. New contributions include an updated authorization standard for securely granting agents access to data and services, as well as a registry service to publish and discover MCP-compatible endpoints.

Microsoft’s broader goal is to make agent development and deployment secure, interoperable, and standards-based, ensuring developers avoid vendor lock-in while gaining more control over how agents authenticate, retrieve, and communicate across the web.

This aligns with Microsoft’s vision of enhancing AI agent functionality through tools like Copilot Studio, GitHub Copilot, Azure AI Foundry, and Windows AI Foundry. These platforms now offer developers features for enterprise-grade governance, memory, reasoning, and trust, integrated with compliance tools like Microsoft Entra and Microsoft Purview.

With NLWeb and comprehensive MCP integration, Microsoft is betting that the next evolution of the internet will be driven by AI agents that are context-aware, secure, and capable of seamless real-time collaboration across digital ecosystems.

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