# codex Published articles for codex. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Muse review: The personal AI agent that gets consumer UX right DevFeed: [Muse review: The personal AI agent that gets consumer UX right]() Original publisher: [Read original article]() Author: Claire Vo Published: 2026-09-16T12:02:14Z Content type: opinion Language: en Sources: [Lenny's Newsletter]() Topics: [AI Agent](), [User experience (UX)](), [Meta](), [browser](), [pdf](), [codex]() Tags: [agent](), [ai](), [ai-agent](), [browser](), [codex](), [comparison](), [meta](), [muse](), [pdf](), [product-design](), [ux]() ### AI overview This review tests Meta's Muse personal AI agent through onboarding, calendar management, goal setting, document generation, and browser-based shopping. It finds strong consumer UX, permission handling, activity-feed design, and avatar design, while browser shopping performance is mixed. ### Source excerpt Watch now (38 mins) | 🎙 I gave Meta's Muse my calendar, my email, and my kids' chaotic schedule, and it produced a one-shot family PDF more beautiful than anything I've ever made with Claude or Codex ## How to connect AI usage to business value DevFeed: [How to connect AI usage to business value]() Original publisher: [Read original article]() Published: 2026-09-16T12:00:00Z Content type: tutorial Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [ChatGPT](), [codex](), [data](), [Software Engineering]() Tags: [ai](), [analytics](), [business-value](), [chatgpt](), [codex](), [product](), [training]() ### AI overview This tutorial explains how ChatGPT Work and Codex analytics help administrators connect AI adoption, usage, spending, supported tasks, and outcomes to business decisions. It covers views for identifying training needs, evaluating workflows, reviewing model and tool usage, and monitoring Codex contributions and code-review activity. ### Source excerpt Learn how ChatGPT Work and Codex analytics help teams understand AI usage and spend, identify training needs, and connect adoption to business outcomes. ## Meta lets Claude and Codex configure WhatsApp Business via MCP DevFeed: [Meta lets Claude and Codex configure WhatsApp Business via MCP]() Original publisher: [Read original article]() Author: Paul Sawers Published: 2026-09-15T22:08:56Z Content type: news Language: en Sources: [The New Stack]() Topics: [Meta](), [Model Context Protocol](), [AI-assisted coding](), [Claude](), [codex](), [API]() Tags: [ai](), [ai-agents](), [ai-coding-agents](), [api](), [claude](), [codex](), [developer-tools](), [mcp](), [mcp-server](), [meta](), [model-context-protocol](), [product](), [updates]() ### AI overview Meta announced a WhatsApp Business Tools MCP server that lets developers connect Claude or Codex to selected businesses they administer. The agents can help configure WhatsApp Business accounts, verify phone numbers, manage templates, and perform related API tasks, with access scoped to the businesses the developer selects. ### Source excerpt Any business worth its salt in 2026 needs to be embracing the right tools to reach its customers, and few The post Meta lets Claude and Codex configure WhatsApp Business via MCP appeared first on The New Stack. ## Inside OpenAI's agentic software factory DevFeed: [Inside OpenAI's agentic software factory]() Original publisher: [Read original article]() Author: Gergely Orosz Published: 2026-09-15T15:41:25Z Content type: article Language: en Sources: [The Pragmatic Engineer]() Topics: [OpenAI](), [codex](), [Software](), [coding]() Tags: [agentic](), [codex](), [engineering](), [openai](), [software]() ### AI overview This article examines Codex's role at OpenAI, the lab's agentic software factory, and the engineering challenges associated with serving one billion users. ### Source excerpt A deepdive into how Codex has "taken over" OpenAI, how the frontier lab builds its agentic software factory, and the engineering challenges of one billion users. Details from inside OpenAI ## How to Run Codex in an Ubuntu Virtual Machine on Proxmox DevFeed: [How to Run Codex in an Ubuntu Virtual Machine on Proxmox]() Original publisher: [Read original article]() Author: Travis Henderson Published: 2026-09-15T12:00:11Z Content type: tutorial Language: en Sources: [Atomic Object]() Topics: [AI-assisted coding](), [codex](), [Linux](), [Ubuntu](), [Proxmox](), [OpenSSH](), [Authorization]() Tags: [ai-agent](), [ai-for-developers](), [codex](), [coding-agents](), [development](), [linux](), [openssh](), [permissions](), [proxmox](), [sandbox](), [ubuntu]() ### AI overview This guide explains how to isolate Codex in a headless Ubuntu virtual machine running on Proxmox, using a separate Linux account and OpenSSH. The setup limits the files, dependencies, and network access available to the agent while keeping administrator tasks separate, but it does not eliminate risks from credentials, network access, or mistakes pushed to GitHub. ### Source excerpt The more useful coding agents become, the more access they tend to need. Installing dependencies, running commands, changing files, and generally more autonomy are part of the appeal. They're also the point where I start thinking about what else the coding agent can reach, especially while these tools are changing so quickly. My answer is [...] The post Your Coding Agent Should be in Jail. Here's Why and How. appeared first on Atomic Spin. ## AI's best coding agent fails 60% of the time -- and the data backs it up DevFeed: [AI's best coding agent fails 60% of the time -- and the data backs it up]() Original publisher: [Read original article]() Author: Amanda Caswell Published: 2026-09-14T22:22:27Z Content type: news Language: en Sources: [The New Stack]() Topics: [Benchmark](), [AI-assisted coding](), [Fable](), [Claude Code](), [codex](), [Command-line interface](), [anthropic]() Tags: [ai](), [ai-engineering](), [ai-models](), [benchmark](), [benchmarks](), [claude-code](), [cli](), [codex](), [coding](), [fable](), [performance](), [software-testing]() ### AI overview Real-SWE evaluates coding agents on private company codebases and reports substantially lower success rates than public-repository benchmarks. Claude Fable 5.1, running through Claude Code, led the comparison with a 38.8% score, while the tested systems often failed most attempts. ### Source excerpt Claude Fable 5.1 just won a new coding benchmark despite failing more than six out of 10 times. Its 38.8% The post AI's best coding agent fails 60% of the time -- and the data backs it up appeared first on The New Stack. ## AI SDK harness layer now supports native subscription authentication DevFeed: [AI SDK harness layer now supports native subscription authentication]() Original publisher: [Read original article]() Author: Felix Arntz Published: 2026-09-14T21:28:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [vercel ai sdk](), [Authentication](), [OAuth](), [codex](), [Claude Code]() Tags: [ai](), [authentication](), [claude-code](), [codex](), [coding-agents](), [copilot](), [cursor](), [gateway](), [oauth](), [opencode](), [sdk]() ### AI overview The AI SDK harness layer now supports authenticating supported coding-agent harnesses through their native subscriptions. It uses explicit provider credentials when available, otherwise falls back to a host-native subscription without requiring code or configuration changes. ### Source excerpt The AI SDK harness layer now supports authenticating harnesses through their native subscriptions, where the underlying harness supports them. The harness layer runs different coding agents through the same HarnessAgent interface, so you can switch agents without changing your application code. No code changes or new settings are required. The direct authentication mode uses explicit provider environment credentials when they are present, and otherwise a native subscription found on the host. The default auto mode does the same when no AI Gateway credentials are set. The ai-gateway mode never reads native subscriptions. Native subscription credentials stay on the host. Just like with API keys, credentials are resolved at the host boundary. OAuth access tokens are refreshed there as needed. Where the sandbox supports it, the harness receives placeholder credentials and the real token is injected into outbound requests on the host. Native subscriptions work across harness adapters wherever the harness itself supports subscription login. These include Claude Code, Cline, Codex, Cursor, fx, GitHub Copilot, Grok Build, OpenCode, and Pi. Read the harness documentation to learn more. Read more ## Inside the LLM Call: GenAI Observability with OpenTelemetry DevFeed: [Inside the LLM Call: GenAI Observability with OpenTelemetry]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-09-14T16:56:42Z Content type: tutorial Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [agent observability](), [telemetry](), [AI Agent](), [Large Language Model]() Tags: [agent](), [ai-agent](), [claude-code](), [codex](), [observability](), [opentelemetry](), [token](), [tool](), [visibility]() ### AI overview This tutorial explains how OpenTelemetry Semantic Conventions for Generative AI record LLM calls, tool invocations, token counts, and related events. It demonstrates exporting telemetry from an LLM-powered application, viewing it with Aspire Dashboard, and considering sensitive-data implications of optional content capture. ### Source excerpt Your AI agent just took 45 seconds to answer a simple question. Was it the model? A slow tool call? A retry loop? Every time an application calls an LLM, a chain of model calls, tool invocations, and token exchanges happens behind the scenes -- and without observability, you are guessing. The OpenTelemetry Semantic Conventions for Generative AI give you that visibility. They standardize how GenAI operations are recorded -- the model being called, input and output token counts, and when opted in, the full content of prompts, completions, tool calls, and tool results. ## AWS Weekly Roundup: OpenAI GPT-6 Astra on Amazon Bedrock, Amazon Quick desktop GA, Kiro for students, and more (September 14, 2026) DevFeed: [AWS Weekly Roundup: OpenAI GPT-6 Astra on Amazon Bedrock, Amazon Quick desktop GA, Kiro for students, and more (September 14, 2026)]() Original publisher: [Read original article]() Author: Micah Walter Published: 2026-09-14T15:56:33Z Content type: news Language: en Sources: [AWS News Blog]() Topics: [Amazon Bedrock](), [Frontier Model](), [OpenAI](), [context window](), [browser](), [ChatGPT](), [codex](), [macOS](), [Windows](), [Mobile]() Tags: [agents](), [ai](), [ai-agents](), [amazon](), [amazon-bedrock](), [amazon-elastic-block-store-amazon-ebs](), [amazon-opensearch-service](), [amazon-quick-suite](), [aws](), [aws-lambda](), [aws-outposts](), [aws-transform](), [bedrock](), [browser](), [chatgpt](), [codex](), [context-window](), [frontier-model](), [google-play](), [gpt](), [kiro](), [launch](), [macos](), [mobile](), [openai](), [week-in-review](), [windows]() ### AI overview This AWS Weekly Roundup highlights the general availability of OpenAI GPT-6 Astra on Amazon Bedrock, describing its reasoning, writing, design, computer-use, browser-use, and million-token context-window capabilities. It also covers the Amazon Quick desktop app for macOS and Windows, including synchronized conversations and agents across desktop and mobile, plus other AWS launches and updates. ### Source excerpt There's a particular energy to mid-September in New York. Pumpkin spice lattes are flowing, temperatures are dropping, and it's nearly sweater weather. The city is back at full speed, and so is the AWS launch calendar. This week that energy showed up in a new frontier model on Amazon Bedrock, a desktop app for Amazon [...] ## I Had Never Built A VR App - 8 Days Later, Mine Was On The Quest Store DevFeed: [I Had Never Built A VR App - 8 Days Later, Mine Was On The Quest Store]() Original publisher: [Read original article]() Author: Craig Storm Published: 2026-09-14T15:12:36Z Content type: article Language: en Sources: [UploadVR]() Topics: [ai-coding](), [codex](), [ChatGPT](), [coding](), [Code](), [App](), [Meta](), [APK](), [SDKs]() Tags: [ai](), [ai-coding](), [apk](), [app](), [app-development](), [chatgpt](), [code](), [codex](), [coding](), [meta](), [openxr](), [sdk]() ### AI overview The article describes an eight-day attempt to build and publish Punchable Face, a simple VR game for Meta Quest, despite having little prior development experience. Using Unity, OpenXR, Meta XR SDK components, ChatGPT, and Codex, the project progressed from an empty Unity project through coding, headset testing, store asset creation, submission, and approval on the Meta Quest Store. ### Source excerpt Until a little over a week ago, Craig Storm had never built a VR app. Eight days later, his AI-assisted Quest game Punchable Face was live on Meta's store. ## Deploy, Discover, Inspect, Observe: A Summer Spent Making a Public Vespa MCP Server DevFeed: [Deploy, Discover, Inspect, Observe: A Summer Spent Making a Public Vespa MCP Server]() Original publisher: [Read original article]() Author: eivinbingen oystein viktor mfstort Published: 2026-09-13T00:00:00Z Content type: article Language: en Sources: [Vespa Blog]() Topics: [Model Context Protocol (MCP)](), [MCP Server](), [Cloud](), [AI Agent](), [Large Language Model](), [Command-line interface]() Tags: [ai-agent](), [ai-assistants](), [claude](), [cli](), [cloud](), [codex](), [internships](), [language-models](), [mcp](), [mcp-server]() ### AI overview This article describes the construction of a standalone, publicly hosted Vespa Cloud MCP server. It explains how MCP connects AI assistants and language models to external systems through resources, tools, and prompts, and discusses evaluating MCP usage against terminal access and Vespa CLI access. ### Source excerpt We built a standalone Vespa Cloud MCP server as a summer interns project ## "Same mission, bigger stage": OpenAI hires Git AI founders to help Codex prove its ROI DevFeed: ["Same mission, bigger stage": OpenAI hires Git AI founders to help Codex prove its ROI]() Original publisher: [Read original article]() Author: Paul Sawers Published: 2026-09-12T14:46:53Z Content type: news Language: en Sources: [The New Stack]() Topics: [ai observability](), [cursor]() Tags: [ai](), [ai-agents](), [ai-coding](), [codex](), [cost](), [cursor](), [developer-tools](), [git](), [open-source](), [openai]() ### AI overview OpenAI hired Git AI's founders to help measure the performance, cost, and return on investment of Codex and other AI coding tools. ### Source excerpt OpenAI has hired the founders of Git AI, an open-source tool that tracks how much code is written by AI The post "Same mission, bigger stage": OpenAI hires Git AI founders to help Codex prove its ROI appeared first on The New Stack. ## CrowdStrike Extends Endpoint Security to Stop Software Supply Chain Attacks DevFeed: [CrowdStrike Extends Endpoint Security to Stop Software Supply Chain Attacks]() Original publisher: [Read original article]() Author: Anne Aarness - Chris Prall Published: 2026-09-12T11:17:51.295154Z Content type: article Language: en Sources: [Blog]() Topics: [Endpoint Security & XDR](), [supply-chain-security](), [Security](), [Open Source](), [Software](), [Artificial Intelligence](), [Claude](), [codex]() Tags: [agentic](), [ai](), [codex](), [credential-theft](), [developer](), [developers](), [development](), [endpoint-security-xdr](), [malicious-packages](), [open-source](), [open-source-packages](), [persistence](), [security](), [software-supply-chain](), [supply-chain]() ### AI overview The article describes CrowdStrike's Real-Time Supply Chain Attack Protection, embedded in the Falcon sensor, which detects and blocks malicious open-source packages before their code executes on enterprise endpoints. It explains how AI-assisted and agentic applications have expanded software supply chain risk beyond developer workstations to endpoints across the organization. ### Source excerpt Real-Time Supply Chain Attack Protection, embedded into the Falcon sensor, blocks malicious open-source packages at download to protect the endpoint. ## Visual Studio Code 1.138 (Insiders) DevFeed: [Visual Studio Code 1.138 (Insiders)]() Original publisher: [Read original article]() Author: Visual Studio Code Team Published: 2026-09-12T11:03:34.159469Z Content type: release Language: en Sources: [Visual Studio Code - Code Editing. Redefined.]() Topics: [Visual Studio Code](), [releases](), [SDKs]() Tags: [agents](), [codex](), [release](), [release-notes](), [sandbox](), [vs-code]() ### AI overview Visual Studio Code 1.138 Insiders adds improvements to Agent Host sessions, including shareable links, adjacent sessions, repository context, voice awareness, SDK setup recovery, sandbox-policy consistency, and session cleanup controls. ### Source excerpt Learn what's new in Visual Studio Code 1.138 (Insiders) Read the full article ## OpenAI's researchers burned $7,000 a day on AI agents -- now it's opening the floodgates DevFeed: [OpenAI's researchers burned $7,000 a day on AI agents -- now it's opening the floodgates]() Original publisher: [Read original article]() Author: Amanda Caswell Published: 2026-09-11T21:27:42Z Content type: news Language: en Sources: [The New Stack]() Topics: [Inference](), [long-context]() Tags: [agents](), [ai](), [ai-agents](), [ai-infrastructure](), [api](), [cloud-services](), [codex](), [compute](), [developers](), [inference](), [openai](), [research](), [sandbox](), [tools]() ### AI overview OpenAI's public-beta Agents API lets developers run long-lived agents with managed job state, context compression, optional tools, parallel subagents, and execution in OpenAI's sandbox or developer-controlled infrastructure. The article highlights the resulting inference and compute costs, citing internal research-agent usage figures. ### Source excerpt OpenAI rolled out its Agents API in public beta Thursday, opening the backend behind Codex to developers looking to run The post OpenAI's researchers burned $7,000 a day on AI agents -- now it's opening the floodgates appeared first on The New Stack. ## Put Redis data and engineering guidance to work in ChatGPT Work DevFeed: [Put Redis data and engineering guidance to work in ChatGPT Work]() Original publisher: [Read original article]() Author: Olga Lopaci Published: 2026-09-11T00:00:00Z Content type: release Language: en Sources: [Redis Blog]() Topics: [Developer Tools](), [AI Chat](), [AI Bots]() Tags: [agent-skills](), [chatgpt](), [codex](), [engineering](), [observability](), [rag](), [redis](), [review](), [security](), [skills](), [tech](), [work]() ### AI overview Redis launched a development plugin for ChatGPT Work and Codex that supplies current Redis guidance for writing, reviewing, and troubleshooting code. It also describes connecting Redis data to ChatGPT Work's Data agent for plain-language exploration and investigation. ### Source excerpt Redis has launched a development plugin that brings current Redis engineering guidance into ChatGPT Work and Codex. It helps teams write, review, and troubleshoot Redis code without switching between documentation and development tools. Alongside Ope... ## OpenAI Releases GPT-6 Astra for Coding and Computer Use DevFeed: [OpenAI Releases GPT-6 Astra for Coding and Computer Use]() Original publisher: [Read original article]() Author: Daniel Dominguez Published: 2026-09-10T17:49:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [releases](), [AI-assisted coding](), [AI Bots](), [Vulnerabilities](), [SDKs]() Tags: [agent](), [agentic](), [agents](), [ai](), [ai-ml-data-engineering](), [anthropic](), [api](), [artificial-intelligence](), [chatgpt](), [codex](), [coding](), [computer-use](), [cybersecurity](), [evaluation](), [gpt](), [large-language-models](), [ml-data-engineering](), [news](), [openai](), [openai-gpt6-astra](), [releases](), [vulnerabilities]() ### AI overview OpenAI released GPT-6 Astra, a model for computer use, coding, multi-step software tasks, and cybersecurity. The article reports benchmark results, long-context and Codex context features, deployment availability, and safety restrictions for advanced offensive cybersecurity tasks. ### Source excerpt OpenAI has released GPT-6 Astra, a new model focused on coding, computer use, long-running agentic tasks, and cybersecurity, with availability across ChatGPT, Codex, and the OpenAI API. By Daniel Dominguez ## GitHub Copilot is now available in the AI SDK harness layer DevFeed: [GitHub Copilot is now available in the AI SDK harness layer]() Original publisher: [Read original article]() Author: Felix Arntz Published: 2026-09-10T17:39:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [GitHub Copilot](), [vercel ai sdk](), [AI-assisted coding](), [cursor]() Tags: [agent](), [ai](), [claude](), [claude-code](), [code](), [codex](), [coding](), [copilot](), [cursor](), [github](), [github-copilot]() ### AI overview The AI SDK harness layer adds official GitHub Copilot support through an adapter, allowing applications to run Copilot and other coding agents through the same HarnessAgent interface. ### Source excerpt The AI SDK harness layer now supports GitHub Copilot through the official @ai-sdk/harness-github-copilot adapter. The harness layer lets your application run different coding agents through the same HarnessAgent interface, so you can switch agents without changing your application code. Pass githubCopilot to HarnessAgent: Under the hood, the adapter uses @ai-sdk/harness-acp to connect GitHub Copilot to HarnessAgent through the Agent Client Protocol (ACP). Supported harnesses now include, in addition to GitHub Copilot, Claude Code, Cline, Codex, Cursor, Deep Agents, fx, Grok Build, OpenCode, and Pi, with more coming soon. Read the GitHub Copilot harness documentation to get started. Read more ## How a researcher uses Codex and ChatGPT to search for new antimicrobial molecules DevFeed: [How a researcher uses Codex and ChatGPT to search for new antimicrobial molecules]() Original publisher: [Read original article]() Published: 2026-09-10T16:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Deep neural networks](), [datasets](), [Code]() Tags: [ai](), [ai-models](), [antibiotics](), [applied-ai](), [chatgpt](), [code](), [codex](), [datasets](), [deep-learning](), [search]() ### AI overview César de la Fuente's lab uses deep-learning models, ChatGPT, and Codex to search genome and protein datasets for antimicrobial candidates that could help fight drug-resistant infections. ### Source excerpt César de la Fuente's lab uses Codex and ChatGPT to search living and extinct genomes for antimicrobial candidates to fight drug-resistant infections. ## ClickHouse is a launch partner for the Data agent in ChatGPT Work DevFeed: [ClickHouse is a launch partner for the Data agent in ChatGPT Work]() Original publisher: [Read original article]() Author: Aditya Chidurala; Teresa Blanco Published: 2026-09-10T15:13:26Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [AI Chat](), [dashboards](), [AI Bots]() Tags: [agent](), [agent-skills](), [analytics](), [chatgpt](), [clickhouse](), [codex](), [dashboards](), [mcp](), [mcp-server](), [oauth]() ### AI overview ClickHouse announces a ChatGPT Work plugin that connects ClickHouse Cloud through OAuth for natural-language data exploration, reports, and interactive dashboards. ### Source excerpt ClickHouse joins the Data agent in ChatGPT Work, connecting ClickHouse Cloud to natural-language queries, reports, and interactive dashboards. ## Why I think we should write our own PR descriptions DevFeed: [Why I think we should write our own PR descriptions]() Original publisher: [Read original article]() Author: Ryan Chandler Published: 2026-09-10T12:15:00Z Content type: opinion Language: en Sources: [Laravel Blog]() Topics: [AI Bots](), [AI Chat]() Tags: [agents](), [claude](), [codex](), [developers](), [pull-request](), [review](), [writing]() ### AI overview The article argues that developers should write their own pull request descriptions even when AI agents implement most of a change. Writing serves as a checkpoint for understanding the change and gives reviewers human context beyond an agent-generated diff summary. ### Source excerpt Agents can write your PR descriptions, but they shouldn't. Here's why writing them yourself makes you a better engineer and a better teammate. ## How to Move an AI App from a Frontier Model to Open Weights DevFeed: [How to Move an AI App from a Frontier Model to Open Weights]() Original publisher: [Read original article]() Author: Gus Schissler Published: 2026-09-10T12:00:43Z Content type: tutorial Language: en Sources: [Atomic Object]() Topics: [Artificial Intelligence](), [Large Language Model](), [Benchmark](), [inference-providers](), [codex]() Tags: [ai](), [ai-for-developers](), [benchmark](), [codex](), [how-to](), [inference](), [inference-providers](), [llm](), [prototyping]() ### AI overview This tutorial describes moving an AI document-processing prototype from a frontier model to cheaper open-weight models through hosted inference providers. It explains how to define a trusted gold set from real project outputs and use workflow-specific evaluation to identify where lower-cost models fail. ### Source excerpt At Atomic Object, we're encouraged to prototype and dogfood internal projects. Over the last four months, I've been building a prototype to help solve a part of my job that I dislike. The first version used an LLM to extract and classify information from documents, then connect related pieces so humans and agents could retrieve [...] The post How to Move an AI App from a Frontier Model to Open Weights appeared first on Atomic Spin. ## Understanding RF Trace Impedance in a KiCad Sensor Hub PCB DevFeed: [Understanding RF Trace Impedance in a KiCad Sensor Hub PCB]() Original publisher: [Read original article]() Published: 2026-09-10T03:45:45Z Content type: article Language: en Sources: [Jessie Frazelle]() Topics: [Hardware](), [kicad](), [codex]() Tags: [codex](), [hardware](), [kicad](), [pcb]() ### AI overview The article explains how the author resolved differing impedance calculations for a Sensor Hub's RF layout. It shows that both inner PCB layers contained ground copper, and that the RF trace's reference plane, dielectric thickness, copper thickness, and adjacent ground gap affect the 50-ohm impedance calculation. ### Source excerpt We're back! Not with rework. This time we're talking about impedance and review. Apparently I can get into a heated argument about a board before it even gets here. In part one, I wrote about using Codex to design my own hardware because I'm sick of Control4, Savant, and the rest of that shit. The useful part wasn't one-shotting a PCB. It was having the agent work through datasheets, compare parts, and check the design. Then I had to notice that the connectors were facing the wrong fucking way. There was more to review. Which board are we arguing about? I was talking through the Sensor Hub's RF layout with Paul, and we were getting different answers for the impedance. This turned into a pretty heated argument, which might have scared some of the other people in the room. Honestly, we were just trying to figure it out. Paul started with this impedance calculator. I kept annoying him because I still didn't understand why we were getting different numbers. Eventually he switched to JLC's calculator, which was what the model was using. I wanted to understand the model's math and compare it with his. The KiCad view was part of the confusion. The connection looked orange, and the second interior layer, In2.Cu, was orange in the layer list. The first interior layer, In1.Cu, was green. So we thought ground was on the second one, and kept arguing about the thickness between layers. Then I realized both interior layers had ground copper, with ground vias connecting across layers. Seeing orange didn't mean the connection was only on that layer. There was ground on the green layer too, right under the RF trace. The model was right! I was just trying to understand what it was telling me. The confusing view, recreated in KiCad. In2.Cu is selected in orange; the green In1.Cu ground is there too. The RF trace is on F.Cu, the top layer. There is 0.1164 mm of insulating material between it and the first inner ground plane. If we used the second inner layer as the reference, we'd be i ## Introducing the Agents API DevFeed: [Introducing the Agents API]() Original publisher: [Read original article]() Published: 2026-09-10T00:00:00Z Content type: release Language: en Sources: [OpenAI News]() Topics: [AI Bots]() Tags: [agents](), [api](), [cloud](), [codex](), [developers](), [infrastructure](), [launch](), [orchestration](), [product](), [sandbox](), [tool]() ### AI overview OpenAI introduces the Agents API in public beta, providing a managed harness and infrastructure for building production-ready, long-running agents with tools and configurable compute environments. ### Source excerpt Build and launch cloud agents with the Agents API, a managed service powered by the Codex harness for orchestration, long-running sessions, and tool use. [Next page]()