# codex Codex is an AI coding partner from OpenAI that completes software engineering tasks such as feature development, refactoring, migrations, testing, and code review. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## 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 ## 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. ## 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 ## Building Codex with Tibo Sottiaux DevFeed: [Building Codex with Tibo Sottiaux]() Original publisher: [Read original article]() Author: Gergely Orosz Published: 2026-09-09T15:57:24Z Content type: article Language: en Sources: [The Pragmatic Engineer]() Topics: [codex](), [OpenAI](), [Development](), [software-development](), [Command-line interface](), [Git]() Tags: [agentic](), [agents](), [cli](), [codex](), [git](), [openai](), [rust](), [software-development]() ### AI overview In a Pragmatic Engineer Podcast episode, OpenAI's Tibo Sottiaux discusses how Codex was built and iterated, including the Rust-based open-source CLI, evolving harness and models, support for multiple model providers, and use across software development tasks such as code reviews, maintenance, and system rearchitecture. ### Source excerpt OpenAI's Tibo Sottiaux shares how Codex was built and how it's reshaping software development. ## Some thoughts on the Navier-Stokes Millennium Prize Problem DevFeed: [Some thoughts on the Navier-Stokes Millennium Prize Problem]() Original publisher: [Read original article]() Author: Simon Willison Published: 2026-09-08T23:55:12Z Content type: opinion Language: en Sources: [Simon Willison](), [Simon Willison's Weblog]() Topics: [OpenAI](), [Mathematics](), [Claude](), [codex](), [Math and Logic](), [Lean]() Tags: [agents](), [ai](), [ai-2-235](), [ai-ethics](), [ai-ethics-342](), [claude](), [codex](), [generative-ai](), [generative-ai-1-981](), [llms](), [llms-1-947](), [mathematics](), [mathematics-22](), [openai](), [openai-463](), [paper](), [training-data](), [training-data-68]() ### AI overview This commentary examines OpenAI's reported resolution of the Navier-Stokes existence and smoothness problem with an unreleased model, alongside accusations that the effort may have drawn on information from related work by mathematicians using Claude and Codex. It also describes questions about timing, data access, authorship, and OpenAI's subsequent use of agents and Lean formalization. ### Source excerpt On the Navier-Stokes Millennium Prize Problem introduces an impressive result from OpenAI, who used an unreleased model to produce a resolution to the Navier-Stokes existence and smoothness problem, one of the seven Millennium Prize Problems that have been subject to a $1,000,000 prize since May 24th, 2000. The discovery is somewhat overshadowed by accusations of skulduggery from Tristan Buckmaster, an NYU mathematics professor who was collaborating on related problems with Levent Alpöge, an accomplished mathematician who currently works for Anthropic. Tristan's complaint accompanied a hastily published version of their own results. Here's the PDF describing what happened. The very short version is that Tristan and Levent worked on the problem for almost a year, making extensive use of Claude and Codex (mainly GPT-5.6 Sol), then had a breakthrough on August 15th. The mathematical rumour mill kicked into gear and Tristan and Levent heard that OpenAI had heard that Anthropic had resolved "a major open problem", so they reached out and learned that OpenAI had a team working on a related problem, with a similar approach. Quoting Tristan: I asked when the first prompt had been sent by them. This question was not answered directly by OpenAI for some time. Eventually it was agreed that it had been sent in the past few days, after information about our work had reached OpenAI. I asked whether the model had been trained on, or had access to, our sessions in Codex, into which we had been putting all our drafts for the whole of this project. I was told the model did not look up user data. I asked again, about training, and I did not get an answer. It gets more complicated from there. The OpenAI team offered to wait for Tristan to publish, or to have him author a paper about their result, but were clear that Levent would not be invited as a co-author due to OpenAI's competitive relationship with his employer. Here's how OpenAI described their work: On Tuesday, September 1, we h ## The Work Now Within Reach DevFeed: [The Work Now Within Reach]() Original publisher: [Read original article]() Published: 2026-09-08T13:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Artificial Intelligence](), [OpenAI](), [Software Engineering](), [API](), [ChatGPT](), [codex](), [Software]() Tags: [agentic](), [ai](), [api](), [applications](), [codex](), [company](), [developers](), [enterprise](), [openai]() ### AI overview OpenAI describes how more capable and affordable AI could expand the work that people and businesses can accomplish. It highlights GPT-6 Astra's capabilities, OpenAI's full-stack compute strategy, and the reinforcing relationship between research, products, infrastructure, revenue, and adoption. The article also discusses ChatGPT, ChatGPT Work, Codex, API applications, enterprise deployments, developers, and agentic products. ### Source excerpt Explore how more capable, affordable AI can expand the work people and businesses can accomplish--and make growth more economical. ## Review: Codex Tools for Improving Accessibility DevFeed: [Review: Codex Tools for Improving Accessibility]() Original publisher: [Read original article]() Author: Riley Collins Published: 2026-09-08T12:00:30Z Content type: opinion Language: en Sources: [Atomic Object]() Topics: [codex](), [Accessibility](), [Tooling]() Tags: [accessibility](), [codex](), [developer](), [developer-tools](), [review]() ### AI overview A software developer reviews Codex accessibility tools after breaking their wrist. The article focuses on dictation, describing how it transcribes speech into text for messages, emails, and prompts, while noting transcription errors and dictionary settings that can improve accuracy. ### Source excerpt Recently, I was met with a situation that you do not wish to run into as a software developer. I was playing a game of baseball, and due to a wild pitch, I broke my wrist. This resulted in being put into a cast (and for a moment a sling) that made it very difficult [...] The post Review: Codex Tools for Improving Accessibility appeared first on Atomic Spin. ## Home Hardware, Part 1: My Control4 Revenge Arc DevFeed: [Home Hardware, Part 1: My Control4 Revenge Arc]() Original publisher: [Read original article]() Published: 2026-09-08T00:34:58Z Content type: opinion Language: en Sources: [Jessie Frazelle]() Topics: [Home Assistant](), [Hardware](), [Bluetooth](), [Homekit](), [codex]() Tags: [api](), [bluetooth](), [codex](), [connect](), [hardware](), [home-assistant](), [homekit](), [sensor](), [sensors]() ### AI overview The author describes designing consumer hardware for a Home Assistant-based smart home, including a Bluetooth sensor hub and a maintenance display. The post discusses Bluetooth proxy range, regulatory constraints, testing considerations, and the use of NFC stickers for maintenance tracking, while reflecting on using Codex during the project. ### Source excerpt Fuck1 it, we're doing consumer hardware for ourselves now and getting fucked by economies of scale, I guess. This all started with me buying some Olimex Bluetooth proxies for Home Assistant. Then I started looking at the components and wondering if I could get better range. Now I'm designing boards, displays, and enclosures, and emailing manufacturers because their bezels are enormous. I've ordered the first two boards: a Bluetooth sensor hub and a little maintenance display. I've been working on this in Codex, and this post is going to go through what it was good at, where it got stuck or got things wrong, and where I had to step in. Why build this? Honestly, Control4, Savant, and the rest of these fucking systems seem built for rich people who don't know how to turn on their TV and would rather call someone. I want to program the fucking thing. Control4 puts HomeKit integration in its paid Connect tier.2 Why am I paying a recurring fee to connect things I already bought? I don't want to call a Control4 or Savant dealer, either, just because I want to change how something works. Give me API access or give me death. Source works too. I'll pick the hardware and connect it to Home Assistant, HomeKit, or my own code. If I want another sensor or some weird maintenance reminder, I can write that. It's my fucking house.31 Back to the Bluetooth proxies With a Bluetooth proxy, I can put the BLE radio near the sensors and get back to Home Assistant over the network.4 The machine running Home Assistant doesn't have to be within range of every sensor. When I mentioned my plans to Paul (paultag) over Slack, he pointed out that Olimex might be constrained by what the FCC allows, not just the components it picked. A radio supporting more transmit power doesn't mean you can use all of it.5 I hadn't thought about that. These are boards for my house. I'm not selling them. Fuck it, I'll build them and test them. I still have to measure the range; a bigger number on the radio's datash ## The iOS Simulator Inside Cursor, Claude Code, and Codex DevFeed: [The iOS Simulator Inside Cursor, Claude Code, and Codex]() Original publisher: [Read original article]() Author: Antoine van der Lee Published: 2026-09-07T13:07:15Z Content type: opinion Language: en Sources: [SwiftLee]() Topics: [iOS](), [cursor](), [Claude Code](), [codex](), [App](), [Tooling]() Tags: [agent](), [agent-skills](), [ai-development](), [app-development](), [claude-code](), [codex](), [cursor](), [developer-tools](), [ios]() ### AI overview An opinion article examines how the iOS Simulator is becoming integrated into Cursor, Claude Code, and Codex as app development shifts toward orchestrating AI agents. It argues that visual testing, performance review, and critical human validation remain essential, and describes AI Agents for the iOS Simulator as a way to automate navigation and validation within the developer workflow. ### Source excerpt App development is changing, and the iOS Simulator is too, as it starts to appear in Cursor, Claude Code, and Codex in different ways. I've been developing apps since 2009 and the RocketSim developer tool since 2019, and I can tell we're reinventing ourselves like never before. I also started to wonder: what is the ... -> The post The iOS Simulator Inside Cursor, Claude Code, and Codex appeared first on SwiftLee. ## When your Codex allowance runs out, use an API key instead of credits DevFeed: [When your Codex allowance runs out, use an API key instead of credits]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-04T15:35:41Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [codex](), [API](), [API keys](), [OpenAI]() Tags: [api](), [codex](), [openai]() ### AI overview The article argues that Codex extra credits use the same published token rates as the OpenAI API, while a benchmark found the credit lane was 1.5 times slower than the API at indistinguishable quality. It reports a blinded comparison of API-key and Codex subscription access, with nearly identical quality scores and no blockers in either arm. ### Source excerpt Codex extra credits price out to exact API list rates, and we measured the credit lane 1.5x slower at quality we couldn't tell apart. Overflow to the API. ## Hands-on GPT-6 Astra review covering computer use, coding, hardware, Blender, and desktop app projects DevFeed: [Hands-on GPT-6 Astra review covering computer use, coding, hardware, Blender, and desktop app projects]() Original publisher: [Read original article]() Author: Claire Vo Published: 2026-09-03T19:34:20Z Content type: opinion Language: en Sources: [Lenny's Newsletter]() Topics: [gpt-6-astra](), [Artificial Intelligence](), [computer-use](), [coding](), [blender](), [Figma](), [codex]() Tags: [ai](), [blender](), [codex](), [coding](), [computer-use](), [figma](), [gpt-6-astra]() ### AI overview A hands-on review of GPT-6 Astra covering computer use, browser-based QA, coding projects, a hardware hack, Blender 3D asset creation, and a Mac app. The episode also discusses speed, cost, and whether Astra is suitable as a daily driver. ### Source excerpt Watch now | 🎙 My hands-on GPT-6 Astra review covers real production work in Figma, Flora, and Adio, one-shot coding wins 5.6 and Fable couldn't match, and a hardware hack I've chased for months ## Encore now works with Entire DevFeed: [Encore now works with Entire]() Original publisher: [Read original article]() Author: Ivan Cernja Published: 2026-09-02T00:00:00Z Content type: tutorial Language: en Sources: [Encore Updates]() Topics: [AI-assisted coding](), [codex](), [Claude Code](), [coding](), [Git](), [cursor](), [PostgreSQL]() Tags: [claude-code](), [codex](), [coding](), [coding-agents](), [cursor](), [git](), [object-storage](), [postgresql]() ### AI overview Encore now works with Entire, allowing developers to use Codex, Claude Code, Gemini, and Cursor in Encore projects while recording agent sessions in Git and linking them to commits. The article demonstrates building and testing an image service with local PostgreSQL and object storage, including integration tests and a live upload/download verification. ### Source excerpt Keep the agent session behind every Encore change, directly in Git. ## Using Six Scoped Subagents to Manage Context Windows DevFeed: [Using Six Scoped Subagents to Manage Context Windows]() Original publisher: [Read original article]() Author: Paul Iusztin Published: 2026-09-01T05:00:29Z Content type: tutorial Language: en Sources: [Decoding ML]() Topics: [context window](), [long-context](), [Artificial Intelligence](), [Code](), [coding](), [Claude](), [Claude Code](), [codex](), [LangChain](), [Python](), [Cloud]() Tags: [agent](), [agents](), [ai](), [claude](), [claude-code](), [cloud](), [codex](), [coding](), [coding-agents](), [context-engineering](), [context-window](), [langchain](), [python]() ### AI overview This tutorial explains how splitting research work among six parallel subagents can reduce context-window noise and limit the state returned to an orchestrator agent. It also covers designing subagent protocols, maintaining an agent registry, and running parallel agent workflows. ### Source excerpt The harness determines what your orchestrator agent never sees, not the model. ## Omnigent: A Meta-Harness for Coding Agents DevFeed: [Omnigent: A Meta-Harness for Coding Agents]() Original publisher: [Read original article]() Author: Daniel Beach Published: 2026-08-31T12:04:20Z Content type: opinion Language: en Sources: [Data Engineering Central]() Topics: [Artificial Intelligence](), [AI-assisted coding](), [Claude Code](), [codex](), [Model Context Protocol]() Tags: [agents](), [bash](), [claude-code](), [codex](), [coding-agents](), [cursor](), [mcp]() ### AI overview The author introduces Omnigent as a meta-harness for agents while discussing the overload of coding-agent tools, configurations, plugins, MCP servers, and Bash-command controls. ### Source excerpt I got you boo ## AI's third era: the rise of persistent AI coworkers | Tara Seshan (Product Lead ChatGPT Work) DevFeed: [AI's third era: the rise of persistent AI coworkers | Tara Seshan (Product Lead ChatGPT Work)]() Original publisher: [Read original article]() Author: Lenny Rachitsky Published: 2026-08-30T12:31:30Z Content type: opinion Language: en Sources: [Lenny's Newsletter]() Topics: [Artificial Intelligence](), [codex](), [ChatGPT](), [OpenAI]() Tags: [ai](), [chatgpt](), [codex](), [openai]() ### AI overview A podcast discussion with Tara Seshan, head of Codex and ChatGPT Work at OpenAI, about persistent AI coworkers, ambition as a differentiator, steering versus rowing, and building for expected model progress over the next two to three months. ### Source excerpt Listen now | Tara Seshan, head of Codex and ChatGPT Work at OpenAI, on why ambition is now the differentiator, steering vs. rowing, and why you need to build for where the models will be in two to three months ## AI-assisted migration from Enzyme to React Testing Library DevFeed: [AI-assisted migration from Enzyme to React Testing Library]() Original publisher: [Read original article]() Author: Ivan Klaric Published: 2026-08-27T18:04:54Z Content type: article Language: en Sources: [The Pragmatic Engineer]() Topics: [Testing](), [migration](), [testing-library](), [Artificial Intelligence](), [OpenAI](), [codex](), [React Native]() Tags: [ai](), [codex](), [migration](), [migrations](), [openai](), [react](), [testing](), [testing-library]() ### AI overview The article examines Asana's migration from Enzyme to React Testing Library and discusses how AI-assisted coding, including OpenAI Codex, may make large testing-system migrations more practical. It compares the different testing approaches and syntax used by the two libraries. ### Source excerpt Asana migrated off testing framework Enzyme in two weeks: without AI, this work would surely have been kicked down the road. Airbnb and Uber share similar stories and AI seems excellent at migrations. ## How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents DevFeed: [How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-08-26T20:05:06Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Artificial Intelligence](), [Reinforcement learning](), [codex](), [coding](), [Simulation and Design](), [CUDA]() Tags: [agent](), [agentic-ai-generative-ai](), [ai](), [ai-agent](), [ai-agents](), [architecture](), [codex](), [coding](), [cuda](), [development](), [evaluation](), [framework](), [nvidia](), [omniverse](), [physical-ai](), [reinforcement-learning](), [robotics](), [simulation-modeling-design](), [skills](), [testing](), [training](), [tutorial](), [workflow]() ### AI overview This tutorial presents an agent-driven COMPASS workflow for training and evaluating cross-embodiment robot navigation policies. It covers asset preparation, smoke testing, residual reinforcement learning, checkpoint evaluation, runtime integration, and optional reconstructed environments using NVIDIA Omniverse NuRec. ### Source excerpt Navigation enables a robot to turn perception and motion into purposeful autonomy. Unlike locomotion, which produces stable movement, navigation must be used to... ## How loveholidays is making everyone a builder with Codex DevFeed: [How loveholidays is making everyone a builder with Codex]() Original publisher: [Read original article]() Published: 2026-08-26T00:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [codex](), [OpenAI](), [AI Development](), [Code](), [Software Engineering](), [Deployment](), [Front end]() Tags: [ai](), [building](), [code](), [codex](), [deployment](), [frontend](), [openai](), [software-development]() ### AI overview loveholidays uses OpenAI Codex to broaden software development beyond engineering, enabling product, design, and commercial teams to contribute code, infrastructure changes, experiments, and deployments. The article highlights growth in AI-assisted code changes and deployment frequency, alongside improvements to its Data Platform and the creation of Search Playground. ### Source excerpt Discover how loveholidays uses OpenAI Codex to make software development accessible across the business, helping teams turn ideas into products faster. [Next page]()