OpenAI has shipped a Chrome extension for Codex, its AI coding agent, enabling it to complete browser-based tasks directly inside Google Chrome on macOS and Windows — including interacting with signed-in websites, using Chrome DevTools, and running multi-step workflows across browser tabs.
The post OpenAI Adds Chrome Extension to Codex, Letting Its AI Agent Access LinkedIn, Salesforce, Gmail, and Internal Tools via Signed-In Sessions appeared first on MarkTechPost.
How OpenAI runs Codex securely with sandboxing, approvals, network policies, and agent-native telemetry to support safe and compliant coding agent adoption.
How hook implementation gives Claude Code, Codex, and Cursor persistent memory via Neo4j, without locking you into any one of them.
The post Unified Agentic Memory Across Harnesses Using Hooks appeared first on Towards Data Science.
Inference efficiency has quietly become one of the most consequential bottlenecks in AI deployment. As agentic coding systems such as Claude Code, Codex, and Cursor scale from developer tools to infrastructure powering software development at large, the underlying inference engines serving those requests are under increasing strain. The LightSeek Foundation researchers have released TokenSpeed, an […]
The post LightSeek Foundation Releases TokenSpeed, an Open-Source LLM Inference Engine Targeting TensorRT-LLM-Level Performance for Agentic Workloads appeared first on MarkTechPost.
Writing code has always been the most time- and resource-intensive task in software development. AI is changing that, and faster than most engineering organizations are prepared for. Tools like Claude Code and Cursor are already handling significant parts of code construction, freeing developers to spend more time on requirements, architecture, and design.
But that shift creates a new challenge nobody is talking about enough. As AI takes on the heavy lifting, the skills that matter most are moving upstream: how to provide the right context for a prompt, how to evaluate what the model produces, and how to understand a problem deeply enough that you can’t be fooled by a confident but wrong answer.
This piece explores those three skills and why developers who master them will have a significant edge over those who don’t.
Beyond coding: Mastering the art of the prompt
Software translation tools such as compilers and assemblers map a high-level description of code to a lower-level represent
I’m not even remotely worried about AI eliminating software development jobs. In fact, I’m pretty sure there will soon be a boom in both software development jobs and the amount of software available to everyone.
People have always worried about automation causing massive unemployment. Each time a breakthrough happens, folks are sure that “it will be different this time.” Only it never is different.
But the worriers persist.
It’s paradoxical
You can tell them all about the Jevons paradox — the observation that as something becomes more efficient, demand for that more efficient thing increases rather than decreases. In the mid-19th century, William Jevons noticed that the use of coal became more efficient. Humans figured out how to get more heat and energy out of less and less coal. The common belief was that, because less coal was needed for the same amount of energy or heat, there would be less demand for coal as a result. Everyone was concerned that coal miners would lose their jo
OpenAI’s B2B Signals research shows how frontier enterprises deepen AI adoption, scale Codex-powered agentic workflows, and build durable competitive advantage.
