Codex

OpenAI introduced Daybreak tools, including Codex Security and GPT-5.5-Cyber, to help organizations find, validate, and patch vulnerabilities at scale. The new tools are meant to bring AI-assisted security workflows to every organization, with a focus on faster vulnerability discovery and remediation.

Jason Liu describes using Codex to preserve context and manage complex projects so work can continue beyond a single prompt. The key point is that Codex is being used for long-running tasks where retaining state and continuity matters more than one-shot answers.

Samsung Electronics is deploying ChatGPT Enterprise and Codex to employees worldwide, marking one of OpenAI’s largest enterprise AI rollouts. This gives Samsung broad access to OpenAI’s tools across its global workforce and signals continued expansion of enterprise AI adoption at major hardware companies.

Astrophysicist Chi-kwan Chan uses Codex to help build black hole simulations for studying extreme physics and testing Einstein’s theory of general relativity. It shows how coding assistants can speed scientific simulation work in a domain where accurate models are computationally demanding and physically complex.

OpenAI plans to acquire Ona to add secure, persistent cloud environments to Codex, enabling long-running AI agents across enterprise workflows. The deal matters because persistent environments are a key missing piece for agentic coding and enterprise automation, where models need stable state and execution over long periods.

Oracle is offering access to OpenAI models and Codex through Oracle Cloud, allowing customers to use existing cloud commitments to build and deploy AI applications with enterprise security and governance. This matters because it lets enterprises consume OpenAI capabilities without changing procurement, while keeping workloads inside Oracle’s security and governance framework.

Nextdoor engineers are using Codex with GPT-5.5 to investigate hard-to-reproduce issues and build across platforms. The setup is meant to remove engineering bottlenecks so they can spend more time on product outcomes instead of debugging and platform-specific work.

Notion says it uses Codex to one-shot specs and help build features like AI Voice Input for the web, while multiplying engineering output across small teams. The notable detail is that Codex is being positioned as a practical force multiplier for product and engineering work, not just a coding assistant.