OpenAI has introduced Chronicle, a new experimental feature for its Codex app that allows the AI to observe a user’s screen activity and build contextual memory automatically. The feature, now available in preview for ChatGPT Pro users on macOS, represents a significant step toward more autonomous and context-aware AI assistants.

Chronicle operates in the background by periodically capturing screenshots, analyzing them, and converting them into structured text summaries. These summaries are stored locally and used to provide context for future interactions, allowing Codex to understand ongoing tasks without requiring users to repeatedly explain their work.

OpenAI president Greg Brockman described the feature as giving the assistant the ability to “see and remember” recent activity, enabling a more seamless and responsive workflow.

Turning Activity Into Context

The core goal of Chronicle is to reduce friction in AI-assisted work. By tracking what users are doing across applications, Codex can infer project context, tools in use, and recent actions, making interactions more efficient.

This approach aligns with a broader trend in AI development toward persistent memory and agent-like behavior, where systems can operate continuously and build knowledge over time. Instead of responding to isolated prompts, Codex can maintain continuity across sessions and tasks.

However, this deeper integration also introduces technical and operational trade-offs, particularly around data handling and system performance.

Privacy and Security Concerns

Chronicle’s architecture has raised concerns about user privacy and security. Screenshots captured by the system are sent to OpenAI servers for processing and are deleted within six hours. However, the generated summaries are stored locally as unencrypted Markdown files, potentially accessible to other applications.

OpenAI has acknowledged the risks, noting that the feature could increase exposure to prompt injection attacks and accidental leakage of sensitive information visible on screen. The company advises users to disable Chronicle when working with confidential data.

The feature may also increase usage costs, as continuous background processing consumes more request capacity within subscription limits.

Echoes of Industry Challenges

The launch draws comparisons to Microsoft’s earlier attempt to introduce a similar feature, Recall, in Windows. That tool also captured user activity for AI processing but faced strong backlash over privacy concerns, leading Microsoft to delay its rollout and make it optional.

Chronicle reflects the same tension facing the industry: balancing the benefits of highly contextual AI systems with the risks of continuous data capture. As AI tools become more integrated into daily workflows, managing that balance will be critical for user trust and adoption.

The feature signals OpenAI’s push toward more proactive, agent-like assistants, but its long-term success may depend on how effectively the company addresses privacy and security challenges.

Anthropic is investigating reports that unauthorized users gained access to its unreleased Claude Mythos Preview, a highly advanced system designed for cybersecurity applications. According to a report by Bloomberg, a small group accessed the model through a third-party vendor environment on the same day Anthropic began limited testing with approved organizations.

The company confirmed it is reviewing the incident, stating that it is examining claims of unauthorized access through external infrastructure. The model, part of Anthropic’s Project Glasswing initiative, is being deployed under strict controls to a limited number of partners for defensive cybersecurity purposes.

The reported breach raises concerns given the model’s capabilities. Mythos is designed to identify software vulnerabilities and simulate cyberattacks, functions that are typically restricted due to potential misuse.

High-Stakes Capabilities and Risks

Anthropic has positioned Mythos as a tool for strengthening cybersecurity by helping organizations detect weaknesses before attackers do. However, its capabilities also highlight the dual-use nature of advanced AI systems.

Reports suggest the model can identify complex and previously unknown vulnerabilities, construct multi-step attack scenarios, and generate functional exploit code. Such capabilities could significantly lower the barrier to entry for cyberattacks if misused.

Regulators and industry observers have already expressed concern about systems like Mythos, which blur the line between defensive and offensive cybersecurity tools. Anthropic has limited access to the model and avoided a full public release, citing safety considerations.

Security Controls Under Scrutiny

The incident underscores the challenges of securing highly capable AI systems, particularly when they are deployed through third-party infrastructure. Even controlled rollouts can introduce vulnerabilities if external systems are involved.

Anthropic said it is continuing discussions with government and industry partners about safe deployment of the technology. The company has emphasized that Mythos is intended for defensive use, such as vulnerability research and red-teaming.

The situation also highlights broader questions about how AI developers should manage access to powerful models. As capabilities increase, ensuring that systems are used responsibly becomes more complex, especially when demand for such tools is high.

Growing Pressure Around AI Governance

The reported access comes amid heightened scrutiny of advanced AI models and their potential impact on cybersecurity. Governments and organizations are increasingly focused on balancing innovation with risk mitigation.

Anthropic has already faced regulatory attention and internal debate over how widely to release Mythos. The company has framed the model as a way to stay ahead of attackers, but the incident illustrates the difficulty of maintaining strict control over such systems.

As AI models become more capable of executing complex, real-world tasks, incidents like this may shape future policies on access, oversight, and deployment of high-risk technologies.

OpenAI has launched Codex Labs, a new initiative aimed at accelerating enterprise adoption of its Codex platform, as usage continues to grow rapidly. The company said weekly active developers using Codex have surpassed 4 million, up from 3 million just two weeks earlier.

The expansion reflects strong demand from both individual developers and large organizations, with enterprises increasingly integrating Codex into real-world workflows. Companies including Virgin Atlantic, Ramp, Notion, Cisco, and Rakuten are using the platform across tasks such as testing, code review, feature development, and incident response.

OpenAI said Codex is increasingly being used beyond engineering teams, helping organizations analyze information, generate documents, and automate workflows across departments.

Bringing AI Into Enterprise Workflows

Codex Labs is designed to help companies move from early experimentation to production-scale deployment. Through workshops and hands-on sessions, OpenAI experts will work directly with organizations to identify high-value use cases, integrate Codex into existing systems, and establish repeatable workflows.

The initiative addresses a key challenge in enterprise AI adoption: translating early success into consistent, organization-wide impact. OpenAI said demand for Codex support is exceeding its internal capacity, prompting the creation of a structured program to guide deployment.

The company is also emphasizing Codex’s ability to support the full software development lifecycle, from writing and reviewing code to testing and maintaining systems.

Partnering to Scale Adoption

To expand its reach, OpenAI is working with major global systems integrators, including Accenture, Capgemini, Cognizant, Infosys, PwC, and Tata Consultancy Services.

These partners will help enterprises identify opportunities, implement solutions, and scale Codex deployments across complex organizations. Many are also using Codex internally to refine best practices and accelerate delivery for clients.

The move reflects a broader shift in enterprise software, where AI tools are becoming central to how companies build and operate systems. By combining direct support with partner-led implementation, OpenAI is aiming to accelerate adoption globally.

As Codex usage expands beyond coding into broader business workflows, the company is positioning it as a general-purpose productivity layer, capable of transforming how teams work across the enterprise.