AI-curated insights from 1000+ daily updates, delivered as an audio briefing of new capabilities, real-world cases, and product tools that matter.
Stay ahead with AI-curated insights from 1000+ daily and weekly updates, delivered as a 7-minute briefing of new capabilities, real-world cases, and product tools that matter.
Join The GenAI PMDive deeper into the topics covered in today's brief with these AI PM insights.
As of 2025-10-07, Google DeepMind introduced CodeMender, an AI agent using Gemini Deep Think to automatically patch critical software vulnerabilities. PMs looking to streamline security patching can leverage CodeMender to reduce manual intervention and accelerate vulnerability fixes. Here’s how to evaluate and implement CodeMender: 1. Assess your current security patch process: Identify the critical vulnerabilities that require immediate automated fixes and map out your existing workflows. 2. Review integration capabilities: Check CodeMender’s API documentation and integration guides to understand how it interfaces with your infrastructure, including compatibility with your software stack. 3. Run a pilot test: Start with a non-critical segment of your system. Monitor the AI agent’s performance in patching vulnerabilities automatically and verify if the patches meet security standards. 4. Measure key metrics: Track critical metrics such as improvement in patch deployment speed and reduction in manual effort. Early reports suggest significant time savings though specific percentages will emerge from later case studies. 5. Iterate and scale: Based on the pilot feedback, fine-tune the prompting and monitoring process. Ensure that your team has clear guidelines for intervening if automated patches do not behave as expected. Real-world trial: While detailed case studies are still emerging, early implementation reports as of 2025-10-07 indicate that PMs who integrate tools like CodeMender can better manage context-aware, automated security patches, allowing more time to focus on strategic product development. By following these steps, PMs can ensure CodeMender is effectively evaluated and scaled to support robust security operations.
As of 2025-10-07, OpenAI began rolling out ChatGPT Apps to Free, Go, Plus, and Pro users outside of the EU, with additional pilot partner apps to follow. For PMs, this presents a powerful opportunity to integrate third-party applications directly into the ChatGPT interface, thereby enriching user engagement and functional flexibility. Here’s how to set it up: 1. Identify strategic partner applications: Pinpoint which third-party tools or services align with your product’s goals and could benefit from integrated AI-driven interactions. 2. Review OpenAI’s API documentation: Familiarize yourself with the deployment guidelines and technical requirements for integrating partner apps into ChatGPT. This includes ensuring that data flows, authentication, and user experience guidelines are met. 3. Conduct a pilot integration: Start by integrating one or two key partner apps. Use a controlled user group to validate the interface functionality, response times, and overall user experience. 4. Monitor performance metrics: Track user engagement data, error rates, and performance ballots. With an expanding set of pilot partner apps expected soon, these metrics will be crucial in determining ROI and identifying potential areas of improvement. 5. Iterate based on feedback: Gather qualitative and quantitative feedback from your initial user base, refine the integration, and prepare for broader deployment. While concrete case studies are still being developed, early implementation reports as of October 2025 indicate that PMs leveraging ChatGPT Apps have already begun to see increased user interaction and smoother workflows, positioning integrated partner applications as a key competitive advantage for AI-powered products.