A question for @Nate Herk Everything seems to be moving towards Codex and Claude being the machine, the operations centre. But is that or should that really be the case? As far as I can tell it doesn't make sense to use them for any repeatable task? They'll always be token cost heavy and that would suggest N8N should still be where you go? Maybe using them to build faster? Am I missing something?

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n8n just released a brand-new feature: native data tables. This makes it possible to store and manage data directly inside your n8n environment without needing an external database or constant API calls. In this video, I walk you through how these tables work, how to set them up, and how you can connect them to your workflows or AI agents in just a few clicks. I also cover the pros and cons, and when you might still want to use a traditional database instead. If you’re building quick proof of concepts, demos, or just want a simple way to manage data without latency or rate limit issues, this feature is a game-changer. The google sheets templates: Contacts Sales Test

In this video, I’ll show you how to connect ChatGPT directly to your n8n AI agents so you can trigger powerful workflows right from the ChatGPT interface. This integration can seriously boost your productivity by combining ChatGPT’s intelligence with your custom n8n workflows. I walk through a real example where ChatGPT parses data from an invoice using its document understanding capabilities and sends that data to n8n, which handles the rest of the workflow behind the scenes. Whether you're looking to streamline operations or build smarter automations, this setup opens up a ton of possibilities. ActionGPT