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what's the current best approach on an AI that can help me handle my email inbox? seems like a big opportunity for folks playing with openclaw. For all of us who are drowning in email, this seems like a tier one problem that would be amazing to solve. (And I think I would pay $150k/year to have this product? I bet I'm not the only one) what I want is: - watch my inbox and process emails as they come in - score each message to see if it seems important (look at the sender, the topic/body, if its addressed to me or a big list, if I've ever replied to the sender before, etc etc) - read the email and reference a vast DB of knowledge that's been assembled already (based on my work, meeting notes, what I've replied on, etc), and decide what to do - reply with a draft note. For now, don't send, so that I can review the email -- but in the future maybe there's a YOLO option (but it would probably disclose that it's my assistant writing) - if less important, label it and file away. Eventually gather summaries for all of these less important emails and send me a summary of all of them with links to get back to it - or archive if it seems unimportant - or unsubscribe / mark spam / block if random marketing - if critical send me a notification right away so I can take a look I've played around with a bunch of the current AI tools and nothing quite works like this. There's a lot of blockers: - first, it needs 1000x more context about each problem, which it could get by crawling all my projects/notes/emails/slides/meetings/etc - This system should be designed to take action rather than simply just prioritizing messages. We've had prioritized inboxes for a long time but they're fine, not great - then someone has to put this entire UX together to be cohesive. In the future, we may not even really have an email inbox, but instead an interaction that feels more like I'm talking to an assistant who has a few questions for me. But otherwise just wants to provide a few quick updates and get some yes/nos. And otherwise filter all the noise -- just give me the most important messages It feels like we're very, very close to being able to do this, with the latest models from Anthropic and Open AI, we have the technology already. Someone just needs to package it all together in a way where it's able to index all of your emails and notes and calendars and contacts and sort of create a second brain that knows almost everything that you know so that I actually do things that are intelligent. It seems like with the excitement of OpenClaw we have the architecture to integrate a lot of different data sources and to take actions across multiple different channels. And it's built with one sort of monolithic memory and context, so that you're able to interact with it in such a way where it feels like it can try to replicate your actions more closely than the relatively stateless and memoryless LLM chats that we've gotten accustomed to. If someone is working on this, please point them to me. I would be both a customer and an investor!

Peter Steinberger just exposed the perception trap destroying every AI company’s moat. Every model release dies the same death. Week one: unprecedented breakthrough. Week five: mass complaints about quality collapse. Steinberger: “A new model comes out, people are like, oh my God, this is so good. And then like a month later, it degraded, it’s not good anymore.” Nothing degraded. The model is byte-for-byte identical. Your expectations just rewired themselves in real-time, turning magic into mediocrity without the technology changing at all. This can’t be solved. It’s human firmware. Open source models matching last year’s cutting edge get savaged as worthless. Capabilities that seemed impossible months ago now feel like broken promises. Steinberger: “In a year, we’ll have this open source. And then we’ll complain about this because we are used to this.” The frontier companies keep their technical advantage forever. Not because anyone appreciates it. Because human baseline expectations accelerate faster than physics allows technology to improve. But Steinberger identified where the real prison gets built. Not in models. In memory. Steinberger: “Every company kind of has their own silo, right? There’s no way to actually get the memories out of ChatGPT.” Models become commodities on clockwork schedules. Context doesn’t. Your conversation archive. Preference learning. Interaction patterns. The invisible skeleton making AI stop being a tool and start being an extension of your cognition. You can abandon any model instantly. Abandoning your context means self-amputation. The winners aren’t racing for smarter AI. They’re building context traps you can’t escape without losing pieces of yourself. Once your work, your thinking, your operational memory crystallizes in their system, switching doesn’t mean finding better technology. It means choosing between their product and personal lobotomy. Models are temporary. Memory is forever. And whoever owns yours owns you.