I’d like to make a note. And record my prediction!...
# feedback
c
I’d like to make a note. And record my prediction! I saw a youtube interview with Robert, and he said OpenHands is scoped within SWE. He didn’t exactly say that personal agents are out of scope, but it felt like that to me. (I had to double check!). I want to expand on a different point of view on personal agents. So one way to look at the SWE scope is to say, ok, OpenHands is focused on SWE; in its entirety (from requirements gathering, triage to deploy, monitoring, feedback). But that could be said as both focus and limitation, as in, focus on SWE and limited to SWE (that is, no “booking flights”, you know, the favorite example since OpenAI’s old Atlas) I think the first, focus, is fine, sure; but the second, limiting, isn’t really true. Software has been eating the world because software is in almost every human endeavor. If an agent is good in making software, then it’s good in “booking flights” too. Sure, sometimes you may want some extra skills, but of course you can install them and it’s perfectly doable. In the measure personal agents mean “some agent that knows how to book me flights”, OpenHands can do it. Also, since it’s SWE, you can have it make the others! (I note that the other way around it’s not necessarily true: most specialized agents that I’ve seen - legal, customer service - have been, at least for a while, full of predefined workflows, which is to say, they’re not good in a different domain unless you strip them down first, and even then, it depends. Reduce them to bash, python, memory, and maybe browsing, if you can - if they even have them - then it can be done.) More importantly, I think that’s not what personal agents mean: I believe it’s primarily UX. It’s how they feel like, how you use them, not whether they can do stuff in a particular domain, SWE or non-SWE. It’s really just UX: your agent is defined not by what it can do, but by a few other characteristics which all come down to UX: • knows your priorities and preferences (which can be work or SWE) • accessible wherever you are (Slack, WhatsApp, Discord, GitHub, etc) • memory/learning. For example, my personal agent is literally an OpenHands agent, it works on agent-sdk REST interface. It can do everything OpenHands can do. Thanks to memory, access for context, and some bit of proactivity/personality, it _feels different_; which is to say, UX. It also feels like I can do more with it, within SWE, too. e.g. I never need to “select repo by clicking a UI element” (why? it knows them all) etc. Which is to say, smooth UX wise. I have, in the past, argued that OpenHands could return to its roots, and walk the path of personal AI engineer - it literally had in its system prompt that it’s “an AI software engineer” (since that’s what Cognition’s Devin campaign was claiming to be, back in the day). Doing so would imply to see it behave or feel like more like an entity, an “AI colleague”, than as “a web app”. I mean, it would imply, it seems to me, that the way interactivity works would be like a personal agent. (automations are the non-interactive side) I lost that argument. In a sense, we always walked a few steps on that path with the OpenHands Slack agent (since late 2024!), but we stopped at basics. You can mention it, that is, prompt it, and it can do its stuff as usual (yes, SWE stuff), and that’s about it. It doesn’t feel like a personal agent, and I don’t think - to my knowledge - that it feels like an “AI colleague”. I do want to say though: I notice, as we all do, that after the OpenClaw explosion (which went down! apparently), personal agents are actually showing up in the industry lately quite a bit. And TBH I’m not surprised: it’s my prediction that personal agents/AI colleagues, customizing them for both user and team and public, are only going to grow. People will try things, test limits, maybe get some unexpected UX right; while going to a web app to prompt them… is not part of the future. I could be wrong. Hey, it’s happened before! I want to record this prediction; as you may have seen, I’ve made the argument for a while; just want to be clear about it, and be burned at stake for it. Pinned. 😅
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h
Love it! What are you using for personal agent memory?
w
I largely agree with you here 🙂 In particular, I agree that if you build a great SWE assistant, you have everything you need for a great personal assistant. And I'm excited folks are using OpenHands to do more than just software! But one of the trickiest things about building in the AI era is that everything can do everything. If you're not clear about "who should use this product, and what should they use it for", it just gets drowned in an ocean of generic intelligence products. So I'm going to keep banging the drum that OpenHands is primarily for software engineers, to be used for software tasks. We'll highlight integrations with GitHub and Jira, we'll push automations for things like code review and bug triage, etc etc. But I also love the idea that we're giving software engineers agentic building blocks! E.g. your smolpaws is a great example of what you can build on top of OpenHands with some creativity. I do want to see more of that type of experimentation
c
Love it! What are you using for personal agent memory?
(1) Markdown files! 😂 • it has a prompt about it • it saves in daily memory files e.g. memory-09-22-26.md • and in memory.md (2) Dreaming • periodically, a scheduled task reads memory files with a good LLM • and shuffles things around, recency, relevance etc • so the main memory.md might change They're simple and inspired from MemGPT/Letta. There are others, a
gbrain
attempt, repos like
papers-please
(which is kind of an LLM wiki), and notebooks like
<http://enyst.github.io|enyst.github.io>
. I mean, those things need remembered, too, but they don’t need to be in a single place to find them. 🤔
But one of the trickiest things about building in the AI era is that everything can do everything. If you're not clear about "who should use this product, and what should they use it for", it just gets drowned in an ocean of generic intelligence products.
nod I hear you. Speaking of which, I was thinking about Linear’s trajectory for a while… and there it comes, sorry, Linear is practically becoming a competitor for OpenHands Cloud.
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What are you using for personal agent memory?
I've been also experimenting with a new condensation mechanism: let the LLM take care of the context of its future self. • it gets a warning at 75% • when it decides to, it saves notes for the future self • then calls a
condense
tool, with a message • then previous history is not sent anymore in context • it's free to read its notes to get its bearings again. It works very well, I haven't seen forgetting stuff, no issues with computing anything, because it's just as simple as that. LLMs are at the point where a lot of hardcoded scaffolding for this isn't a necessity, as it was in the past.