[HN Gopher] Nanobot: Ultra-Lightweight Alternative to OpenClaw
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Nanobot: Ultra-Lightweight Alternative to OpenClaw
Author : ms7892
Score : 199 points
Date : 2026-02-05 09:39 UTC (13 hours ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| johaugum wrote:
| Skimmed the repo, this is basically the irreducible core of an
| agent: small loop, provider abstraction, tool dispatch, and chat
| gateways . The LOC reduction (99%, from 400k to 4k) mostly comes
| from leaving out RAG pipelines, planners, multi-agent
| orchestration, UIs, and production ops.
| baby wrote:
| RAG seems odd when you can just have a coding agent manage
| memory by managing folders. Multi agent also feels weird when
| you have subagents.
| antirez wrote:
| Totally useless indeed.
| rando77 wrote:
| I've been leaning towards multi agent because sub agent
| relies on the main agent having all the power and using it
| responsibly.
| PlatoIsADisease wrote:
| Interesting.
|
| I guess RAG is faster? But I'm realizing I'm outdated now.
| lxgr wrote:
| No, RAG is definitely preferable once your memory size
| grows above a few hundred lines of text (which you can just
| dump into the context for most current models), since
| you're no longer fighting context limits and needle-in-a-
| haystack LLM retrieval performance problems.
| Aurornis wrote:
| > once your memory size grows above a few hundred lines
| of text (which you can just dump into the context for
| most current models)
|
| A few hundred lines of text is nothing for current LLMs.
|
| You can dump the entire contents of The Great Gatsby into
| any of the frontier LLMs and it's only around 70K tokens.
| This is less than 1/3 of common context window sizes.
| That's even true for models I run locally on modest
| hardware now.
|
| The days of chunking everything into paragraphs or pages
| and building complex workflows to store embeddings,
| search, and rerank in a big complex pipeline are going
| away for many common use cases. Having LLMs use simpler
| tools like grep based on an array of similar search terms
| and then evaluating what comes up is faster in many cases
| and doesn't require elaborate pipelines built around
| specific context lengths.
| lxgr wrote:
| Yes, but how good will the recall performance be? Just
| because your prompt fits into context doesn't mean that
| the model won't be overwhelmed by it.
|
| When I last tried this with some Gemini models, they
| couldn't reliably identify specific scenes in a 50K word
| novel unless I trimmed down the context to a few
| thousands of words.
|
| > Having LLMs use simpler tools like grep based on an
| array of similar search terms and then evaluating what
| comes up is faster in many cases
|
| Sure, but then you're dependent on (you or the model)
| picking the right phrases to search for. With embeddings,
| you get much better search performance.
| Aurornis wrote:
| > Yes, but how good will the recall performance be? Just
| because your prompt fits into context doesn't mean that
| the model won't be overwhelmed by it.
|
| With current models it's very good.
|
| Anthropic used a needle-in-haystack example with The
| Great Gatsby to demonstrate the performance of their
| large context windows all the way back in 2023:
| https://www.anthropic.com/news/100k-context-windows
|
| Everything has become even better in the nearly 3 years
| since then.
|
| > Sure, but then you're dependent on (you or the model)
| picking the right phrases to search for. With embeddings,
| you get much better search performance.
|
| How do are those embeddings generated?
|
| You're dependent on the embedding model to generate
| embeddings the way you expect.
| lxgr wrote:
| That doesn't match my experience, both in test and actual
| usage scenarios.
|
| Gemini 3 Pro fails to satisfy pretty straightforward
| semantic content lookup requests for PDFs longer than a
| hundred pages for me, for example.
| Aurornis wrote:
| > for PDFs longer than a hundred pages for me
|
| Your original comment that I responded to said a "few
| hundred lines of text", not hundred page PDFs.
| rdedev wrote:
| I think it still has a place of your agent is part of a
| bigger application that you are running and you want to
| quickly get something in your models context for a quick
| turnaround
| simonw wrote:
| Yeah, vector embeddings based RAG has fallen out of fashion
| somewhat.
|
| It was great when LLMs had 4,000 or 8,000 token context
| windows and the biggest challenge was efficiently figuring
| out the most likely chunks of text to feed into that window
| to answer a question.
|
| These days LLMS all have 100,000+ context windows, which
| means you don't have to be nearly as selective. They're also
| exceptionally good at running search tools - give them grep
| or rg or even `select * from t where body like ...` and
| they'll almost certainly be able to find the information they
| need after a few loops.
|
| Vector embeddings give you fuzzy search, so "dog" also
| matches "puppy" - but a good LLM with a search tool will
| search for "dog" and then try a second search for "puppy" if
| the first one doesn't return the results it needs.
| y1n0 wrote:
| Context rot is still a problem though, so maybe vector
| search will stick around in some form. Perhaps we will end
| up with a tool called `vector grep` or `vg` that handles
| the vectorized search independent of the agent.
| visarga wrote:
| The fundamental problem wit RAG is that it extracts only
| surface level features, "31+24" won't embed close to "55",
| while "not happy" will be close to "happy". Another issue
| is that embedding similarity does not indicate logical
| dependency, you won't retrieve the callers of a function
| with RAG, you need a LLM or code for that. Third issue is
| chunking, to embed you need to chunk, but if you chunk you
| exclude information that might be essential.
|
| The best way to search I think is a coding agent with grep
| and file system access, and that is because the agent can
| adapt and explore instead of one shotting it.
|
| I am making my own search tool based on the principle of
| LoD (level of detail) - any large text input can be trimmed
| down to about 10KB size by doing clever trimming, for
| example you could trim the middle of a paragraph keeping
| the start and end, or you could trim the middle of a large
| file. Then an agent can zoom in and out of a large file. It
| skims structure first, then drills into the relevant
| sections. Using it for analyzing logs, repos, zip files,
| long PDFs, and coding agent sessions which can run into MB
| size. Depending on content type we can do different types
| of compression for code and tree structured data. There is
| also a "tall narrow cut" (like cut -c -50 on a file).
|
| The promise is - any size input fit into 10KB "glances" and
| the model can find things more efficiently this way without
| loading the whole thing.
| visarga wrote:
| Ok 2 hours later here is the release:
| https://github.com/horiacristescu/nub
| gervwyk wrote:
| This is a very cool idea. I've been dragging CC around
| very large code bases with a lot of docs and stuff. it
| does great but can be a swing and a miss.. have been
| wondering if there is a more efficient / effective way.
| This got me thinking. Thanks for sharing!
| m00dy wrote:
| RAG is broken when you have too much data.
| thunky wrote:
| Gemini with Google search is RAG using all public data, and
| it isn't broken.
| fhd2 wrote:
| It's not tool use with natural language search queries?
| That's what I'd expect.
| kaicianflone wrote:
| It is tool use with natural language search queries but
| going down a layer they are searched on a vector DB, very
| similar to RAG. Essentially Google RankBrain is the very
| far ancestor to RAG before compute and scaling.
| thunky wrote:
| It's RAG via tool use, where the storage and retreival
| method is an implementation detail.
|
| I'm not a huge fan of the term RAG though because if you
| squint almost all tool use could be considered RAG.
|
| But if you stick with RAG being a form of "knowledge
| search" then I think Google search easily fits.
| PlatoIsADisease wrote:
| Cant you make thresholds higher?
|
| Hmm... I guess not, you might want all that data.
|
| Super interesting topic. Learning a lot.
| plingamp wrote:
| Specifically when the document number reaches around 10k+, a
| phenomenon called "Semantic Collapse" occurs.
|
| https://dho.stanford.edu/wp-
| content/uploads/Legal_RAG_Halluc...
| yjftsjthsd-h wrote:
| So you're telling me rampancy (
| https://www.halopedia.org/Rampancy ) is real.
| zophi wrote:
| > Specifically when the document number reaches around 10k+
|
| Where are you getting this? just read the paper and not
| seeing it -- interested to learn more
| RGamma wrote:
| The RAG GP used suffered from semantic collapse.
| naasking wrote:
| Unless I'm misunderstanding what they are, planners seem kind
| of important.
| johaugum wrote:
| As you mentioned, that depends on what you mean by planners.
|
| An LLM will implicitly decompose a prompt into tasks and then
| sequentially execute them, calling the appropriate tools. The
| architecture diagram helpfully visualizes this [0]
|
| Here though, planners means autonomous planners that exist as
| higher level infrastructure, that does external task
| decomposition, persistent state, tool scheduling, error
| recovery/replanning, and branching/search. Think a task like
| "Prompt: "Scan repo for auth bugs, run tests, open PR with
| fixes, notify Slack." that just runs continuously 24/7, that
| would be beyond what nanobot could do. However, something
| like "find all the receipts in my emails for this year, then
| zip and email them to my accountant for my tax return" is
| something nanobot would do.
|
| [0]
| https://github.com/HKUDS/nanobot/blob/main/nanobot_arch.png
| naasking wrote:
| Sure, instruction tuned models implicitly plan, but they
| can easily lose the plot on long contexts. If you're going
| to have an agent running continuously and accumulating
| memory (parsing results from tool use, web fetches,
| previous history, etc.), then plan decomposition,
| persistence and error recovery seems like a good idea, so
| you can start subagents with fresh contexts for task items
| and they stay on task or can recover without starting
| everything over again. Also seems better for cost since
| input and output contexts are more bounded.
| skybrian wrote:
| I don't know what these planners do, but I've had reasonably
| good luck asking a coding agent to write a design doc and
| then reviewing it a few times.
| jannniii wrote:
| Okay so is this "inspired" by nanoclaw that was featured here two
| days ago?
| jimmcslim wrote:
| Hah, I was looking at this and going "wasn't this up on HN
| front page just a few days ago?" and has completely missed
| Nanoclaw vs Nanobot.
| reustle wrote:
| For the curious
|
| https://github.com/gavrielc/nanoclaw
| vanillameow wrote:
| Yeah I mean idk, my takeaway from OpenClaw was pretty much the
| same - why use someone's insane vibecoded 400k LoC CLI wrapper
| with 50k lines of "docs" (AI slop; and another 50k Chinese
| translation of the same AI slop) when I can just Claude Code
| myself a custom wrapper in 30 mins that has exactly what I need
| and won't take 4 seconds to respond to a CLI call.
|
| But my reaction to this project is again: Why would I use this
| instead of "vibecoding" it myself. It won't have exactly what I
| need, and the cost to create my own version is measured in
| minutes.
|
| I suspect many people will slowly come to understand this
| intrinsic nature of "vibecoded software" soon - the only valuable
| one is one you've made yourself, to solve your own problems. They
| are not products and never will be.
| pelagicAustral wrote:
| I mean, in not vibecoding it yourself you are already saving
| tokens... Personally, I see no benefit in having an instance of
| something like this... so, I wouldn't spend tokens, and I
| wouldn't spend server-time, or any other resource into it, but
| a lot of people seem to have found a really nice alternative to
| actually having to use their brains during the day.
| vanillameow wrote:
| I do see the potential in something like OpenClaw,
| personally, but more as a kind of interface for a collection
| of small isolated automations that _could_ be loosely
| connected via some type of memory bank (whether that's a RAG
| or just text files or a database or whatever). Not all of
| these will require LLMs and certainly none of them will
| require vibecoding at all if you have infinite time; But the
| reality is I don't have infinite time, and if I have 300
| small ideas and I can only implement my like 10 of them a
| week by myself, I'd personally rather automate 30 more than
| just not have them at all, you know?
|
| But I am talking about shell scripts here, cronjobs, maybe
| small background services. And I would never dare publish
| these as public applications or products. Both because I feel
| no pride about having "made" these - because, you know, I
| haven't, the AI did - and because they just aren't public
| facing interfaces.
|
| I think the main issue at the moment is that so many devs are
| pretending that these vibecoded projects are "products". They
| are not. They are tailor-made, non-recyclable throwaway
| software for one person: The creator. I just see no world at
| the moment where I have any plausible reason to use someone
| else's vibecoded software.
| tianshuo wrote:
| Our team doesn't use things like OpenClaw. We use Windmill,
| which is a workflow engine that can use AI to program
| scripts and workflows. 90% of our automated flows are just
| vanilla python or nodejs. We re-use 10% of scripts in
| different flows. We do have LLM nodes and other AI nodes,
| and although windmill totally supports AI tool
| calling/Agentic use, we DON'T let AI agents decide the next
| step. Boring? Maybe. Dependable? Yes.
| johaugum wrote:
| > a lot of people seem to have found a really nice
| alternative to actually having to use their brains during the
| day.
|
| Or have they have found a way to use their brains on what
| they deem as more useful, and less on what is rote?
| pelagicAustral wrote:
| Yeah, I guess I just don't really have a lot of meaningful
| things to take care of.
| kmaitreys wrote:
| I see this retort pasted everywhere. What exactly are you
| referring to? I think it's fair to assume any competent
| person never spends their brain in what may be considered
| as rote in the first place. If one was doing that, well
| it's unfortunate.
|
| I just keep coming to the conclusion about devs who use
| agents or other AI tooling extensively: these are
| programmers who did not like to program.
| sumitkumar wrote:
| It is not about making it yourself but a tradeoff between how
| much it can be controlled and how much has seen the real world.
| Adding requirements learned by mistakes of others is slower in
| self-controlled development vs an open collaboration vs a
| company managing it. This is the reason vibe-coded(initial
| requirements) projects feels good to start but tough to
| evolve(with real learnings).
|
| Vibe-coded projects are high-velocity but low-entropy. They
| start fast, but without the "real-world learnings" baked into
| collaborative projects, they often plateau as soon as the
| problem complexity exceeds the creator's immediate focus.
| CuriouslyC wrote:
| So, as an OpenClaw disliker, the agent harness at the core of
| it (pi) is really good, it's super minimal and well designed.
| It's designed to be composed using custom functionality, it's
| easy to hack, whereas Claude Code is bloated and totally
| opinionated.
|
| The thing people are losing their shit over with OpenClaw is
| the autonomy. That's the common thread between it, Ralph and
| Gastown that is hype-inducing. It's got a lot of problems but
| there's a nugget of value there (just like Steve Yegge's stuff)
| j16sdiz wrote:
| The core "design" not bad, but the "code" quality is .. mid.
|
| They are basically keep breaking different feature on every
| release.
| px43 wrote:
| "Open source" is no longer about "Hey I built this tool and
| everyone should use it". It's about "Hey I did this thing and
| it works for me, here's the lessons I learned along the way",
| at which point anyone can pull in what they need, discard what
| they don't, and build out their own bespoke tool sets for
| whatever job they're trying to accomplish.
|
| No one is trying to get you to use openclaw or nanobot, but now
| that they exist in the world, our agents can use the knowledge
| to build better tooling for us as individuals. If the projects
| get a lot of stars, they become part of the global training set
| that every coding agent is trained against, and the utility of
| the tooling continues to increase.
|
| I've been running two openclaw agents, and they both made their
| own branchs, and modified their memory tooling to accommodate
| their respective tasks etc. They regularly check for upstream
| things that might be interesting to pull in, especially
| security related stuff.
|
| It feels like pretty soon, no one is going to just have a bunch
| of apps on their phone written by other people. They're going
| to have a small set of apps custom built for exactly the things
| they're trying to do day to day.
| vanillameow wrote:
| "If the projects get a lot of stars, they become part of the
| global training set that every coding agent is trained
| against, and the utility of the tooling continues to
| increase."
|
| OpenClaw currently has 1.8k issues, 400k lines of code, had
| an RCE exploit discovered just a few days ago, it takes 5
| seconds to get a response when I type "openclaw" in my CLI
| and most of the top skills are malware. I'm pretty sure
| training on that repository is the equivalent to eating a
| cyanide pill for a coding model.
|
| I actually agree with your take that custom apps will take
| over a subset of established software for some users at some
| point, but I don't think models poisoning themselves with
| recklessly vibecoded bloatware is how we get there at all.
| kmaitreys wrote:
| > Open source" is no longer about "Hey I built this tool and
| everyone should use it".
|
| Was open source ever about that? I thought it was "Hey I
| built this tool and I'm putting it on internet if anyone
| wants to use it" often accompanied by a license saying "no
| warranties".
|
| > It feels like pretty soon, no one is going to just have a
| bunch of apps on their phone written by other people. They're
| going to have a small set of apps custom built for exactly
| the things they're trying to do day to day
|
| I think today's AI tools like Agents are for people who are
| programmers but don't want to program, not ones who aren't
| programmers and don't want to program. As in, "no one is
| going to..." is a very broad statement to make for an average
| person who just uses apps on thier phone. Your average person
| will not start vibe coding their own apps just because they
| can (because they couldn't care less).
| exographicskip wrote:
| Are you me?? I'm literally building highly personalized
| and/or idiosyncratic software with claude to solve personal
| and professional problems.
|
| Thanks to tauri, I've now made two desktop apps and one
| mobile app for the first time in the last two months.
|
| None of this was nearly as feasible just a year ago
| threethirtytwo wrote:
| What I read is the unlimited token count. You get the most out
| of this when having it run on an autonomous loop where your
| interaction is much more minimal? But pinging the thing every
| minute in a loop is going to terminate your token limit so
| running the LLM locally is the way to get infinite tokens.
|
| The problem is local models aren't as good as the ones in the
| cloud. I think the success stories are people who spent like
| 2-4k on a beefy system to run OpenClaw or these chatbots
| locally.
|
| The commands they run are, I assume like detailed versions of
| prompts that are essentially: "build my website." "Invest in
| stocks." And then watch it run for days.
|
| When using claude code it's essentially a partnership. You need
| to constantly manage it and curate it for safety but also so
| the token count doesn't go overboard. With a fully autonomous
| agent and unlimited token count you can assign it to tasks
| where this doesn't matter as much. Did the agent screw up and
| write bad code? The point is you can have the system prompt
| engage in self correction.
| loveparade wrote:
| What are people using these things for? The use cases I've seen
| look a bit contrived and I could ask Claude or ChatGPT to do it
| directly
| dominicq wrote:
| Yeah, I don't get it either. Deploy a VM that runs an LLM so
| that I can talk to it via Telegram... I could just talk to it
| through an app or a web interface. I'm not even trying to be
| snarky, like what the hell even is the use case?
| BoredPositron wrote:
| It's not even an LLM it's just to pipe api calls.
| xylo wrote:
| Difference is that openclaw is not LLM but engine that spawns
| up agent that interact with LLM and the system its installed
| on.
|
| It can have full access to the system it's running on. So it
| can browse internet via browser, run cli commands, api's via
| skills etc.
|
| Idea is to act like a Jarvis personal assistant. You tell
| what to do via chat e.g telegram, then it does it for you.
| gergo_b wrote:
| I have no idea. the single thing I can think of is that it can
| have a memory.. but you can do that with even less code. Just
| get a VPS. create a folder and run CC in it, tell it to save
| things into MD files. You can access it via your phone using
| termux.
| sReinwald wrote:
| You could, but Claude Code's memory system works well for
| specialized tasks like coding - not so much for a general-
| purpose assistant. It stores everything in flat markdown
| files, which means you're pulling in the full file regardless
| of relevance. That costs tokens and dilutes the context the
| model actually needs.
|
| An embedding-based memory system (letta, mem0, or a self-
| built PostgreSQL + pgvector setup) lets you retrieve
| selectively and only grab what's relevant to the current
| query. Much better fit for anything beyond a narrow use case.
| Your assistant doesn't need to know your location and address
| when you're asking it to look up whether sharks are indeed
| older than trees, but it probably should know where you live
| when you ask it about the weather, or good Thai restaurants
| near you.
| ryanjshaw wrote:
| Here's a copy of a post I made on Farcaster where I'm
| unconvinced it's actually being used at all:
|
| I've used OpenClaw for 2 full days and 3 evenings now. I simply
| don't believe people are using this for anything majorly
| productive.
|
| I really, really want to like it. I see glimpses of the future
| in it. I generally try to be a positive guy. But after spending
| $200 on Claude Max, running with Opus 4.5 most of the time, I'm
| just so irritated and agitated... IT'S JUST SO BAD IN SO MANY
| WAYS.
|
| 1. It goes off on these huge 10min tangents that are the
| equivalent of climbing out of your window and flying around the
| world just to get out of your bed. The /abort command works
| maybe 1 time out of 100, so I end up having to REBOOT THE
| SERVER so as not to waste tokens!
|
| 2. No matter how many times I tell it not to do things with
| side effects without checking in with me first, it insists on
| doing bizarre things like trying to sign up for new accounts
| people when it hits an inconvenient snag with the account we're
| using, or it tried emailing and chatting to support agents
| because it can't figure out something it could easily have
| asked ME for help with, etc.
|
| 3. Which reminds me that its memory is awful. I have to remind
| it to remind itself. It doesn't understand what it's doing half
| the time (e.g. it forgets the password it generated for
| something). It forgets things regularly; this could be because
| I keep having to reboot the server.
|
| 4. It forgets critical things after compaction because the
| algorithm is awful. There I am, typing away, and suddenly it's
| like the Men in Black paid a visit and the last 30min didn't
| happen. Surely just throwing away the oldest 75% of tokens
| would be more effective than whatever it's doing? Because it
| completely loses track of what we're doing and what I asked it
| NOT to do, I end up with problem (1) again.
|
| 5. When it does remember things, it spreads those memories all
| over the place in different locations and forgets to keep them
| consistent. So after a reboot it gets confused about what is
| the truth.
| threethirtytwo wrote:
| there's an entire cohort on HN who still claim AI is utterly
| and completely useless despite in your face evidence.
| Literally people making a similar claim word for word who say
| that they don't understand the hype that they used AI
| themselves and it's shit.
|
| Meanwhile my entire company uses AI and the on the ground
| reality for me versus the cohort above is so much at odds
| with each other we're both claiming the other side is insane.
|
| I haven't used these bots yet but I want to see the full
| story. Not just one guys take and one guys personal
| experience. The hype exists because there are success
| stories. I want to hear those as well.
| jamespo wrote:
| There's people saying AI isn't living up its hype /
| valuation, I don't see many saying "utterly useless".
|
| And there's plenty who worship at the altar of Claude.
| threethirtytwo wrote:
| >There's people saying AI isn't living up its hype /
| valuation, I don't see many saying "utterly useless".
|
| There's more people saying AI doesn't live up to the
| hype. The people who are saying it's utterly useless is
| still quite large on HN. It's just that most of them are
| midway through changing their story because reality is
| smashing them in the face.
|
| >And there's plenty who worship at the altar of Claude.
|
| I mean who doesn't use it? No one claims it's perfect or
| a god of code. But if you're not using it you're behind.
| somebehemoth wrote:
| > There's more people saying AI doesn't live up to the
| hype.
|
| It is possible they are correct and nothing you have
| written suggests otherwise.
|
| > The people who are saying it's utterly useless is still
| quite large on HN.
|
| Are these people's opinions less valid than your own? Are
| you angry your opinion might be a minority on this one
| website?
|
| > It's just that most of them are midway through changing
| their story because reality is smashing them in the face.
|
| You made this up.
|
| > But if you're not using it you're behind.
|
| Yeah, well, you know, that's just, like, your opinion,
| man
| Philip-J-Fry wrote:
| What do you use AI for?
|
| Pretty much everyone in my company also uses AI. But
| everyone sees the same downsides.
| threethirtytwo wrote:
| Yep. But on HN, there's a huge cohort of people saying AI
| is useless.
|
| Everyone sees the downsides but the upside is the one
| everyone is in denial about. It's like yeah, there's
| downsides but why is literally everyone using it?
| grey-area wrote:
| Not everyone is using it.
| threethirtytwo wrote:
| Not yet.
| ryanjshaw wrote:
| I don't know how you came to that conclusion from my
| comment. I'm talking about a particular product named
| OpenClaw, representing a new style of doing work; not AI in
| general.
|
| I dropped $200 on Claude Max in my personal capacity to
| test OpenClaw because I use Opus 4.5 all day in Cursor on
| an enterprise subscription... because it works for those
| problems.
| threethirtytwo wrote:
| >I don't know how you came to that conclusion from my
| comment. I'm talking about a particular product named
| OpenClaw, representing a new style of doing work; not AI
| in general.
|
| Right, I'm saying AI in general is an example of the
| unreliability of peoples experiences on openclaw. If
| people are so unreliable about the narrative of AI, I
| don't trust the narrative of openclaw which on this
| thread in particular is very negative and in stark
| contrast to the hype.
|
| >I dropped $200 on Claude Max in my personal capacity to
| test OpenClaw because I use Opus 4.5 all day in Cursor on
| an enterprise subscription... because it works for those
| problems.
|
| The comment wasn't directed at you personally. I'm just
| saying I want to see counter examples of openclaw
| succeeding, not just examples of it failing. Frankly on
| this thread there's Zero success stories which I find
| sort of strange.
| renewiltord wrote:
| You're correct. Any statement by HN users that something is
| useless has no value because they say that about useful
| things too.
|
| Moltbot has the shape of the future but doesn't feel like
| it to me. Sort of like Langchain once was. Demonstrated
| some new paradigm shift but is itself flawed so may not be
| the implementation that lasts. Time will tell.
|
| The only thing here to say is "put it in a VM and try it".
| It's easy to try.
| Aurornis wrote:
| The comment above was saying OpenClaw was useless relative
| to their other heavy AI usage.
|
| The person you're criticizing says they're a heavy AI user.
| The take was about OpenClaw, not AI.
| bmurphy1976 wrote:
| Yeah, and he's basically asking for more OpenClaw success
| stories.
| bosky101 wrote:
| i've never had situations where i prompt and had to go out
| for coffee or a walk or drive. one shotting - your first
| prompt. perhaps.
|
| but like a person - when the possibility of going off in the
| wron g direction is so high, i've always had 1 - 2 line
| prompts, small iterations much more appealing. The only times
| i've had to rollback would be when i run out of credits, and
| a new model cant deal with the half baked context, errors,
| refactoring.
| sReinwald wrote:
| Disclaimer: Haven't used any of these (was going to try
| OpenClaw but found too many issues). I think the biggest value-
| add is agency. Chat interfaces like Claude/ChatGPT are
| reactive, but agents can be proactive. They don't need to wait
| for you to initiate a conversation.
|
| What I've always wanted: a morning briefing that pulls in my
| calendar (CalDAV), open Todoist items, weather, and relevant
| news. The first three are trivial API work. The news part is
| where it gets interesting and more difficult - RSS feeds and
| news APIs are firehoses. But an LLM that knows your interests
| could actually filter effectively. E.g., I want tech news but
| don't care about Android (iPhone user) or MacOS (Linux user).
| That kind of nuanced filtering is hard to express as
| traditional rules but trivial for an LLM.
| loveparade wrote:
| But can't you do the same using appropriate MCP servers with
| any of the LLM providers? Even just a generic browser MCP is
| probably enough to do most of these things. And ChatGPT has
| Tasks that are also proactive/scheduled. Not sure if Claude
| has something similar.
|
| If all you want to do is schedule a task there are much
| easier solutions, like a few lines of python, instead of
| installing something so heavy in a vm that comes with a whole
| bunch of security nightmares?
| j16sdiz wrote:
| OpenClaw allow the LLM to make their own schedule, spawn
| subagents, and make their own tool.
|
| Yes, basically just some "appropriate MCP servers" can do.
| but OpenClaw sell it as a whole preconfigured package.
| sReinwald wrote:
| > But can't you do the same just using appropriate MCP
| servers with any of the LLM providers?
|
| Yeah, absolutely. And that was going to be my approach for
| a personal AI assistant side project. No need to reinvent
| the wheel writing a Todoist integration when MCPs exist.
|
| The difference is where it runs. ChatGPT Tasks and MCP
| through the Claude/OpenAI web interfaces run on their
| infrastructure, which means no access to your local network
| -- your Home Assistant instance, your NAS, your printer. A
| self-hosted agent on a mac mini or your old laptop can talk
| to all of that.
|
| But I think the big value-add here might be "disposable
| automation". You could set up a Home Assistant automation
| to check the weather and notify you when rain is coming
| because you're drying clothes on the clothesline outside.
| That's 5 minutes of config for something you might need
| once. Telling your AI assistant "hey, I've got laundry on
| the line. Let me know if rain's coming and remind me to
| grab the clothes before it gets dark" takes 10 seconds and
| you never think about it again. The agent has access to
| weather forecasts, maybe even your smart home weather
| station in Home Assistant, and it can create a sub-agent,
| which polls those once every x minutes and pings your phone
| when it needs to.
| loveparade wrote:
| But if you run e.g. Claude/Codex/opencode/etc locally you
| also have access to your local machine and network? What
| is the difference?
| rustyhancock wrote:
| I have a few cron jobs that basically are `opencode run` with
| a context file and it works very well.
|
| At some point OpenClaw will take over in terms of it's
| benefits but it doesn't feel close yet for the simplicity of
| just run the job every so often and have OpenCode decide what
| it needs to do.
|
| Currently it shoots me a notification if my trip to work is
| likely to be delayed. Could I do it manually well sure.
| rafram wrote:
| But this could be done for 1/100 the cost by only delegating
| the news-filtering part to an LLM API. No reason not to have
| an LLM write you the code, too! But putting it in front of
| task scheduling and API fetching -- turning those from
| simple, consistent tasks to expensive, nondeterministic ones
| -- just makes no sense.
| sReinwald wrote:
| Like I said, the first examples are fairly trivial, and you
| absolutely don't need an LLM for those. A good agent
| architecture lets the LLM orchestrate but the actual API
| calls are deterministic (through tool use / MCPs).
|
| My point was specifically about the news filtering part,
| which was something I had tried in the past but never
| managed to solve to my satisfaction.
|
| The agent's job in the end for a morning briefing would be:
| - grab weather, calendar, Todoist data using APIs or MCP
| - grab news from select sources via RSS or similar, then
| filter relevant news based on my interests and things it
| has learned about me - synthesize the information
| above
|
| The steps that explicitly require an LLM are the last two.
| The value is in the personalization through memory and my
| feedback but also the ability for the LLM to synthesize the
| information - not just regurgitate it. Here's what I mean:
| I have a task to mow the lawn on my Todoist scheduled for
| today, but the weather forecast says it's going to be a bit
| windy and rain all day. At the end of the briefing, the
| assistant can proactively offer to move the Todoist task to
| tomorrow when it will be nicer outside because it knows the
| forecast. Or it might offer to move it to the day after
| tomorrow, because it also knows I have to attend my
| nephew's birthday party tomorrow.
| fassssst wrote:
| That's ChatGPT Pulse
| stavros wrote:
| I couldn't really use OpenClaw (it was too slow and buggy), but
| having an agent that can autonomously do things for you and
| have the whole context of your life would be massively helpful.
| It would be like having a personal assistant, and I can see the
| draw there.
| lxgr wrote:
| One significant advantage over Claude/ChatGPT is that your own
| agent will be able to access many websites that block cloud-
| hosted agents via robots.txt and/or IP filters. This is
| unfortunately getting more common.
|
| Another is that you have access to and control over its memory
| much more directly, since it's entirely based on text files on
| your machine. Much less vendor lock-in.
| jarboot wrote:
| I spun up an Debian stable ec2 vm (using an agent + aws cli +
| aws-vault of course) to host openclaw, giving it full root
| access, and I talk to it on discord.
|
| It's a little slow sometimes, but it's the first time I've felt
| like I have an independent agent that can handle things kind
| of.
|
| The only two things I did were 1. Ask it to create a Monero
| address so I could send it money, and have it notify me
| whenever money is sent to that address. It spun up its own
| monerod daemon which was really heavy and it ran out of space.
| So I had to get it to use the Monero wallet instead, but had to
| manually intervene to shut down the monerod daemon and kill the
| process and restart openclaw. In the end it worked and still
| works. 2. I simply asked it "@ me the the silver price every
| day around 8am ET" and it just figured out how to do it and
| schedule it. To my understanding it has its own cron
| functionality using a json file. 3. Write and host some python
| scripts I can ping externally to send me a notification
|
| I've had it done other misc stuff, but ChatGPT is almost always
| better for queries, and coding agents + Zed is much better for
| coding. But with a cheap enough vm and using openrouter plus
| glm 4.7 or flash, it can do some quirky fun stuff. I see the
| advantage as mainly having control of a _system_ where it can
| have long term state (like files, processes, etc) and manage
| context itself. It is more like glue and it 's full mastery and
| control of a Linux system gives it a lot of flexibility.
|
| Think of it more as agent+os which you aren't getting with raw
| Claude or ChatGPT.
|
| I've done nothing that interesting with it, it's absolutely a
| security nightmare, but it's really fun!
| FergusArgyll wrote:
| The main novelty I see in openclaw is the amount of channels and
| how easy it is to set them up. This just has whatsapp, telegram &
| feishu
| tunney wrote:
| Has anyone managed to get the WhatsApp integration working and
| chatting that way?
| Aeroi wrote:
| can anyone breakdown a comparison of multi-agent vs subagent?
|
| looking for pro's and cons.
| Tepix wrote:
| What are your solutions for if your AI bot wants to leak your
| credentials?
| manwithmanyface wrote:
| Is this something I run for my company in Slack, where employees
| send messages and the LLM processes the text, uses the functions
| I created to handle different tasks, and then responds back?
| sally-suite wrote:
| Not bad, but I'm a bit skeptical. Is it mainly about the way of
| working in IM?
| yberreby wrote:
| Watching the OpenClaw/Molbot craze has been entertaining. I
| wouldn't use it - too much code, changing too quickly, with too
| little regard for security - but it has inspired me.
|
| I often have ideas while cleaning around, cooking, etc. Claude
| Code (with Opus 4.5) is very capable. I've long wanted to get
| Claude Code working hands-free.
|
| So I took an afternoon and rolled my own STT-TTS voice stack for
| Claude Code. The voice stack runs locally on my M4 Pro and is
| extremely fast.
|
| For Speech to Text, Parakeet v3 TDT:
| https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3
|
| For Text to Speech, Pocket TTS: https://github.com/kyutai-
| labs/pocket-tts
|
| Custom MCP to hook this into Claude Code, with a little bit of
| hacking around to get my AirPods' stem click to be captured.
|
| I'm having Claude narrate its thought process and everything it's
| doing in short, frequent messages, and I can interrupt it at any
| time with a stem click, which starts listening to me and sends
| the message once a sufficiently long pause is detected.
|
| I stream the Claude Code session via AirPlay to my living room
| TV, so that I don't have to get close to the laptop if I need
| extra details about what it's doing.
|
| Yesterday, I had it debug a custom WhatsApp integration (via [1])
| hands-free while brushing my teeth. It can use `osascript` for OS
| integration, browse the web via Claude Code's builtin tools...
|
| My back is thankful. This is really fun.
|
| [1]: https://github.com/jlucaso1/whatsapp-rust
| gdhkgdhkvff wrote:
| On one hand, I think this project is super cool and something I
| would use and/or would have loved to build myself for my own
| use.
|
| On the other hand, it makes me wonder if we're just heading for
| a future where everyone is just always working, at all times,
| even while doing other things.
|
| "Wow look at our daughter taking her first steps! She's doing
| so... wait hold on... No, Claude. I said to name the class
| "potatoes", not "'pot' followed by eight 'O's," you dumb
| robot!"
| volkk wrote:
| we kind of already are with our phones and Slack, the
| difference at this point is negligible. i personally won't
| have airpods in 24/7 with my kid (or ever) so if i were doing
| something like this, it would be through my phone, which is
| already something i use fairly often. not too much difference
| there IMO (at least anecdotally speaking)
| orsorna wrote:
| I don't know what kind of work you do on a daily basis.
| But, the difference between sending a Slack message and
| sending a message to kick off an agent to chain a bunch of
| tasks together is a vastly lower activation barrier. I
| think many people will jump over that lower barrier out of
| FOMO, to avoid being outcompeted by those who already
| jumped.
|
| As an IC though, me sending a slack message is perhaps less
| impactful than a PL responding to a report :)
| htrp wrote:
| you basically just described management, where you send a
| slack message and kick off a bunch of tasks to your team
| mpolichette wrote:
| I don't disagree, but I think there is the otherside of that
| same coin... What if we could do other stuff while remaining
| productive.
|
| Rather than the example of missing first steps, what if we
| had, "Ok Claude, prepare a few slides for my presentation,
| I'm going to watch my childs mid-day recital..." maybe you
| get a success/failure ping and maybe even need to step out
| for part of the event, but in another world you couldn't have
| gone at all.
| orsorna wrote:
| I expect the opposite, where if you are not exploiting your
| newly freed time with more work, you will be left behind.
|
| This is the premise of the comic _Power Nap_.
|
| https://www.powernapcomic.com/powernap/
| Jommi wrote:
| repo?
| vmbm wrote:
| I got into a bike accident yesterday and injured both of my
| arms. Fortunately the damage wasn't too severe, but it was bad
| enough that using a computer is rather difficult. So now I'm
| spending some of my idle time playing around with different
| options for voice control. Like you I am a little wary of
| OpenClaw so I might try something similar to your setup as an
| alternative. So far I have gotten to the point where I can use
| voice dictation in notepad to write comments and commands, but
| copying and pasting the text is enough of a struggle
| (compounded by the fact that my cat is competing with me for
| the keyboard and I am in no state to fend her off) that I am
| aiming to push things a bit further. Sucks being injured but
| having a nice distraction to keep my mind occupied has so far
| been a great way to pass the time.
| lxgr wrote:
| Can this be sandboxed? I've been running OpenClaw in a VM on
| macOS, which seems more resource intensive than necessary.
| cpursley wrote:
| I'd like to see one of these in Rust (over Python, Node, etc) and
| in Apple's container environment.
| raphaelmolly8 wrote:
| The 4k LOC claim is interesting but I think the real insight is
| about what you _remove_ rather than what you keep. Looking at the
| codebase, they 've essentially bet that LLMs with 100k+ context
| windows make most RAG pipelines redundant - just give the agent
| grep/rg and let it iterate.
|
| What's clever is treating memory as filesystem ops rather than
| vector stores. For codebases this works great since code has
| natural structure (imports, function calls) that grep
| understands. The question is whether this scales to truly
| unstructured knowledge where semantic similarity matters.
|
| Would love to see benchmarks comparing retrieval accuracy vs a
| proper embedding pipeline on something like personal notes or
| research papers.
| mrklol wrote:
| Didn't openclaw switch to vector based because it used way less
| tokens as it always loaded all memories? Seems way more
| efficient
| pawelduda wrote:
| What? OpenClaw has 450kLoC? Why?
| halfax wrote:
| Bottom Line HAL-AI-2 is a real system. Nanobot is a toy. They are
| not peers. They are not even in the same category. Nanobot is
| useful only as a conceptual sketch of an agent loop. HAL-AI-2 is
| the substrate you've been building toward for months.
| resonious wrote:
| I hate to side-track like this but I'm having trouble
| understanding the architecture diagram. LLM has 2 arrows to Tools
| - what does that mean? Similarly, Tools has both a doublesided
| arrow and an outgoing arrow to Context. Chat Apps having outgoing
| arrows to both Message and LLM also _kinda_ tripped me up but I
| suppose you could say it 's because the apps both provide
| messaging and context for the LLM.
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