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.
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.
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.
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?
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.
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.
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.
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?
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.
"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.
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)
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.
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.
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.
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.
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.
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.
I've been leaning towards multi agent because sub agent relies on the main agent having all the power and using it responsibly.
Totally useless indeed.
RAG is broken when you have too much data.
Gemini with Google search is RAG using all public data, and it isn't broken.
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
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.
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.
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?
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.
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.
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.
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.
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?
It's not even an LLM it's just to pipe api calls.
can anyone breakdown a comparison of multi-agent vs subagent?
looking for pro's and cons.
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.
"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.
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)
The core "design" not bad, but the "code" quality is .. mid.
They are basically keep breaking different feature on every release.
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.
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.
> 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?
Yeah, I guess I just don't really have a lot of meaningful things to take care of.
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.
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.
Okay so is this ”inspired” by nanoclaw that was featured here two days ago?
Has anyone managed to get the WhatsApp integration working and chatting that way?
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