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.

Unless I'm misunderstanding what they are, planners seem kind of important.

RAG is broken when you have too much data.

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.

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.

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.

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.

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?

"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.

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.

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.

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.