OpenClaw’s memory is unreliable, and you don’t know when it will break

aleksiy123

I do feel like the memory the biggest hurdle I’ve been encountering and I’m curious what solutions people have been doing to make it work. What seems to be somewhat working for me 1. Karpathy wiki approach 2. some prompting around telling the llm what to store and not. But it still feels brittle. I don’t think it’s just a retrieval problem. In fact I feel like the retrieval is relatively easy. It’s the write part, getting the agent to know what it should be memorizing, and how to store it.

Animats

"Who's in charge here?" "The Claw." Some of this stuff is starting to look like technologies that worked, looked promising, but were at best marginally useful, such as magnetohydrodynamic generators, tokamaks, E-beam lithography, and Ovonics.

choiway

Good to know that I'm not alone. I now use it for music recommendations (not so great) and keeping track of restaurants I want to try (really good at this but so are a lot of other apps).

jbverschoor

Sounds like an armchair expert

broadsidepicnic

Could we stop with the clickbaiting headlines?

aunty_helen

> 0 legitimate use cases My teams currently using it for: - SDR research and drafting - Proposal generation - Staging ops work - Landing page generation - Building the company processes into an internal CRM - Daily reporting - Time checks - Yesterday I put together proposal from a previous proposal and meeting notes, (40k worth)

thepasch

It would’ve happened eventually anyway, but OpenClaw is basically what kickstarted the beginning of the end of token subsidies. It’s a almost begging to be used wastefully. And agents would miss and lose nothing without it. It’s devoid of a reason to exist.

MadSudaca

It can integrate apis for you on the fly. That’s one of the biggest usecases IMO. Combine that with skills, cron, and sub-agents, and you get a lot of power there.

hackermeows

there are zero legitmate use cases? sure bro. you can say that to my claw which is making me more money than my salary

operatingthetan

I'm using openclaw as a personal development bot, which is pretty useful. It pings me throughout the day using crons to complete tasks and follows up on them. But aside from that, it is a very unreliable piece of software. I'm constantly having to fix it, or track down correct configurations. It can just decide to randomly edit it's own config, uses incorrect json keys and then the whole thing is dead. Or it blows through it's context and doesn't know to compact. Then it's just stuck. I can't wait till it matures or something more reliable comes along.

jwpapi

From my perspective there are some people that have never built real processes in their life that enjoy having some processes now. But agent processes are less reliable slower and less maintenable then a process that is well-defined and architectured and uses llm’s only where no other solution is sufficient. Classification, drafting, summarizing. I’ve had a Whatsapp assistant since 2023, jailbraked as easy assistant. Only thing I kept using is transcription. https://github.com/askrella/whatsapp-chatgpt was released 3 years ago and many have extended it for more capabilities and arguably its more performant than Openclaw as it can run in all your chat windows. But there’s still no use case. It’s really classification and drafting.

estetlinus

Who is this guy and why is he casually admitting to reading all the user conversations???

axus

The twist? This article and marketing campaign for it are 100% by OpenClaw.

littlekey

I'm still trying to figure out what to use it for other than news aggregation...

jmward01

It is an interesting take. I think this is mainly early adoption pains though. This stuff is moving so fast that if you say 'it isn't useful because X isn't good enough' then just wait a month and X will be good enough to find Y as the blocker (or no blockers are left and it truly does become useful). Soon we will see this hooked into the home assistant world well combined with local and remote compute and then we are likely to see real movement.

theturtletalks

The hype around OpenClaw is a bit confusing but I think I figured it out. For most coders, Claude Code in the terminal was an important event. Letting it access code and change files directly. For normal users, they didn’t see the power is that. OpenClaw runs Pi in a terminal and exposes the chat thru Telegram or any chatting app. This gave the ah-ha moment to non-coders that coders had had for 6+ months prior.

the_real_cher

I was getting a lot of use case out of it mainly interacting with the file system. The problem is if not carefully designed it will burn through tokens like crazy.

BeetleB

If you look at my comment history, you'll see what seems to be someone defending OpenClaw (even though I stopped using it). I have some issues with the article, but I agree with some of the conclusions: It's great tinkering with it if you have time to spare, but not worth using weeks of your time trying to get a perfect setup. It's just not that reliable to use up so much of your time. I will say, it's still amongst the best tools to do a variety of tasks. Yes, each one of those could be done with just a coding agent, but I found it's less effort to get OpenClaw to do it than you writing something for each use case. Very honest question: One of the use cases I had with OpenClaw that I'm missing now that I don't use it: I could tell it (via Telegram) to add something to my TODO list at home while I'm in the office. It would call a custom API I had set up that adds items to my TODO list. How can I replicate this without the hassle of setting up OpenClaw? How would you do it? (My TODO list is strictly on a home PC - no syncing with phone - by design). (BTW, the reason I stopped using OpenClaw is boring: My QEMU SW stopped working and I haven't had time to debug).

_pdp_

IMHO, the biggest problem with OpenClaw and other AI agents is that the use-cases are still being discovered. We have deployed several hundred of these to customers and I think this challenge comes from the fact that AI agents are largely perceived as workflow automation tools so when it comes to business process they are seen as a replacement for more established frameworks. They can automate but they are not reliable. I think of them as work and process augmentation tools but this is not how most customers think in my experience. However, here are a several legit use-case that we use internally which I can freely discuss. There is an experimental single-server dev infrastructure we are working on that is slightly flaky. We deployed a lightweight agent in go (single 6MB binary) that connects to our customer-facing API (we have our own agentic platform) where the real agent is sitting and can be reconfigured. The agent monitors the server for various health issues. These could be anything from stalled VMs, unexpected errors etc. It is firecracker VMs that we use in very particular way and we don't know yet the scope of the system. When such situations are detected the agent automatically corrects the problems. It keeps of log what it did in a reusable space (resource type that we have) under a folder called learnings. We use these files to correct the core issues when we have the type to work on the code. We have an AI agent called Studio Bot. It exists in Slack. It wakes up multiple times during the day. It analyses our current marketing efforts and if it finds something useful, it creates the graphics and posts to be sent out to several of our social media channels. A member of staff reviews these suggestions. Most of the time they need to follow up with subsequent request to change things and finally push the changes to buffer. I also use the agent to generate branded cover images for linkedin, x and reddit articles in various aspect ratios. It is a very useful tool that produces graphics with our brand colours and aesthetics but it is not perfect. We have a customer support agent that monitors how well we handle support request in zendesk. It does not automatically engage with customers. What it does is to supervise the backlog of support tickets and chase the team when we fall behind, which happens. We have quite a few more scattered in various places. Some of them are even public. In my mind, the trick is to think of AI agents as augmentation tools. In other words, instead of asking how can I take myself out of the equation, the better question is how can I improve the situation. Sometimes just providing more contextually relevant information is more than enough. Sometimes, you need a simple helper that own a certain part of the business. I hope this helps.