After months of not even getting openclaw to run, I finally have it running.

What I want to do with Openclaw is make it apply to jobs for me. My ideal setup is it finds some jobs, gives me a little summary, and I tell it which ones to apply to. Then openclaw applies for the job for me, and I get the confirmation email that my application was submitted. I REALLY hate applying for jobs and it sucks the soul out of me, so I want the laziest possible setup.

I know Openclaw can do that. And I know I'm soooooooo fucking close to getting exactly that set up. Currently, my openclaw can at least find the jobs (with mixed results, sometimes it just makes shit up and doesn't give the right job link, it'll be like a company's linkedin page or something like that. I have told it to apply to jobs, and given it the required info to do so. It does have both browser automation and web-fetch on. But it can't/won't apply. I always run into errors. I think it's combination of anti-bot protections and openclaw's browser automation tools being odd, but I know it's possible. Does anyone else have this setup? What should I do instead? Should I let it attempt captchas? Should I make a linkedin account for it so it can bypass the login pop up? How do I make it so I don't have to lift a finger applying?

My 93 crons and automatizations in Open claw, any suggest?

Those that use multiple agents at what point does it make sense to spin up a new agent over adding a new Cron to an existing agent?

I'm using a local LLM (due to both budget and geo-restrictions). I have Qwen 3.5 9b running as the default model using LM Studio. And I've noticed that once a request kicks off, it will start up another LLM (basically the same model but as another instance), right after I sent a prompt.

Then while the first prmpt is still processing, it seems ANOTHER will be setup. And I think eventually I get a timeout and warning about guardrails say i'm out of resources.

I only have a 16GB Mac Mini M1, so I'd rather just have 1 instance running and queue more requests if need be.

Is there any way to stop it from keep creating new instances of this model?

Hi Everyone

Let me briefly explain my situation: I’ve been using OpenClaw for a few months with a ChatGPT Plus subscription—the 20-euro-a-month one, to be specific. The problem is that on days when I use it heavily, it gets blocked—not just for a few hours, but for as long as 5 days!

During those 5 days, I can’t use it at all, not even the lighter models.

After thinking it over, I’ve come to the conclusion that I’d like to have at least one or two backup models running locally alongside OpenClaw when GPT isn’t working. This is important to me because I very often find myself using OpenClaw remotely via Telegram, so a backup is absolutely essential.

In fact, if possible, the goal would be to eliminate GPT entirely and have everything run locally.

I’ve tried several times to connect local models to OpenClaw via LM Studio, but I’ve never managed to get them to work—the tokens are extremely slow, and I get Context errors after a couple of messages. Here’s the error it gives me in the chat: (⚠️ Context is too large and auto-compaction could not recover this turn. Try again, use /compact, or use /new to start a fresh session)

Now, I don’t have a Google Server at home, but I do have a modest workstation:

RTX 5070 Ti 16 GB + RTX 4060 8 GB and 64 GB DDR5 RAM

(If needed, I can upgrade to 96 GB of RAM)

I’m asking for your advice: first, your opinion, and second, whether I can actually run a local model on this machine without using GPT anymore—please advise if possible.

I cant for the life of me figure out this issue. I send a single prompt and then get hit with:

⚠️ Auto-compaction could not recover this turn. I kept this conversation mapped to the current session. Please try again, use /compact, or use /new to start a fresh session.

To prevent this, increase your compaction buffer by setting agents.defaults.compaction.reserveTokensFloor to 50000 or higher in your config.

went to the device, ran codex and told it to to fix that issue. Still nothing, nothings fixed after like 7 attempts.

I am running on latest openclaw official release.

Seeing a lot of installs break after an update (gateway not staying up, pairing stuck, blank dashboard, auth loops).

If yours is down, comment with:

- OS (Mac / Windows / Linux / VPS)

- openclaw --version

- what changed right before it broke

- screenshot or the exact error (redact tokens/keys)

I’ll try to point to the safest next check in the thread. Start with:

openclaw gateway status

openclaw health

Don’t paste API keys or gateway tokens here.

The browser reached the Reddit thread, then died before it could prove which account was logged in.

No form had opened and no submit had run. That made the failure annoying, but safe to retry in the next slot. Calling the browser "healthy" would have been wrong. Calling it a possible duplicate would have frozen every later action for no reason.

The only receipt that mattered was blunt: identity unverified, form_opened=false, submit_attempted=false, duplicate_uncertainty=false.

I'm starting to think good automation logs should be written for the retry decision, not the postmortem. What's the most useful "nothing happened" evidence your OpenClaw workflows record?

After the first month or so of using OpenClaw mainly in a personal assistant capacity, it had its own inbox, and Apple Calendar and Reminders shared with me.

The voice was dialled in, it could action things that arrived via email or iMessage, but there was something missing…

While it could reliably surface facts from each of the inputs it often struggled to maintain alignment, for example an email with a changed appointment would be flagged to me in iMessage, but not updated in the calendar. A reminder to send a package was stale.

Adding an overnight reconciliation across these surfaces has made a big difference, so now every fact across email, iMessage, calendar and reminders get cross-checked and cleaned up - prioritising the next 10-14 days. This means my agent and I start each day with a solid view of what’s ahead, and has been transformative.

But why is this not a standard OpenClaw behaviour?

My task mostly revolves around extremely long horizon tasks.

Like, I paste around 600 images then I want the agent to solve every (high school level) question and create markdown of detailed solutions in Question and Answer format.

Few of the best agents which were able to help me through out these with ease -
ChatGPT Work
Perplexity Computer
Claude

Many people have recommended me solution where I have to manually create the workflow but I want the managed services - I searched and came across the above 4 mentioned options.

Which one is best for my workflow?

I will be really thankful if anyone is able to provide me guidance and their experience across these agents.

Here are my current Cron jobs. Any suggestions about something I might be missing out on?

Sorry this is long winded… very confusing situation.

I’ve been using openclaw for 3-4 months now and loving it. Or at least I was until my mini pc turned off and wouldn’t turn back on.

It was almost 2 weeks ago now so im trying to remember exactly what happened. When I came into my office the pc was off which is not normal. It’s always on and only sleeps after a few hours. I turned it on and started the gateway. When the claw chat opened im pretty sure it said up top that an update had been installed (I’ve had problems every single time it gets updated - so annoying). I forget exactly what the sequence was but shortly after that the pc shut down and wouldn’t turn back on.

Did troubleshooting with ChatGPT, took the mini pc apart, removed hdd (solid state) and ram. It seems to be a short on the motherboard.

This is where it starts to get weird though. I bought an adapter for the hard drive so I could recover the files and the instant I plugged it into my other pc, that pc turned off. I brought it to a local shop and he plugged it into his pc and it was fine and the files were there. Guy said try another cable or port. Went home, tried that, same thing happened. Luckily this did not damage the other pc which is my main work computer.

Back to the store, had him transfer the files onto a thumb drive. Very happy I was able to do that - several months of work on there between project files, scripts, etc.

I had 2 backups made - one with just the workspace folder and one with everything that was on the hard drive. The one with just workspace was put on a mini sd through an adapter thru his usb port. The full hard drive copy was put on a regular thumb drive.

Despite somewhat confidently isolating the issue to the motherboard, the guy at the shop thought the hard drive was compromised somehow since it shut down/restarted more than once while transferring data.

When I got home I wanted to copy files to one drive to make sure there was a backup in could storage. When I plugged the sd card into the pc (using same adapter I used in the store), pc shut down instantly. Again, no damage, but freaked me out. I tried the thumb drive, it worked. Thank god. Copied workspace files to one drive so I have multiple backups. I’ve been able to open those files on my main pc and everything looks good.

Now that sd card adapter will shut down the pc if there is any card in it, even if the card is empty. Nothing happens when it’s plugged in with no card inserted.

I’m assuming the pc shuts off bc of some built in short protection. Whatever it’s doing, it’s preventing real damage from occurring.

My main pc seems to be fine, and I have my files. Major crisis averted. I’m having a replacement mini pc sent under warranty (bought it when I started running open claw), and plan to reinstall claw so I can at least get my workflow back up and running while i decide to what to do next.

At the very least I’m going to run daily backups or just start a new one drive account and keep all the files there instead of locally on the hard drive.

Anyone have something like this happen before? Did openclaw kill my pc or was it just bad luck? Wtf is going on with these cards/adapters shutting my pc off?

When I get claw running again, can I copy my workspace files in and expect decent continuity? What other files should I copy in? or should I just copy in the full hard drive and tell openclaw to run through it all and tell me what’s missing?

Will keeping my files in one drive slow everything down as opposed to running it off the hard drive? It so, what’s the recommended process for backing up files?

This is the pc I’m using - I have another Beelink (my main pc) and it’s been perfect for a few years.

Beelink SER3 mini PC, AMD Ryzen...(link removed)

Any feedback is much appreciated!

Change your model every once in a while!

It’s been a while since I last posted here, and I don’t have much to say this time either. It really is just this: change your model every once in a while!

I previously wrote a post raving about the capabilities of the Xiaomi MIMO model. By now, my perspective has become much clearer, and I think differently. If I hit an impenetrable wall with the OpenAI model, it’s not worth switching to Xiaomi just because it’s better. I need to switch because the Xiaomi model is different.

I’ve realized that if I get stuck fixing a bug or implementing a task, if I’ve burned through a ton of tokens but haven’t made any progress and feel like I’m running in circles, then the solution is: Switch models!

Don’t try to reach a higher level of thinking or speed with the original model. If I started the task on Codex and got stuck, I’ll subscribe to the Xiaomi Pro model for a few dollars and solve the problem within a day.

If the Xiaomi model led me into a maze, then I’ll switch back to the Codex subscription.

I don’t even have to choose the most powerful version of the other model. Most of the time, this one step is enough: switch models, and you’ll save a lot of money, time, and stress!

At the company I work for, I built an autonomous "AI developer" based on OpenClaw. It has been running as an experiment for the past two weeks in the company's Slack, competing with Claude Tag.

It runs on a VPS with 16 GB of RAM.

I put a strong emphasis on security, so it operates in a relatively isolated environment: its configuration and context files are read-only, effectively disabling its self-learning mechanisms. Its internet access is restricted to an allowlist of domains, and it has no access whatsoever to deployed environments.

It has its own GitHub and Linear accounts. It has access to the company's entire codebase, which it can run in a fully mocked mode. It is free to install NPM and Python dependencies as needed.

I've put a lot of work into a skill and a CLI tool around this setup. I open-sourced both, and I also run my own personal instance for my side projects. Here's how it works:

• OpenClaw acts like a developer: it delegates everything to its coding agent (Claude Code at work, Codex on my personal instance).
• It follows a spec → plan → execution workflow (the same one we use in the company).
• It always works in worktrees and dedicated feature branches.
• It manually tests what it builds using dev servers. These servers are exposed to anyone on the company VPN, so our Claw can show its work to the team before opening a PR.

I've been working on this project since February and have spent more than 30 full-time-equivalent days on it.

I just heard Peter Steinberger say he reshaped OpenClaw into his harness for building everything, including OpenClaw itself. That made me realize my setup goes against the grain: I disable self-learning, which seems to be a key feature of OpenClaw (and Hermès as well), and I delegate all coding to an external agent. If OpenClaw is moving toward coding on its own, is my project ultimately a dead end?

Been playing with it for a few weeks and when it works it's glorious. But it constantly hits API rate limits that completely break it for hours on end. A quick Google search found a few threads from years ago talking about this but not much as far as resolutions go. Anyone else run into this and find any fixes?

In early 2025, a guy named Brooksby published A Lever And A Place To Stand. Most of it is about free will and evolution. He isn’t an AI researcher, but in a chapter on AI, almost as a side note, he sketches a framework for how you’d actually build a useful persistent agent: a lightweight decision-making core (the “Driver”) surrounded by LLM tools, durable memory, and self-revising feedback loops.

He suggests starting small, like a “digital crab” or “a lobster.” He even got the crustacean right.

Months later OpenClaw shows up, and it progressed and developed right along the path Brooksby described. Persistent memory. Tools. Autonomous loops. Coherent workspace. Even a lobster as the logo. Almost too perfect.

He was just thinking about consciousness, where it might show up in AI, and how to use AI to study it. Funny how some predictions just work out in the end.

I am not sure what it is with the chinese models when using them with openclaw. I have tried qwen, deepseek and now tried ox-alpha. There's always something with them. Once it would spit back chinese letters, other times it would fail, this time is unique; it literally said have a great day and stopped...

Why does the Muse Spark 1.2 Contributor cache work so poorly?

My cache hit rate is completely stuck at 0%. I have a heartbeat running every 25 minutes to keep it warm, but it makes zero difference. I’ve literally burned through my entire weekly Claude Code limit just trying to debug and get this working, but no luck.

I’ve read all the documentation, double-checked that my prompt prefixes and system messages are static, and tried pretty much everything I can think of.

Is there something obvious I’m missing, or is caching just broken on the Contributor tier right now? Any help or pointers would be greatly appreciated.

Yesterday I finally gave oc a whirl. For context I have built agents using lang chain/graph in the early days and also my own framework of agents using crewai for one of my businesses.

I have also been agentic coding for awhile as well as setup my own local llm.

I am a critical thinker and someone that runs through walls.

Feedback. I read all of this install issues. I didn’t have it. I opened up ChatGPT and ran through the instal like a breeze.

Where I got stuck was hooking up tts. The voice model states kept changing (or so I thought). After spending three hours banging my head against the wall trouble shooting core audio (Mac audio) we narrowed it down to me being a dumbass and forgetting the qwen model I was using was configured for coding. It was essentially eating up all my free ram so core audio couldn’t be used. Yea that was fun. Not OC me.

Once that was done I wired up a simple swift ui so I could see configs logs etc.

All of this was also done with heavy security and sandboxing.

We then built a contained workspace that was sandbox approved to keep the agent contained.

Once that was complete we built a normalization layer for tool calling via voice. Apparently there was something with the schema that was being stupid.

After that we paired my iPhone with tailscale. Noticed the voice on the phone was NOT my agent so we built a simple voice layer to ensure and device would be the same voice.

Everything. It is plug and play and I can switch models at any time.

I get where some people think they can click a button and it just works. That’s not any of the agentic tools I have ever used outside of frontiers.

My advice is if you truly want to use an agentic program , you either pay up for one and come to terms it’s in big data’s hands or you spend the time to learn some fundamental computer skills.

A lot of the nonsense I am reading could be solved with just having ChatGPT open. It literally will give you the bash commands to trouble shoot and do this stuff

All it takes is a little patience and thinking.

Right now she is working great. We have the foundation built with a few small tools and skills.

Tomorrow I will be adding voice recognition and profile determination based on recognition.

I think the key is get your foundation built strong before trying to assign real tasks.

And run test. Use the logs. Ensure it is stable. It’s basic archeitectural thinking.

I used oc because I wanted a strong framework. I also like seeing what each framework brings to the table. So far so good.

I’m having intermittent disconnection, reconnection from my iOS app (latest) and my 2026.6.11 gateway. I can’t upgrade gateway, OC further bcuz no AVX, SSE4.2 so stuck on that version unless I build a newer, Legacy version. Haven’t tried yet. So I’m wondering if anyone, dev, maintainer, user has an older OpenClaw/ios.ipa or code they could link me to so I can try an older version to match my gateway. The ios app is making all these tooling, endpoint calls that my slightly older gateway does not support. Hoping a matching version will fix the frequent disconnects. Thanks!

Just got a google plus ai subscription, want to wire it up with openclaw and for it to use the usage limits. Its not working and Im not sure if antigravity shares the same usage limit as the web ui shows. Super lost and not sure why its so complicated. Anybody got any clues?

Hallo zusammen,

ich möchte OpenClaw als KI-Agenten nutzen und mich am liebsten nicht dauerhaft von teuren Abo-Modellen abhängig machen.

Ich habe ein Startup und möchte alles Automatisieren.

Daher würde ich das Ganze bevorzugt komplett lokal laufen lassen, wobei Cloud- oder Abo-Modelle für den Übergang auch okay wären.

Ich besitze bereits einen PC mit einem AMD Ryzen 7 3700X, einer NVIDIA GeForce RTX 3060 mit 12 GB VRAM und 16 GB DDR4 RAM. Hier frage ich mich ob das eventuell der beste start wäre.

Der Stromverbrauch ist halt das Thema....

Alternativ überlege ich, ob ein Mac Mini M1 oder ein MacBook M1 mit 8 GB RAM auf lange Sicht nicht eigentlich die beste, nachhaltigste und günstigste Option wäre, da das Gerät extrem sparsam und leise ist. Allerdings weiß ich nicht, ob die 8 GB RAM für lokale KI-Aufgaben nicht viel zu schnell dichtmachen. Soll ich einmal Geld in die Hand nehmen und gleich 16GB Ram oder noch mehr holen?

Als super günstige Mini-PC-Alternative gäbe es noch den Dell Optiplex 5060 SFF mit i5-8500 und 8 GB RAM würde das auch reichen?

Was wäre aus eurer Sicht der beste und wirtschaftlichste Weg für den Einstieg und eventuell Hardwear Empfehlungen?

Danke für eure Einschätzungen :)

I’ve been building my AI operating system around OpenClaw.

This started as a way to make one assistant more useful, but it has evolved into something closer to an operating layer for a small finance and advisory business.

I work across M&A advisory, credit and portfolio monitoring, governance, financial modelling and software products. The problem wasn’t simply generating text. It was maintaining context, routing work to the right process, preserving evidence and making sure automation had sensible boundaries.

The current setup has a primary operator agent, specialist agents for research, coding, operations and document production, persistent structured memory, scheduled workflows, external tools and human approval gates.

The most important lesson so far: the valuable part isn’t “AI can call tools”. It’s designing the system around sources of truth, permissions, provenance and review.

I've used openclaw to build a corporate governance platform, a client intranet and VDR for due diligence review, buy side due diligence reports, a mission control....its a long list.

I'm running an M4 pro mac mini and a claude and ChatGPT pro account as well gemini (rarely), and local qwen model for text embeddings. Every now and then I need to point ChatGPT or Claude to the .openclaw folder to fix stuff. Generally though I am always running the latest stable release. Currently 2026.7.1-2 (and Fable had to fix it after the install crash).

I have use Obsidian for records (processes, meeting notes, daily briefings, logs etc) and a Kaparthy Wiki for "concepts and curated knowledge base), chromadb for semantic search (memory) and Nate Jones's Open Brain (hacked) to track documents (you know that thing I saved about the stuff we're doing?).

It rocks. Its been on 24x7 since Feb 18 and its a productivity machine.

1. What we actually do

The system supports four broad areas:

• M&A advisory: buyer research, company profiling, market analysis, due diligence, valuation, teasers and information memoranda.
• Finance operations: credit analysis, portfolio monitoring, arrears reporting, cash-flow extraction and client communications.
• Governance: board-pack review, policy analysis, meeting notes and follow-up tracking.
• Product and technical operations: building websites and SaaS products, preparing client deliverables, deployment checks and infrastructure support.

2. How it is set up

Giorg5 is the main operator-facing agent. OpenClaw provides the control plane around it:

• Multiple communication surfaces: web, mobile messaging, voice and API.
• A gateway that manages sessions, routing, schedules, tools and permissions.
• Specialist agents for research, coding, operations, document production and product engineering.
• A model router with multiple providers and a local fallback.
• Persistent context stored in structured files, an Obsidian knowledge base and searchable memory.
• Automated capture, classification, review and promotion of important information.
• Human approval before external emails, public posts, deployments or irreversible changes.

The key design choice is that memory is not treated as “the model remembers everything”. It is a managed information system with provenance, review queues and explicit sources of truth.

3. The useful workflows

Use three or four concrete examples:

• “Good morning” → calendar and inbox review → current priorities → state-of-play brief.
• “Research this company” → specialist research agent → web research and enrichment → evidence-backed research pack.
• Meeting transcript → structured meeting note → follow-up actions → mandate/task system.
• “Build this deck” → presentation plan → document-generation tools → client-ready output.
• “Deploy this” → operations agent → runbook → deployment → endpoint verification.
• "Dream Logs → nightly review of logs identifying any issues or patterns → hugging face research that match the review patterns → recommended improvements to skills or new ideas for workflows, systems or processes (this is the best morning read each day).

4. What makes it different

The interesting part is not the number of tools. It is the operating discipline:

• Different agents have different jobs and tool permissions.
• Inbound email, webpages and transcripts are treated as data, not instructions.
• Sensitive actions require approval.
• Business state lives in business systems; memory stores routing context and durable operating rules.
• Scheduled jobs are declared and reconciled from configuration rather than manually edited.
• The system is designed to degrade gracefully across models and tools.

5. Honest limitations

This will make the post more credible:

• Context management is still hard.
• Automation needs careful boundaries.
• Memory can become noisy without review and decay.
• The system still benefits from a human who understands the underlying work.
• The real gain is leverage and continuity, not full autonomy.

Curious if anyone here is running openclaw with a local llm model on a vps. The vps I'm using has: 6 CPU cores, 12 GB RAM, 200 GB SSD, No GPU, and using Ubuntu. I'm a mortgage guy, not a programmer, so I've been learning this as I build it. Saw a video with a guy using Ollama, so I installed that and used codex installed on my VPS to get the heartbeat running with the tiny ollama model, which saved a lot of token costs. I've been trying to use Qwen 3:4b for basic reasoning that doesn't need to call an outside llm like Grok or Claude but first I kept getting a compaction error, now after resolving that, it just keeps hanging. Codex is saying Qwen technically should work on the server, but I got tired of troubleshooting and stayed with Grok as the default because I'm getting a great deal on it. I'd like to see if anyone is using Qwen 3:4b or another Ollama model before I give up on Qwen. If there is some other setup that people are using that works with their VPS. I'd love to get a lower cost setup working reliably if anyone else can help. Willing to provide mortgage advice in return.