It seems to me that OpenClaw and all its clones are almost useless tools for those who know what they're doing.

It's kind of impressive for someone who has never used a CLI, Claude Code, Codex, etc. Nor used any workflow tool like 8n8 or make.

For these people, asking an AI to create a program or a new tool with a prompt must seem like magic. For those who already use it, it seems like something that simplified the old ones but made them much more chaotic and unsafe.

The only good thing about it is that it made more "ordinary" people interested in these agentic tools. Sending messages via Telegram is much more user-friendly.

It had an insanely meteoritic rise. It felt like it was the only thing anyone had been talking about for months.

Then just, everyone stopped talking about it. Usage based pricing inevitably came and it seems like it was killed over night. Competitors were also rushing to get their alternatives out as well.

So, was OpenClaw just astroturfed? Did it have a legitimate use case or was just hype? Are there still legitimate use cases of people using it?

Edit: Hermes looks cool, I actually didn't know about it before posting this. Still even if you use Hermes or another harness, I'm interested in what kind of actual things you're using it for.

For a split second OpenClaw was all the rage. CEOs were posting about it, reddit was a-buzz with stories of individuals that were automating their entire lives. But then it just died.

I think 2 things happened. First, security was abysmal. And second it wasnt exactly user friendly - the lack of standardization meant every agent needed to somehow standardize without any official guidelines in place.

I've been working on an enterprise quality framework that addresses these two issues, but I want to know from others who used it. What kept it from being great? What things needed to be in place that werent?

I've long wanted to say this, but:

OpenClaw is good, but it's severely overrated.

Most things you can actually do faster yourself. People sometimes even (implicitly) make it out to be as if it's one of the greatest breakthroughs ever or proof that AGI is here (in many extreme fan-boy cases).

We have certainly still not reached the era of agentic assistance. We're still very much in the co-pilot phase, especially when it comes to complex tasks. When it tries to produce solutions to complex tasks, it mostly produces SLOP (especially when not expertly guided); because of the Dunning-Kruger effect, beginners and novices often can't differentiate SLOP from genuinely good content. And the same is true in design and software engineering. There is a big difference between the ability to do something and doing something competently. And because the overuse of AI tends to lobotomise you and makes you overestimate the quality of the work you do, this further amplifies this phenomenon.

For example (not OpenClaw), within the context of design. Can an AI produce a frontend product design that gives beginners the impression they now have Leonardo da Vinci-level artistic thinking? Yes. Is the design actually good? Absolutely not—SoTA AI tends to have terrible design intuition. Doing something ≠ doing it well.

Note*: I mentioned that you can do most things faster yourself, not to completely invalidate the use case for some people of avoiding the work, but rather to invalidate the point of the "doing things significantly faster", which often isn't the case.

The reality is that an AI agent will not transform an undisciplined, lazy person. To make the most out of these kinds of tools, you still need to be conscientious and competent. 

I'd even take it a step further:

The use case of an AI that sends an email is actually a very poor use case. Same as an AI that checks you in for a flight. It's the same for something that is able to handle your inbox, which can often be very ambiguous and unclear, unless you have somewhat of a model of what's inside the person's head and what they want to do with the emails. To get the most out of these models, it often takes a level of hand-holding that is actually inferior and significantly slower than just doing it yourself. 

The kind of personal agentic assistant we are making are not simply plastered-together problems; they are fundamental model problems. As long as we rely on current state-of-the-art systems to be the agentic AI assistants we imagine in movies like Her, we will continue to be producing slop and misleading people into thinking the quality of their work is good. Many AI systems excel (exceptionally, in fact) at explicit knowledge, but they are terrible when it comes to implicit knowledge, and it's the implicit (often complex) knowledge that often makes someone good at their job.

Fundamentally, the hype-to-reality gap is massive.

One thing I would briefly mention is the significance of what OpenClaw represents, and I think it will indeed mark a point in technological history. What it represents, I think, is far greater than the tool itself (a glimpse).

New to the agent game. Didn’t have the space or time to do it before but spent some time last night sandboxing a setup on a dedicated Linux machine.

Using OpenClaw with Codex and a fallback local Ollama model. So far pretty impressed although there are some quirks.

From what I understand about the setup it’s nothing magical, sure. The “Agent” is just some .md files with persistent context to wrap around queries to the model, a workspace folder for scripts, cron jobs, the heartbeat feature which I need to look more into, and tie ins for channels to the agent + ability to run stuff on the machine. I can see a lot of avenues to hack at it with a little know how and the project itself feels well thought out and not super grifty.

I see a lot of hate from people saying they already built out something similar, but even they admit it’s well constructed and has way more features. I’m a SWE and also often hate on things especially if I already did something similar and see a bunch of hype like the whole concept is ground breaking. It IS well delivered and accessible for less technical people and extremely powerful. I’d like to know what I’m missing or if people are just being haters.

My name is Hannes Rudolph and I work at the OpenClaw Foundation. Our initial media attention has faded and some people left after real failures, but npm downloads have grown from about 176,000 a day across February and April to about 422,000 a day across June and July through July 20. That is far from a dead project.

As OpenClaw has scaled scaled, we went through a rough period from April through June when updates broke working installs and too many users spent their time recovering instead of using the product. That damaged trust with people who needed reliability, and I am not going to pretend otherwise. Quite frankly, we are not totally out of the woods yet because v2026.7.1 caused issues with some installs, although it has shown increased overall stability after recovery.

I think the people getting the most out of OpenClaw today are hackers, tinkerers, and businesses willing to put real work into shaping it around their workflows. That includes homelab management, calendars, and job searches, a twice-weekly workflow that surfaced a role one day after it was posted and helped prepare the application that led to an offer, and inventory, purchasing, and other business workflows with varying levels of human oversight.

I also think the bar to getting useful work out of OpenClaw is far too high because onboarding and setup ask too much, day-to-day use needs to be simpler, and stability problems can stop people before they reach those workflows. Our next update focuses on lowering that bar with streamlined onboarding and setup, simpler overall use, and another major round of stability improvements.

To anyone stuck in a “fuck OpenClaw” or “fuck Hermes” mindset, I do not buy the us-versus-them bullshit. The folks at Hermes are great, and if Hermes works for you, good stuff, use it! Turning projects into rival camps creates drama, spreads misinformation, and makes the community hostile to people simply looking for accurate answers and the tool that works best for them.

Criticism is part of how we get better, but unsupported conspiracy theories and personal speculation about the people involved can be hurtful and damaging, and repeating them as fact is not criticism. The claim that OpenClaw was manufactured to get Peter a job at OpenAI has no evidence behind it, and the same goes for other theories about his role there unless evidence supports them. OpenClaw is now stewarded by an independent nonprofit foundation with a full-time team, the source remains public, and Peter still makes many technical calls.

OpenClaw is strong because of the people who build it, review it, test it, report problems, help each other, and keep showing up. We love the hell out of this community, and we will keep listening, strengthening the relationships we already have, forging new ones, and building a harness we know is changing the world. We are not done.

So I spent many, many hours setting OC up. I have it running on a dedicated VPS running with the best free models on OpenRouter.

Now, apart from having a nice companion for regular chat I cannot find any use for OC.

I ask it to send me daily resumes of what is happening on Twitter, Discord, etc. It doesn’t. I ask it to create an application, it doesn’t. I ask it to update its own configuration and it screws everything up. I mean, it’s a good platform to learn about what is possible and how to possibly set up integrations, memory, learn about skills and souls, etc., but actual practical use? I have not seen it (yet).

Plus it’s a huge money pit. Not only the tokens which you more or less can control), but every external tool needs an API token which is mostly a subscription for whatever you want to use (Brave, Browserless, etc).

So yeah, am I missing the point here?

Remember a few weeks ago when Clawdbot/OpenClaw suddenly appeared everywhere all at once? One day it was a cool Mac Mini project, and 24 hours later it was "AGI" with 140k GitHub stars?

If you felt like the hype was fake, you were right

I spent hours digging into the data. They were using the tool to write its own hype posts. It was an automated loop designed to trick SM algorithms, the community and the whole world.

Here is the full timeline of how a legitimate open-source tool got hijacked by a recursive astroturfing campaign.

1. The Organic Spark (The Real Part)
First off, the tool itself is legit. Peter Steinberger built a great local-first agent framework.

• Jan 20-22: Federico Viticci (MacStories) and the Apple dev community find it. It spreads naturally because the "Mac Mini as a headless agent" idea is actually cool.

• Jan 23: Matthew Berman tweets he's installing it.

• Jan 24: Berman posts a video controlling LMStudio via Telegram.

Up to this point, it was real. (but small - around 10k github stars)

2. The "Recursive" Astroturfing (The Fake Part)
On January 24, the curve goes vertical. This wasn't natural.
I tracked down a now-deleted post where one of the operators openly bragged about running a "Clawdbot farm."

• They claimed to be running ~400 instances of the bot.

• They noted a 0.5% ban rate on Reddit, meaning the spam filters weren't catching them.

• The Irony: They were using the OpenClaw agent to astroturf OpenClaw's own popularity on Reddit and X.

Those posts you saw saying "I just set this up and it's literally printing money" or "This is AGI"? Those were largely the bots themselves, creating a feedback loop of hype.

3. The "Moltbook" Hallucination
Remember "Moltbook"? The "social network for AI agents" that Andrej Karpathy tweeted was a "sci-fi takeoff" moment?

• The Reality: MIT Tech Review later confirmed these were human-generated fakes.

• It was theater designed to pump the narrative. Even the smartest people in the room (Karpathy) got fooled by the sheer volume of the noise.

4. The Grift ($CLAWD)
Why go to all this trouble? Follow the money.
During the panic rebrand (when Anthropic sent the trademark notice on Jan 27), scammers launched the $CLAWD token.

• It hit a $16M market cap in hours.

• The "bot farm" hype was essential to pump this token.

• It crashed 90% shortly after.

5. The Aftermath

• The Creator: Peter Steinberger joined OpenAI on Feb 14. (Talk about a successful portfolio project).

• The Scammers: Walked away with the liquidity from the pump-and-dump.

• The Community: We got left with a repo that has inflated stars and a lot of confusion about what is real and what isn't.

TL;DR: OpenClaw is a solid tool, but the "viral explosion" of Jan 24 was a recursive psy-op where the tool was used to promote itself to sell a memecoin.

For the money it will cost you to run OpenClaw, the benefits are significantly weak.

First, it costs you like 50 cents to do like one simple prompt.

Second, if you try to run it local, you need a NASA-level PC.

Third, the security is abysmal. You need to pray that hackers don't find you.

For what? So OpenClaw can press a button for you and send an e-mail?

Am I missing something? It seems godawful.

So everyone lost their minds when the OpenClaw v2026.3 update completely nuked the UI. People were screaming on X, hastily rolling back to v2026.3.11, and claiming the whole project was falling apart. The devs fixed it in 33 minutes. Someone literally just forgot to pack the UI files in the build release.

Classic open-source chaos. But the mass panic over a missing interface exposed something way deeper about the current state of local AI right now. OpenClaw isn't 'crashing' because of a bad pull request. It's crashing because 90% of the user base is fundamentally misusing the framework, and the broader AI ecosystem is getting violently competitive. The founder basically spelled out the actual danger recently, and it has nothing to do with bugs.

Let's get one thing straight immediately. If you are using OpenClaw like it's just a spicier version of ChatGPT, you are doing it wrong. I am seeing this everywhere. People set up a single agent, dump a massive master prompt into it, hand it 15 different tools—web search, code interpreter, file reader—and then act completely shocked when the agent spirals into an infinite logic loop or hallucinates a broken script.

OpenClaw is not a magical business strategy you can just toggle on. Jumping on the tool because some hustle-bro on TikTok said it will replace your whole marketing team is a guaranteed way to burn your time. The real power here is strictly the multi-agent architecture. You need a system. One agent gets one distinct role. Another agent gets specific tools. You have to route the workflow deliberately.

Look at how the independent devs who are actually surviving the token-burn are setting this up. They aren't running single monolithic models anymore. They are running heavily structured, 3-layer military hierarchies. You put Claude Opus 4.6 at the very top as the brain doing the strategic breakdown. Then you pipe the fragmented tasks down to a local execution layer—usually quantized models like Qwen, Gemma, or MiMo—to do the brute force text parsing and daily grunt work. Finally, you maintain a specialist layer running GPT-5.4 just to crack the weird coding roadblocks. That is what OpenClaw was built to orchestrate. If you don't do this, you are leaving 90% of the value on the table and complaining about a tool that you don't understand.

Even with a solid setup, people are getting frustrated by the manual memory management. That is exactly why we are seeing what the Chinese community is literally calling the 'lobster migration' (OpenClaw's mascot is the lobster). Everyone is suddenly looking at Hermes Agent.

Hermes fixes the 'cyber amnesia' that plagues complex agent runs. OpenClaw is incredible at routing, but its native memory management historically required constant hand-holding. Hermes brings a self-evolving loop and dynamic memory natively. It automatically accumulates custom skills without you having to write manual JSON configs every time. Now, the real power users are stacking them: Hermes to tame the local models and handle the memory evolution, and OpenClaw to orchestrate the broader multi-model army.

To be fair, OpenClaw pushed a massive counter-move in the March update to fight back. Hot-swappable memory is officially here. The AI finally doesn't forget who you are midway through a deep coding session. They also rolled out native support for the GPT-5.4 and Gemini 3.1 dual engines, and launched a dedicated plugin store. You can now install skills like apps. It is basically becoming a fully-fledged AI operating system. With over 280,000 stars on GitHub, it is literally outpacing Linux.

But all of this technical progression brings us to the actual, existential danger. Jason Calacanis dropped a bomb on the All-In podcast recently. I usually take his takes with a grain of salt, but I don't think he's acting like a conspiracy theorist here. He stated bluntly that the number one goal of companies like Anthropic and OpenAI right now is to kill OpenClaw.

Think about the mechanics of that for a second. An open-source agent platform is an existential threat to frontier model companies. OpenAI desperately wants you locked into their walled garden, paying for API calls, and using their proprietary agent architectures. Anthropic wants you living entirely inside Claude's artifact system.

If OpenClaw becomes the default Android-like OS for agents, the underlying model becomes totally commoditized. You can swap out GPT-5.4 for a fine-tuned local Llama or Qwen whenever you want. You can run the entire 'lobster' on a flash drive to save on token costs and protect your local hard drive data. One guy recently hooked OpenClaw directly into WhatsApp to negotiate car prices and saved $4,200 without speaking to a human. Another guy bypassed API keys entirely using open-source tools to run it locally without burning a single token.

The big labs lose their moat the second the orchestration layer becomes open and dominant. That is why you are seeing this silent war. The labs are aggressively pushing their own proprietary agent frameworks, trying to starve the open-source alternatives of mindshare, and quietly making it harder to use their APIs for agentic looping. Some creators are even claiming OpenClaw is being 'shadowbanned' or throttled behind the scenes as a coordinated industry harvest.

So no, OpenClaw isn't too complex. It just requires actual engineering discipline instead of mindless tool-jumping. And the reason it feels like you're fighting an uphill battle sometimes isn't just because of bugs—it's because the biggest tech companies on earth have a vested financial interest in making sure open orchestration fails.

The UI bug last week was a minor hiccup. The real test is whether the open-source community can keep the infrastructure resilient enough to survive the API throttling and the corporate walled gardens.

What are you guys currently running for your agent orchestrator? Are you sticking strictly with pure OpenClaw, migrating some workflows over to Hermes, or doing some weird hybrid stack?