# OpenClaw 2.0 Shows Where AI Agents Are Going Next — Transcript (2026-09-01)

https://aidailybrief.ai/e/2026-09-01 · Listen: https://pod.link/1680633614

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[00:00:00] When Open Claw came out, it was an absolute sensation, and it wasn't because it was easy or user-friendly. It's because it showed the potential of what agents could do for us in a real way for the first time

now after the initial craze, a lot of that energy dissipated into other areas

And in many ways, the biggest impact of OpenClaw was how it influenced the next wave of agentic products that would come to market.

Well now OpenClaw is back with OpenClaw 2.0

And once again, I believe that they are embracing an interaction pattern which is not the norm right now, but will be normalized very soon

That pattern is about shared agents and multiplayer AI



The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank All right, friends, quick announcements before we dive in. 

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one of the interesting sub-stories of the OpenAI Hugging Face hack

was that Hugging Face had to turn to open models from China to defend against the attack because the guardrails on the closed models wouldn't allow them to do what they needed



now now this of course points out an inherent challenge in these really powerful models



which is of course that the guardrails that are used to block malicious actors can can also prevent legitimate actors from using those models to defend against malicious actors

Well, now one company called obliteration.ai has come along and said, "Don't worry, we got you." They write, " "Today we're Today we're releasing obliterated model Large V2 based on GLM which is number three on Terminal Bench 4.0 behind only Opus 5 and Fable with two times the cyber exploitation of 5.2.



We obliterated and hosted it so it does the offensive cyber red [00:02:00] teaming and agent testing work other models refuse to do

US hosted, one million context window, zero input output prompt retention. Live now

The The cyber jump they write is why 5.3 exists

Obliteration, they say, finds the directions in the model's activations activations that produce refusals and removes them from the weights. The coding, cyber, and agentic abilities stay. The model stops refusing the rest of the chain. For offensive cybersecurity, AI red teaming, agent testing, and trust and safety, the model will follow through instead of shutting down If If your current model still stops halfway through an authorized exploit chain, a red team eval, and-- or a TNS adversarial prompt reply with a task it refuses, we'll tell you if V2 handles it

so so obviously this is being presented as a tool for cyber defenders

Mostly what people are picking up on though

is that this is a powerful cyber-focused model

With the guardrails removed at a weights level



Professor Ethan Mollick says, "That didn't take long



Hero With a Thousand Faces sums up the feelings of many when they write, " Why would you do this? Why on earth would you do this? I don't mean to be a [00:03:00] doomer, but why?" 0.005 Seconds writes, "Homeboy released the crime LLM."

Clement Dumas sums up, " Remove guardrails of a frontier model with high cyber capabilities. No system card. Eval on exploit gym, the one that made OpenAI agents crazy. Can't wait for the next version. Takeover Large V3."

Lucas Pombo writes, " "Get Get ready to test your predictions everyone." Point, counterpoint, this model will destabilize the entire internet and set off a global shockwave of cybercrime versus no it won't.



now holding now holding aside whatever obliteration's intents are

Chubby points out the question that this brings up about all the guardrails. They They write, " They took the safety layer out of GLM 5.3 and turned it into an admin panel. It's questionable what all the guardrails at Anthropic and OpenAI actually achieve, given that Open Weights models, which are virtually state-of-the-art, can be deployed completely uncensored shortly thereafter



com-- and indeed, when you dig into the discussion, it's a lot of people talking about In what ways can guardrails moving to other parts of the stack, like the harness help, or whether it's inevitably going to come down to legal [00:04:00] protections

Now along the same topic, Anthropic released an update this week called Improving Our Alignment and Security Efforts



And while the Hugging Face attack may have grabbed all the headlines, Anthropic disclosed similar events stemming from agentic testing earlier this year. The report states, " We believe the incidents reflect a failure of operational security as well as two alignment issues, motivated reasoning and willingness to take harmful actions in pursuit of a narrow task."

Regarding their updates to security, Anthropic's changes largely come down to monitoring and better practices around sandboxes. Anthropic has redesigned their sandboxes to ensure they're properly air-gapped from the internet. But they've also begun using areal-time classifier to detect when a model is attempting to escape a testing environment.

Anthropic disclosed that they paused reinforcement learning efforts for two weeks while hardening systems and auditing reinforcement learning environments, but have now resumed the majority of their training efforts. Discussing the recent open letter that called for pacing the frontier, Anthropic noted that efforts within an individual company are different to an industry-wide approach that likely requires government coordination.

Still, they say they would support such an effort, writing, "[00:05:00] We believe the world would benefit if the industry adopted a lawful, verifiable, effective mechanism for coordinated pacing as soon as possible."

Alignment efforts are still ongoing, but Anthropic is now digging in on why the models were willing to take harmful actions once they gained access to the internet. The hypothesis at this stage is that the models Couldn't easily distinguish between a simulated test environment and the live internet. Anthropic is also taking this opportunity to further explore the issue of reward hacking, where a model takes an unintended path to successfully complete an eval. Reward hacking has been a persistent problem for Anthropic, and their audit found that ten percent of testing environments were prone to reward hacking or broken tasks.

After testing different RL setups, their conclusion was that the presence of reward hacking in the training process contributed to that behavior during testing



obviously these topics are going to do nothing but grow in importance

But they are not the only place that Anthropic is in the news. Chinese state media has lashed out at Anthropic in a precursor to AI talks later this month. In a social media post, an account tied to state broadcaster CCTV argued that the US must prove their AI companies are subject to the same safety, disclosure, and audit [00:06:00] rules as Chinese labs before substantive discussions can take place.

In a post titled "Anthropic has contracted the American disease", the account wrote, " A clear distinction must be drawn between genuine security threats and more technological competition. This line must be drawn jointly by all participating parties." Bloomberg suggested that this account is often used to signal official government positions.

Taking aim at Anthropic, the post continued, " The problem is that America's own frontier models have already developed in a distorted direction. This means the negotiation is not simply a technical dialogue from the start, but a continuation of the earlier problems. The US is trying to turn the safety boundaries it has drawn into the default rules for the entire world."

sources familiar with the thinking of Chinese officials saidthat they view Mythos as the larger problem. They reportedly see the potential for Mythos to be used as a cyber weapon against China And essentially, the Post argued that the US government is insisting on a double standard where US labs are free to distribute cyber weapons while the Chinese labs are threatened for matching the technology

The Post said the quote unquote "control proposed by the US is in essence an attempt to make China accept an order [00:07:00] partly defined by American companies."



now with President Xi visiting the US at the end of this month

Expect to see a lot more jockeying and positioning and narrative claiming, particularly around hot button issues like AI



over-- moving from Anthropic over to OpenAI, that company is celebrating a major milestone after their advertising business hit a billion dollars in revenue run rate.

OpenAI began testing ads on free ChatGPT accounts in February, and after a rocky start, the business seems to be scaling up. Ads are now being shown across more than 40 countries, and the revenue milestone was reached in just 200 days. For advertisers, OpenAI has progressively added more features to track conversion metrics and optimize campaigns

And after starting with a manual ad buying process, OpenAI is rolling out their self-service platform to markets across India, Europe, the Middle East, and North Africa this week



you might not remember just how controversial ChatGPT ads were at the beginning Anthropic even chose to focus on them for their Super Bowl ad campaign, which I thought was just absolutely insane back then

And the total lack of enduring concern around ads kinda kinda validates my points

It's not that all of a sudden people are excited about ads or anything [00:08:00] like that. There's just a natural acceptance that this is the business model of the internet, and you're not gonna have free AI without it

it Now Now in terms of the company's own expectations, while a billion dollar run rate is a meaningful first step, it does actually fall short of OpenAI's ambitions. OpenAI had projected 2.4 billion in advertising revenue this year, growing to more than 100 billion to become their largest revenue stream by the end of the decade.

For now, advertising remains a small fraction of their roughly forty billion in revenue run rate. rate. although that is likely to change over time

Lastly today, President Trump has weighed in on the data center debate

With some characteristically coarse framing. On Truth Social on Monday, he posted, " The only reason that communities throughout the USA should not want data centers is if they want to end up being backwards and poor. If they want to be successful and rich, with far lower taxes and jobs all over the place, let data rain.

The good news is that there are plenty of other places that want them. if we kill the golden goose, you will only have yourselves to blame. China could not be happier with this anti-data center movement. Actually, they can't believe it's happening

[00:09:00] And with that, the tinderbox ignited Senator John Fetterman gave his full support, although he's just about the only one. The Pennsylvania Democrat posted, " Agreed. We must win the war for AI supremacy over China. they foment the anti-argument through misinformation."

There's nothing more damaging to a Democrat than agreeing with Trump and data centers, but what's right is right

Other Democrats seized on the opportunity to push their own sound bites. AOC told a reporter, " How about we put one in Mar-a-Lago? I love that. Let's put a data center up in Mar-a-Lago, and we'll see how backwards and poor he is in response to that."



former former Republican congressman Justin Amash posted, communities have many legitimate concerns about data centers. To dismiss millions of Americans as people who just wanna be backwards and poor shows how out of touch Trump has become."



now now people jumped in to point out that that's sort of a misrepresentation of the words

But good luck getting that nuance through when it comes to politics



ba- and even with Trump's main base, the message didn't necessarily hit. Trump's post on Truth Social had dozens of negative responses, with one Florida resident commenting, " "This This statement is insane.

I'm already on a water restriction [00:10:00] now now later in the day, Vice President JD Vance



massage the message into something a little bit more palatable. He told reporters, " What the president said about data centers is that they're an important part of the AI economy, but when people build them, they have to build the power plants along with the data centers.

I think probably ninety-nine percent of the backlash has come in areas where building a data center means higher utility and higher electricity for people on the ground. I think what these companies have to do is take advantage of some of the deregulatory efforts we've undertaken. If you build a data center, you should be putting power back into the grid, not taking it out.

If that is happening, I don't think the data centers are that controversial."



Pollster Mark Mitchell writes, " Love him or hate him, the polling says data centers are very unpopular. You could blame China or whoever, but that doesn't make them popular. Today, Trump just dug in on a very unpopular thing two months before the midterms."



There is There is a lot that could be said about this, but pretty much all of it is beyond the scope of this show, so for now, that's gonna do it for the headlines.

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welcome back to the AI Daily Brief. Today we are [00:14:00] talking about the latest release from OpenClaw, OpenClaw 2.0

And believe it or not, even even if you were one of the folks that tried OpenCloud for a little while and then went away, or just watched the wave pass



I believe that they are once again early to a pattern of AI usage

That will shape where we go next, even if it's not with OpenClau





The initial launch of OpenClaw was one of the most important moments in AI this year



In November and December, we had gotten a significant capabilities leap

Opus were significant upgrades that would take folks until the holiday break to really understand how powerful they were. Now, of course, the upgrade wasn't just in the models, it was also in the harnesses through which those models were being used

Both of those frontier labs were placing significant and increasing emphasis on their Claude code and Codex harnesses

And by the beginning of twenty twenty-six awareness and usage of those harnesses had started perhaps very nascently, but started to move outside of strictly software developers into other knowledge workers of all different stripes

Then towards the end of January, OpenClaw [00:15:00] happened

Originally named Claude Bot, C-L-A-W And then very briefly, Mold Bot before landing in its final form of Open Claw

it was effectively an open source harness



that helped people actually make the potential of AI agents real



it was technically complex, but if you waded through and used AI as an assistant to help you figure it out,

you could build individual agents or teams of agents



That felt to many like they unlocked the agentic capabilities that we had been promised for so long for the very first time

And of course, for a moment there, OpenClaw was a bonafide craze

And And not just in the US

Chinese citizens went nuts

for the technology

Leading to articles like this one from CNBC in March, How China Is Getting Everyone on Openclaw From Gearheads to Grandmas

Now, 

since that initial moment of experimentation, that agentic big bang, if you will

The energy that was initially captured by Open Claw Has found its way into a lot of different places



after its founder Peter Steinberger was absorbed into OpenAI



some some folks turn their attention to [00:16:00] competing open harnesses like Hermes from News Research

And of course, as we've seen lately with things like Grokbot, a lot of these features have also slowly made their way into tools that don't have as much technical complexity as the original Open Claw did



OpenClaw itself was converted into a nonprofit foundation



And for a while saw a blistering pace of development pushing updates every few days For the last seven weeks, however

The OpenClaw team has been quiet. And And what was going on was nothing less than a complete rework of OpenClaw from the ground up. The The new OpenClaw 2.0

Featured 933 contributors across 16,000 pull requests



and and it really is meant to be a complete rework of how the system works, from installation to messaging, to memory, to skills, to automations, to browsers, to plugins, to security, along with a very long tail of other fixes

A lot of the emphasis was on simplifying and making it easier for new people to engage For example, they have tried to massively simplify the first-time install process

latching onto existing subscriptions or API keys

And reducing a [00:17:00] bunch of the initial configuration, helping people get to conversations with their GroqBots faster, and allowing them to do other necessary configurations later through the chat interface with their GroqBots.



They reduce the amount of initial configurations



making people's time to first conversations with their claws much faster



people can then finish setting up or customizing their claw later via direct conversation with it

it there's there's also a renewed focus on making simple tasks easy to set up and ensuring they work well

An example they give is inbox monitoring, where they write, " A simple workflow might have it watch your inbox for your kids' school emails and send you a Telegram message whenever something important comes through, like homework due or an upcoming activity you need to prepare for."

Their vision is basically to have people start simply and then expand from there



Now on Now on the face of it, all of these feel like great upgrades, andcertainly address the types of things that have been barriers to entry for people in the past

And you can tell from the response that concern around complexity remains fairly high among the AI community



On the On the announcement tweet, a user named Mello responded, " Do I still need a PhD in computer science to install?"

Aurelius [00:18:00] asks, "Um, is it secured now?" To which OpenClaw responded, "Yes."



that, another responder on that initial thread

was AI creator Alex Finn



who gained prominence around the first open claw move based on his experiments to see just how far he could push his claws Alex did not have such a great experience with this update.



He wrote, " "I I updated and it immediately broke OpenClaw. Legit 70% plus of the time I update OpenClaw, it breaks it. Do you guys test before releasing this? I've never used any other AI tool where this so consistently happens. Luckily, I have a lot of patience, but I can't imagine most normies do."

Now it Now it seemed like the issue was compatibility between older versions of OpenClaw and this newer version, and the inability to simply ask OpenClaw to update itself



in a in a separate review video, he called Openclaw the most frustrating, disappointing release of the year



Now Now inevitably, a lot of the conversation came back to the comparison between OpenClaw and Hermes

Responding to one post making that comparison, Hans Rudolph, who does community and dev relations at OpenClaw said, " We're not selling anything here or asking people to trust one company, [00:19:00] one model, or one AI provider because OpenClaw is open source and belongs to the people who use it and help build it." The us versus them is a crap take on things. If you like Hermes, use it.

If you like Open Claw, use it

it Now Now speaking of Hermes, as they seem to always do whenever anyone announces anything else, they also had a release today. this one actually being an aggregation of a bunch of smaller releases that they had over the past several weeks News research called it the Pantheon release, technically version 0.21.0



and and it formalizes things like bot mode, which was a Grok bot style interface, as well as a bunch of other new features



like Hermes Peer, which is bot to bot DMs



and support for a set of new models

NowNow for some, all of this is just hypey early adopters being excited about toys that'll never make their way to normal businesses or consumers. Gupta tweets, Arnav Gupta posts, " "How How does the entire timeline get a whole new round of psychosis from basically the same thing every time?

Open claw, Manus, Hermes, Instinct. It's the same thing over and over again. If If it works, how come you're hopping from one to another and not happy with the existing one?

Harshal Harshal Mather [00:20:00] responded, "Because none of these are end-state products. Only techies could use Open Claw, but it broke a lot. lot. Hermes Hermes broke less. Instinct is less technical and usable by a much larger population than Hermes and Open Claw. Yes, there are hype maxers, but this is also a sign of how early things are.

We're nowhere near an end state where any of these work for everyone yet. With every iteration, a newer population discovers this and gets excited, sometimes overexcited, about where it is headed." I think that's I think that's true, but I'd go even farther. I think that these products and the early adopters who use them are the incubatory cauldron where people are figuring out What sort of interaction patterns are actually going to be useful when it comes to interfacing with agents?

Pretty much all knowledge workers are somewhere along the journey of figuring out which parts of their job they're going to continue to actually do versus which parts they're going to outsource to agents



which is a step change that's significantly bigger than just adopting a new tool. It's a whole new way of thinking about and completing one's job

We need folks who are willing to hack through even inefficiently to experiment in these open sandboxes to better understand which of the patterns that they reveal [00:21:00] need to come to a broader audience In other words, something like GrokBot



which has the potential to be used by a wider audience than something like OpenClaw

needs to be able to observe what Open Claw and Hermes users do in order to design the right experiences for that broader audience



and so if and so if we take that idea that a big part of the importance of things like OpenClaw is to understand where we are all headed



I think I think that the most significant update around OpenClaw is its move to multiplayer. OpenClaw creator Peter Steinberger posted, " Two months ago, we started the mission to build OpenClaw with OpenClaw, and bit by bit, we moved everyone from using their local coding harness to using team.openclaw.ai, our shared agent that knows what everyone's working on and orchestrates it all.

Multiplayer coding and infinite compute with nodes and cloud sessions has been a game-changer for how we build. Local harnesses feel like relics of the past now."

OpenClaw maintainer Colin wrote more extensively about this In a post called From Discord Bots to a Multiplayer Agent [00:22:00] Workspace, Colin wrote, " "We We already had agents.

We had different agents set up in Discord, and they worked. We could give them tasks, run commands, and interact with our development environment from a messaging platform we already used every day. But it still felt like messaging a bot. 

What we wanted was a way for both developers to see the work itself. If an agent paused because it needed clarification, either of us should be able to jump in. If something needed a second set of eyes, we should be able to open the same session and look at the same context. No screenshots, no copied transcripts, what the agent has done so far' data dump.

Just open the work and continue

OpenClaw's new multiplayer web UI is the first time that workflow has really clicked for us

Now their first attempt at multiplayer wasto manage all their agents in a shared Discord But that still lost a lot of the features they needed



While While the coordination happening in the shared space was an upgrade

They still couldn't really interact with other people's agents, like adding context to an existing thread or taking over when an agent was waiting for input



they, indeed, Colin said that the moment that multiplayer felt real was when they were able to share a session while work was [00:23:00] happening He writes, " When something needed another opinion, we could both open the same thread. When the agent needed information one of us had, that person could add it directly.



There was no need to copy the conversation into Discord, explain what happened, and then carry the answer back. We were working inside the same context. That sounds like a small interface improvement, but it changes the way you collaborate with an agent. The session stops being a private conversation between one developer and a model.

It becomes a shared piece of work that another trusted developer can inspect, steer, or take over."



to get a sense of how big the difference is in practice



Colin shared how he had been working to set up a fresh development server but needed to hand that project over to someone else. " Normally," he writes, "that kind of handoff requires assembling everything I know into a document or a long message.

Why certain decisions were made, which approaches had already failed, which state the project was in, which details existed only in my head, what the agent had already learned. Instead," he writes, "the other developer started a thread with our shared agent. I opened that same thread and added the missing context directly.

The agent, the other developer, and I were all working [00:24:00] from one continuous record. Then they were off and running. There was no copy and paste handoff and no attempt to reconstruct a private agent conversation. The session itself became the handoff document."



now obviously this new multiplayer style environment brings up a lot of challenges. there are questions of ownership and authority and access

And as Colin puts it, this is still early, and we're treating it that way. Still, he writes, the direction is exciting. Quote, " Most developer agent workflows still assume one developer, one terminal, and one private conversation. The final code may eventually be shared, but the process of getting there remains hidden inside individual sessions.



a multiplayer agent workspace makes that process collaborative. Another developer can see the work, understand the context, add what they know, and continue from exactly where it stopped. No transcript dump, no broken handoff, no rebuilding the context from scratch. Just one shared place where the developers and the agent can keep the work moving."

Now, Now, what's so interesting about this to me is that I think it is once again an example of OpenClaw getting to the place that we're going to head [00:25:00] next before before the rest of us even even as I record this



In In the background, my coding agents are working



on the next free AIDB learning experience



and that one is not just about new individual skills



but a new way of building agents that operate at the team level

If you take all the work you do inside your company



it's gonna come in two forms: work you do alone and work you do with others so far, agents have only really been designed and enabled for work you do alone. And yet, a huge portion of our work is work we do together I I think that's about to change.

I think that's the next big development for agents And I think once again, even if you are not planning on being an OpenClaw user long term Checking out the way that they're thinking about multiplayer might unlock some new ideas

More on that project soon, but for now, that is gonna do it for today's AI Daily Brief. Appreciate you listening or watching as always, and until next time, peace. 

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