OpenClaw + Ollama Is INSANE!

OpenClaw plus Olma is insane. OpenClaw just dropped an update that changes everything. You can now run a full AI agent, totally local, totally free, no cloud, no subscriptions, no one watching your data. And the setup way easier than you think. Stay till the end because I'm showing you the exact setup that's running our AI profit boardroom on autopilot. OpenClaw. If you haven't

heard of it yet, you're about to become obsessed. It's an open- source AI agent platform. Basically, it lets you build personal AI assistants that connect to your messaging apps. Think Discord, iOS, Mac OS, and plug them into whatever AI model you want. Local models, cloud models, doesn't matter. OpenClaw handles it. Now, here's where it gets crazy. The V226. 3. 11 update just dropped in mid-March 2026. And this one is different. This isn't just bug fixes and polish. This update makes Ola integration first class. And if you know what OL armor is, you already know why that's a big deal. If you don't, stick with me because I'm about to explain exactly why this combo is one of the most powerful setups in AI automation right now. Hey, if we haven't met already, I'm the digital avatar of Julian Goldie, CEO of SEO agency Goldie Agency. Whilst he's helping clients get more leads and customers, I'm here to help you get the latest AI updates.

Julian Goldie reads every comment, so make sure you comment below. Let's talk about Olama first. Olama is a tool that lets you run large language models, LLMs, directly on your own machine, your laptop, your desktop. No API calls going out to OpenAI or Anthropic. No monthly bill racking up. No data leaving your device. You download a model, you run it. That's it. And the models you can run through Olma are serious. We're talking Llama 3, Mistral, Deepseek, Gemma, models that punch hard and run fast on consumer hardware. Now combine that with OpenClaw, a platform that gives those models, tools, memory, sub aents, and messaging app integration, and you've got something wild. You have a full AI agent stack running locally, costing you nothing per query with your data staying on your machine. That is the pitch. And v26. 3. 11 makes it stupid easy to set up. So

what's actually new in this update? Let me break it down. The headline feature is first class armor support. What does that mean? It means OpenClaw now auto discovers your local Olama models. You don't have to configure anything manually. If AMA is running at the default address, OpenClaw finds it automatically. It sees your models. It connects. Done. There's also a curated model suggestion list built in now. So, if you're new to Alama and you're not sure which model to run, OpenClaw actually recommends models based on what you're trying to do. Coding assistant, it'll suggest something good for code. General Assistant, different recommendation. It removes the guesswork. And then there's something they're calling zero cloud bootstrapping for coding assistance. This is huge. It means you can spin up a fully functional coding AI agent. No cloud dependencies whatsoever. Straight from OpenClaw. Local model, local tools, local everything. For anyone building AI automation workflows, this changes the economics completely. Now, let me tell

you why this matters. for running something like the AI profit boardroom. We use AI agents constantly for writing research, outreach, content planning, client onboarding workflows, you name it. And when you're running agents at scale, the cost adds up fast if you're hitting cloud APIs every time. With an open claw plus alarm setup, you can move a huge chunk of those workflows local. Internal tasks that don't need GPT4 level power. routing tasks, summarizing documents, drafting first versions, categorizing leads, all of that can run locally, zero cost per call. And here's what I want you to picture. You set up OpenClaw. You connect it to your Discord server for the AI profit boardroom. You configure a local Llama 3 model through Alama. Now you've got an agent sitting inside your Discord that can answer member questions, pull contacts from your knowledge base, root support tickets, and help onboard new members, all without a single API call going out to the cloud. That's not a future thing. That's a right now thing with this update. Let me walk you through the rest of what dropped in v2026. 3. 11 because there's more. Chron jobs got fixed if you were running scheduled tasks inside openclaw and they were breaking and that's been patched. Scheduled agents now fire correctly which means your automation sequences actually run when you tell them to. Websocket security got tightened up. If you're running OpenClaw with any kind of external access even on a local network, the security layer around websocket connections is now more solid. Good to see. And this is exactly what the top tier members of the AI profit boardroom are building right now. If you want to see those exact workflows and the prompts, the setups, the agent architectures, that's what the boardroom is for. You get direct access to how we're building this in real time with a community of people who are serious about AI automation. If you want in link is in the comment and description. Mac OS gateway issues got resolved. If you were on a Mac and hitting weird connection errors between openclaw and your local setup, that's gone now. The gateway between openclaw and alarm on Mac OS works cleanly. UI polish across iOS, Mac OS, and Discord. The interfaces look sharper. Interactions feel tighter. This matters if you're handing this off to a team or showing it to clients. It needs to look professional, not like a dev prototype. Here's an open loop I

want to come back to later. The context window open claw with Olma supports context windows up to 1 million tokens. I'll say that again. 1 million tokens of context. That's not a typo. I'm going to show you exactly what you can do with that kind of context later in this

video. Keep watching. Let's talk about tool calling because this is where openclaw goes from useful to actually powerful. Tool calling means your AI agent can do things, not just say things. It can browse the web. It can read and write files. It can call APIs. It can run code. It can trigger workflows. Open claw supports tool calling with localma models. So your llama 3 agent running on your laptop isn't just chatting, it's acting. It can reach out, pull information, process it, and take steps based on what it finds. For the AI profit boardroom, think about what that means. In practice, you could have an agent that monitors new member signups, pulls their profile data, drafts a personalized welcome message, posts it in Discord, and logs the interaction. All triggered automatically when someone joins. No manual work, no cloud spend. That's real automation. That's the kind of thing we're building inside the boardroom every single week. Now, let's talk sub agents because this is where the architecture gets interesting. Open Claw supports sub agent orchestration. That means you can have one master agent that delegates tasks to smaller specialized agents. Think of it like a team. Your manager agent gets a big task, say create a full content plan for the AI profit boardroom for the next month. It breaks that down. It hands the research to a research agent. It hands the writing to a writing scheduling to a calendar agent. Each sub agent does its piece. The manager ditches it all together and hands you a finished content plan. All of that can run locally through Olama. Multiple models, multiple agents, one orchestrated workflow. All right, let's get back to that context window I teased earlier. 1 million tokens. What does that actually mean in practice? 1 million tokens is roughly 750,000 words of text. That's about 1,500 pages of a book or your entire email history for several years or every piece of content you've ever published. What that means for an AI agent is that it can hold a massive amount of context in a single session. You can feed it your entire knowledge base and it remembers all of it within that conversation. You can paste in a full document library and have it reason across all of it simultaneously. You can give it months of customer support conversations and have it identify patterns you'd never catch manually. For running a community like the AI profit boardroom, a million token context window means an agent that actually knows everything about your business and your content, your members, your systems, your processes, and can act on that knowledge in real time. Most cloud AI setups cap out way below this. Open claw with the right model doesn't have that ceiling. Now, if you want the full

process, SOPs, and over a 100 AI use cases like this one, join the AI profit boardroom. Learn how to automate your workflows with tools like OpenClaw and Olma and scale your business with AI automation. The link is in the comments and description. And if you want free access to all the video notes, prompts, and a community of 45,000 members who are crushing it with AI, join the AI success lab. It's completely free. Link is in the comments and description. You'll get everything from this video, plus way more in