I have been running OpenClaw vs Claude Dispatch constantly since it released on identical jobs. Thousands of attempts. The simplest way to explain it: Claude is a rocket scientist OpenClaw is a workhorse And in real estate, most of the time, you don’t need a rocket scientist. You need something that shows up every day, does the same task 1,000 times, and doesn’t get tired. Claude is incredible at thinking... but most businesses need action. If I need to break down a market, write a podcast, write a course for this Skool group, structure an argument, turn raw ideas into something sharp - claude is the best tool I’ve used. But that’s not most of the job. At least not my job. Most of the job is: - follow up with leads - update the CRM - send messages - book showings - move information between systems Claude doesn’t actually do much of that. It tells you what to do. It identifies workflows very well. But it doesn’t execute nearly as well. And for a lot of real-world tasks, it’s honestly overkill... it's too smart. It will overthink simple workflows, add unnecessary complexity, and cost a lot more while doing it as a result. I have said for a while that these labs are too focussed on building superintelligent models instead of consistent and reliable ones. OpenClaw is the opposite. Running on models like Minimax M2.7 or Deepseek Chat, it’s not as smart. The writing isn’t as clean. The reasoning isn’t as deep. But it works. And that is what my business and most businesses need more than rocket science. It clicks the buttons it sends the messages it updates the CRM it runs the workflow it keeps going in the background And it does all of that for pennies. You can run thousands of actions a month for less than what Claude costs. That’s the real tradeoff: Claude is expensive, high quality, basically Phd Ai. OpenClaw is cheap, scalable, and built for execution. It's the workhorse. So the answer isn’t choosing one. It’s probably going to mean splitting the stack.

1. Karpathy's AutoResearch (free, open source) Andrej Karpathy (co-founder of OpenAI, former Tesla AI director) just open-sourced AutoResearch on GitHub. It's 630 lines of Python that lets an AI agent run 100+ experiments overnight on a single GPU — no human involvement. It modifies code, trains the model, evaluates results, and loops. His README opens with: "One day, frontier AI research used to be done by meat computers… That era is long gone." Why this matters for us: the same "agent loop" pattern — give AI a goal, let it iterate until it solves it — is exactly how the best OpenClaw automations work. Imagine giving your agent a neighbourhood and saying "find me every underpriced listing and tell me why it's underpriced." That loop is coming. github.com/karpathy/autoresearch 2. OpenUtter — your OpenClaw now sits in meetings for you Someone on Reddit just showed their OpenClaw attending Google Meet calls. OpenUtter joins the meeting, captures the entire transcript, saves it to a file, and then your OpenClaw summarizes it. You can literally text your agent from your phone mid-meeting and ask "what are they talking about right now?" Real estate spin: imagine your agent sitting in on a condo board AGM, a team meeting, or a listing presentation call — and giving you the summary plus action items before it's even over. Or sending it to attend a webinar while you're on a showing. 3. OpenClaw Chrome Control (trending on X right now — 9,000+ posts) OpenClaw just got a major update that gives AI agents live Chrome browser control. Your agent can now navigate websites, fill out forms, click buttons, and interact with any web app in real time. For realtors: this means auto-booking showings on BrokerBay, pulling sold data from any board portal, managing your ad accounts, or even filling out listing paperwork on your brokerage's backend — all hands-free while you're at a showing. This was literally trending on X today. Which one are you most interested in trying?