Say goodbye to toy level AI: How did I use OpenClaw to build a fully automated "Golden Dog" research team? (Attached is a guide to saving money and building infrastructure for large models) Everyone is talking about AI/lobster, but the vast majority of people are still stuck in the era of "you ask me, I answer" chat boxes. In the rapidly changing and asymmetric opportunities filled crypto and prediction markets, relying on manually copying and pasting prompts to ask AI is already outdated. The true Alpha is hidden in Autonomous Agents. What you need is a "silicon-based mercenary" who works tirelessly 24 hours a day, has strict discipline, can cross platform capture data, and directly throw decision conclusions to you. In the past period of time, I have been tinkering with the server from start to finish and built my own "Golden Dog Squad" based on the OpenClaw framework. In today's article, I plan to delve into my understanding of OpenClaw, my multi-agent collaborative configuration solution, and how I developed the underlying computing architecture after burning countless API tokens. 1、 OpenClaw Core Cognition: It is not a shell, but the OS of the Agent Many people's first reaction when it comes to building robots is to install a shell and connect it to OpenAI's API. But OpenClaw is completely different, it is designed as an operating system for "multi-agent collaboration" at the underlying level. To understand OpenClaw, the core is to grasp three keywords: SOUL (soul), MCP (sensory), and Routing. 1. SOUL and independent agents are located in the OpenClaw workspace, with each agent having an extremely independent physical isolation directory. The most essential file is SOUL.md. This is not a simple prompt, but the underlying ideological stamp of the agent. For example, as my trading executive, I wrote in its SOUL: "You are an emotionless money printer that only believes in mathematics, probability, and asymmetric odds. Abandoning all subjective narratives, if a single slide exceeds the threshold, it must be forcibly blown." This underlying constraint ensures that it will not produce illusions like the general big model when facing extreme market conditions. 2. MCP (Model Context Protocol) is just a brain in a cylinder without hand eye AI. By mounting the MCP plugin through OpenClaw, I enabled the Agent to directly have the ability to capture news from the entire network (News API) and monitor Twitter sentiment. They are no longer making up stories based on expired training data, but directly sniffing out the unexpected events and new Meme coin sentiment on Polymarket today on Twitter. The most elegant aspect of Telegram UI is that OpenClaw can seamlessly turn Telegram groups into your command center. I don't need to write any front-end code, just create a TG group and bring in several bots including the general manager, research experts, and executives. This is a perfect UI. 2、 Practical Review: My 'Golden Dog Brigade' Collaborative Flow and Record of Stepping on Pitfalls Currently, there are four core employees residing on my Ubuntu cloud server. Daily collaboration is extremely vertical: the General Manager of Dog King is responsible for distributing tasks, the Eye of Dog King (Research) is responsible for uncovering project cards and unlocking schedules, the Dog King money printer is responsible for scanning fund rates and traces of strong village control, and the Dog King evangelist is responsible for noise reduction and report writing. The toughest practical scenario is to execute the "Binance Spot Expectation Sniper" strategy. The red line I set for them is to find all the token combinations on the entire network that have been listed on Binance U-Standard contracts but have not yet been listed on the spot market. This is an information gap with extremely high odds. I request the agent to calculate the OI (contract holdings)/MC (circulating market value) ratio of these coins and search for extreme deviations in the funding game. I encountered a huge obstacle while running this task (see Figure 1). When the task was issued, the general manager went on strike and threw a sensitive error. At first, I thought OpenClaw had crashed, but later on, after a thorough investigation, I discovered that it was triggered by the Trust&Safety (safety compliance risk control) of the underlying large model. Because my instructions contained jargon such as' strong cryptocurrency ',' low-level ambush ',' sniper ', etc., the underlying model determined that this was' market manipulation' or giving 'high-risk financial advice', and forcibly unplugged the network cable. ️ The way to break through: To counter the risk control of such large companies, one must learn to "translate slang". I have conducted an academic reconstruction of Prompt: changing "finding strong banks" to "observing the characteristics of derivative financial games and chip concentration", and changing "ambush" to "finding data bias in asymmetric expected values (EVs)". After donning the cloak of quantitative research on Wall Street and switching to a more tolerant underlying model engine for code and data, this multi-agent collaborative network finally became operational. 3、 Computing infrastructure: from cloud based OpenClaw to local Claude Code The Ubuntu server in the cloud is responsible for keeping Agents monitoring on chain data and Twitter 24 hours a day. But as the 'supreme commander', my personal main productivity is still on the local MacBook. Whether it's writing Python quantization scripts or refactoring framework code, I now heavily rely on terminal programming models like Claude Code. But there is an extremely real pain point here: burning money too quickly. Multi agents interact frequently in the cloud, and every time a bug is changed in the local Claude Code, a huge context must be read. If all official Claude 3.5 Sonnet or foreign full health models are used, the daily API bill will definitely be painful, and it will easily hit the Rate Limit (request frequency limit). This forces me to search for a top of the line, extremely affordable, and native programming tool compatible alternative engine. That's also why I switched both the local development environment and some of the cloud agents' brains to Zhipu GLM. 4、 Why is it Zhipu GLM? (My hidden divine weapon) In the domestic big model echelon, the GLM series of Zhipu (especially GLM-4.7 and above versions) can be said to be the stable first echelon in terms of code understanding and long text logic. Most importantly, it now offers extremely aggressive developer support solutions. For geeks like me who heavily rely on Claude Code and Cline, Zhipu's BigModel open platform is simply a computing power supply station for dimensionality reduction strikes. Through simple environment variable and alias configuration, I directly mapped Claude Code's underlying engine to GLM on Mac, not only bypassing tedious overseas payment and network issues, but also providing an extremely smooth experience. The key is here: Large scale wool If you are also a fellow practitioner of local automation tools, scripting, and quantification, it is strongly recommended that you replace the underlying code engine with the GLM Coding package. The programming ability is comparable to top models, but the price is only one-third of Claude Code, and the usage is three times that! Perfectly compatible with over 20 mainstream AI programming tools. Come and assemble the models quickly, with a great value subscription to GLM Coding from Zhipu. We invite you to work together to make a profit! Claude Code, Cline, and over 20 other major programming tools are seamlessly supported, with full "code power" available, making it even more enjoyable to work together! Start buying now and enjoy a limited time surprise price! Link: https://www. (bigmodel.cn)/glm-coding? ic=BU4RDFVGRE The wave of AI has evolved from "generating content" to "executing actions". By mastering an Agent framework like OpenClaw and configuring your underlying computing engine, you can have a tireless invincible fleet in the digital world. Let's tinker together, code and data won't lie. BTC Eth Sol BNB Openclaw Lobster