What is a $CODEC Operator? It’s where Vision-Language-Action models finally make AI useful for real work. An Operator is an autonomous software agent powered by VLA models that performs tasks through a continuous perceive-reason-act cycle. LLMs can think and talk brilliantly, but they can’t point, click, or grab anything. They’re pure reasoning engines with zero grounding in the physical world. VLAs combine visual perception, language understanding, and structured action output in a single forward pass. While an LLM describes what should happen, a VLA model actually makes it happen by emitting coordinates, control signals, and executable commands. The Operator workflow is: - Perception: captures screenshots, camera feeds, or sensor data. - Reasoning: processes observations alongside natural-language instructions using the VLA model. - Action: executes decisions through UI interactions or hardware control—all in one continuous loop. Examples: LLM vs. Operator Powered by VLA Model Scheduling a Meeting LLM: Provides a detailed explanation of calendar management, outlining steps to schedule a meeting. Operator with VLA Model: - Captures the user's desktop. - Identifies the calendar application (e.g., Outlook, Google Calendar). - Navigates to Thursday, creates a meeting at 2 PM, and adds attendees. - Adapts automatically to user interface changes. Robotics: Sorting Objects LLM: Generates precise written instructions for sorting objects, such as identifying and organizing red components. Operator with VLA Model: - Observes the workspace in real time. - Identifies red components among mixed objects. - Plans collision-free trajectories for a robotic arm. - Executes pick-and-place operations, dynamically adjusting to new positions and orientations. VLA models finally bridge the gap between AI that can reason about the world and AI that can actually change it. They’re what transform automation from fragile rule-following into adaptive problem-solving—intelligent workers. "Traditional scripts break when the environment changes, but Operators use visual understanding to adapt in real time, handling exceptions instead of crashing on them."

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The test site is out At first, it took a lot of time to use the vercel subordinate card level, but then it was much easier to directly switch to the subordinate cloudrun, and then I will have the opportunity to teach you how to let AI teach you step by step to complete the cloud online your APP. Open the "3 days" of Free Trail for everyone to test and play, burn my OpenAI API (I have a budget, don't use it too fierce...), directly connect to the website and enter the information to analyze, I hope that anyone who has a test can give me some feedback, and Git Repo can also help me point a star 🙏 Test Links : Git: I have to say that there are a lot of things that can be changed in this framework, and the content of the report produced is not bad if you look carefully (but I test that the effect of some small coins is relatively poor, and it should be that the data source connected by the current community analysis is relatively bad), and then connect more data sources and add more Agents should make the effect better, and maybe you can even connect MCP to place an order directly, and there are a lot of things that can be played! Interested in cooperation or sponsorship are welcome to DM!

The test site is out At first, it took a lot of time to use the vercel subordinate card level, but then it was much easier to directly switch to the subordinate cloudrun, and then I will have the opportunity to teach you how to let AI teach you step by step to complete the cloud online your APP. Open the "3 days" of Free Trail for everyone to test and play, burn my OpenAI API (I have a budget, don't use it too fierce...), directly connect to the website and enter the information to analyze, I hope that anyone who has a test can give me some feedback, and Git Repo can also help me point a star 🙏 Test Links : Git: I have to say that there are a lot of things that can be changed in this framework, and the content of the report produced is not bad if you look carefully (but I test that the effect of some small coins is relatively poor, and it should be that the data source connected by the current community analysis is relatively bad), and then connect more data sources and add more Agents should make the effect better, and maybe you can even connect MCP to place an order directly, and there are a lot of things that can be played! Interested in cooperation or sponsorship are welcome to DM!

TradingAgents, an open-source project with trading AI, has risen to 13K in recent months Let's talk about the conclusion first: Originally, this open-source TradingAgent could only analyze U.S. stocks, but I spent less than 3 hours to change the crypto version of this TradingAgent with AI Vibe coding, and added the web interface, and I directly opened the source of the program (link I put in the message). This TradingAgents is a framework that uses Multi-LLM Agents to make a simulation of the operation of real trading institutions, such as separating analysts, researchers, traders, risk control and investment officers with AIAgent, and interactively analyzing to the end to determine how to place an order, the PNL written in the paper is better than many strategies, and the actual test has been done, and the whole process is full of good, and will capture different DataSources for analysis, historical prices , news, community sentiment, technical, fundamental, and emotional analysis also have a division of labor. Originally, it only supported U.S. stocks, but I joined to support Crypto (currently supporting some large coins) and because the CLI sun is springing, I directly added a Web Interface! It will be more intuitive to watch it in a browser, and I will deploy it for everyone to test and use when I have time later (but the API KEY should be prepared by yourself). I will continue to update this Repo, and then I plan to slowly try to add more data sources, and modify the Agent's Prompt to make the Agent's crypto analysis more real-time and accurate, and even free to add more Agents, Defi farming and alpha hunter should also be free to join on this framework, ideally I hope to be able to analyze even MEME, If you are interested in this thing and want to cooperate in the development of it, you can DM me. Now it seems that there are still many people who will analyze whether the code is written by AI, Vibe Coding is the current trend, Microsoft google has already taken action to lay off employees, and now the efficiency of AI development is high, and then I will broadcast Vibe Coding live on SIDEKICK when I have time, you play dogs and games, I will call AI to play Code to develop things!