Run a VC analyst agent over Telegram
Sharing initial learnings from building an AI agent that could save me dozens of hours per quarter, replace multiple $5000+ software subscriptions and why sub-agent management will be a critical skill. Task: The author deployed OpenClaw on a Hostinger VPS, integrating Telegram for mobile access and OpenRouter for model routing. The agent, named 'Pao', was configured as a VC analyst to handle tasks like security audits and CRM replacement. The author managed the setup via terminal commands and API keys, while the agent executed autonomous tasks like firewall configuration. Human involvement included initial setup, monitoring costs, and approving outputs before publication.; tools: OpenClaw. Human role: The original post does not say how a person stayed involved.; limitations: The technology is not consumer-ready, requiring knowledge of API keys, SSH, and terminal commands. Model performance varies, with some models failing at orchestration or providing inaccurate information. The author emphasizes that sub-agent management is a new skill set. Costs are consumption-based, requiring careful monitoring to avoid unexpected expenses..
Tools
Published on Agent Work Atlas:
Overview
Sharing initial learnings from building an AI agent that could save me dozens of hours per quarter, replace multiple $5000+ software subscriptions and why sub-agent management will be a critical skill
Workflow
The author deployed OpenClaw on a Hostinger VPS, integrating Telegram for mobile access and OpenRouter for model routing. The agent, named 'Pao', was configured as a VC analyst to handle tasks like security audits and CRM replacement. The author managed the setup via terminal commands and API keys, while the agent executed autonomous tasks like firewall configuration. Human involvement included initial setup, monitoring costs, and approving outputs before publication.
Reported result
The setup took approximately 45 minutes, and a security audit cost $0.30. The author spent about $25 to build a basic CRM version. However, the author reported issues with model reliability, noting that Claude hit limits and Kimi lacked reasoning for orchestration. The author explicitly stated they do not fully trust the agent and have not granted high-stakes permissions.
Human role
The original post does not say how a person stayed involved.
Limitations
The technology is not consumer-ready, requiring knowledge of API keys, SSH, and terminal commands. Model performance varies, with some models failing at orchestration or providing inaccurate information. The author emphasizes that sub-agent management is a new skill set. Costs are consumption-based, requiring careful monitoring to avoid unexpected expenses.
Try it
I want to replicate the OpenClaw VC analyst setup described in the source. First, provision a Hostinger VPS and install OpenClaw via the single command-line script. Configure Telegram integration by creating a bot with BotFather and pairing it. Set up OpenRouter to route tasks to appropriate models like Claude or Kimi. Define the agent persona as a direct VC analyst. Before running any high-stakes tasks, perform a dry run with a sample security audit request. Monitor token usage closely. Do not grant permissions for financial transactions or public publishing without my explicit approval. If the agent fails to deploy or hits model limits, switch the orchestrator model to ChatGPT 4.1 mini as suggested in the source. Provide a report on setup time, cost incurred, and any errors encountered.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.