David Andre demonstrates how to build and self-host AI agents by creating a Python-based web scraper enhanced with a large language model, then deploying and automating it on an affordable VPS using SSH and cron jobs. This approach offers full control over data, cost savings, and flexibility, enabling continuous, remote AI agent operation without reliance on cloud ecosystems.
In this video, David Andre demonstrates how to self-host AI agents by running applications on a server that you control, specifically using a Virtual Private Server (VPS). Self-hosting offers several advantages including full control over data and privacy, cost-effectiveness compared to cloud solutions, and flexibility to move your AI agents easily without being locked into an ecosystem. David outlines a clear plan: first, building a simple AI agent in Python; second, accessing a VPS via SSH; and third, deploying the AI agent onto the VPS.
David begins by building a simple AI agent that scrapes the Hacker News front page daily, saving the top 10 posts into a markdown file. He uses AI coding assistants like Codex to generate the project structure and Python scripts, making it accessible even for beginners. The agent is designed to run scheduled commands and can be adapted to scrape any website for various use cases. After testing the scraper locally, David enhances the agent by integrating a large language model (LLM) to analyze the scraped data and generate actionable AI insights, turning the scraper into a more intelligent AI agent.
Next, David explains how to prepare the project for deployment by initializing a Git repository, creating a .gitignore file to protect sensitive environment variables, and managing dependencies. He demonstrates how to obtain an Open Router API key for the LLM integration and troubleshoot issues such as missing proxies. After confirming the agent runs smoothly locally with detailed logging, he moves on to setting up the VPS environment, recommending Hostinger’s KVM2 VPS plan for its affordability, scalability, and ease of use.
David then guides viewers through accessing the VPS via SSH, explaining the benefits of secure remote access and file transfer capabilities. He shows how to update the server, install necessary dependencies like Python and pip, and transfer the local project to the VPS using SCP. Once the project is on the VPS, he activates a Python virtual environment, installs dependencies, and runs the AI agent to verify it works correctly on the remote server. This setup allows the AI agent to run independently of the local machine, accessible from anywhere.
Finally, David demonstrates how to automate the AI agent’s execution using cron jobs on the VPS, scheduling it to run daily at 9 a.m. He walks through editing the crontab file using the nano editor, adding the command with the API key, and saving the configuration. This automation ensures the AI agent continuously scrapes and analyzes data without manual intervention. David concludes by encouraging viewers to subscribe and emphasizes that with a bit of intention and AI assistance, anyone can build and self-host powerful AI agents on a VPS.