As a solo maker, I've been diving deep into the world of autonomous AI agents (LangChain, LlamaIndex, etc.). One of the biggest bottlenecks I kept hitting was code execution.
When an agent needs to analyze data, scrape a site, or run a simulation, it writes code. But where do you safely run it?
exec() or subprocess on the host machine? Terrifying. One bad prompt injection and the LLM accesses your .env files or exfiltrates data.
Standard Docker containers? Too slow and heavy for rapid-fire agent tool calls.
Cloud sandboxes? Great, but I didn't want to send my local data or proprietary agent logic to a 3rd party API just to run a simple pandas script.
A free calculator that converts your birth date into a Mayan Tzolk'in reading, including your Nawal day sign, Galactic Tone, daily Mayan date, and compatibility insights.
