Agents made my retro tech safe to use again and showed their real value as testers of ideas

In the past, my residence has transformed into a haven for obsolete technology, housing numerous ancient computers that have long since become unsupported. While most of these devices still function, they are no longer considered safe to use due to their outdated status. This situation changed when I decided to explore the possibility of using an agent to revive a 15-year-old device with a small CPU, an older version of Arch Linux, and an outdated browser that lacked the necessary encryption for modern web browsing.

I allowed the agent to have full control over the device, and over the course of three hours, the agent repeatedly struggled to compile the latest cURL toolchain with modern cryptography. Finally, the agent succeeded after finding a fast math library, enabling cURL to operate smoothly. This experience led me to wonder about the potential of agents to breathe new life into my entire collection of retro technology.

Within minutes, the agents appeared, transforming a 12-year-old iMac Pro, a 10-year-old virtual reality PC, and a Surface Go into machines running the latest versions of their respective operating systems, all thanks to the agents. As soon as the operating system boots and the network connection is established, I install an agent to configure and maintain the devices.

This process has made it effortless to experiment with new ideas, as the cost of testing them has significantly decreased. I am now able to learn at an unprecedented pace, feeding rough ideas into the agents and allowing them to explore multiple paths until a satisfactory result is achieved. This concept has the potential to revolutionize not only retro-tech revivals but also various scientific fields, such as biology, physics, and materials science.

For instance, Google DeepMind recently saw four of its key personnel leave to launch Discovery Loop, an initiative that applies these same practices to scientific research. Discovery Loop exemplifies the future of scientific exploration, where scientists propose hypotheses and agents run the necessary tests. While agents have provided speed and scope, the true bottleneck lies in the ability to discern which measurements truly matter, which can be manipulated, and which should be disregarded.

This qualitative judgment is inherently human, and it is crucial to recognize the role agents play in enhancing our capabilities while leaving the critical decision-making to humans.