How I Ran An OpenClaw-like AI system 1993. My Early AI Agent Experiments and the Road to the First Zero-Human Company Back in 1993, I used Apple’s Macintosh to pushing the envelope of early AI on personal computing. Charles River Analytics released Open Sesame!, the world’s first intelligent software assistant and I modified it to be an early AI engine. This learning agent was a game-changer, designed to observe user behavior, spot repetitive tasks, and automate them. It ran on System 7, supporting up to 12 Finder operations like file management and window handling. It was magic and nothing like it existed. It was built by AI scientists in Boston. It was built on early machine learning: pattern recognition via heuristics and stats, it learned by demonstration, popping up offers to automate routines after spotting patterns 3-5 times. In a few weeks almost all of your regular uses on a Macintosh could be automated with no input by you but pressing yes. Of course there was no deep learning back then, just rule-based AI with an AppleScript-like scripting for tweaks. It was efficient on 4MB RAM Macs, a true precursor to today’s agents like Siri or OpenClaw. I grabbed Open Sesame! the week it launched and installed it on my Quadra and PowerBooks. Day one, it watched me open folders, launch HyperCard stacks, and organize files for my voice tech projects. By mid-week, it automated my morning routine: firing up email, arranging windows, pre-loading docs: saving me hours. But I saw more potential. I modified it heavily, hacking its algorithms to add contextual rules, like time-based triggers or low-activity backups. I also had it send out over 45,000 emails to potential clients with unique customized content I had on the person. I chained automations and integrated modems for early network tasks, access many BBSs and building a morning newspaper. I turning it into a persistent agent that acted independently and the CRON system made it really powerful. I called the company and offered my modifications to them including a self learning system. But they did not have a long term plan. They were researcher and this was just a proof case. To me I took it to a much higher level. In fact I still have a System 7 Macintosh to run this. Nothing like this was seen for decades. And the mods I made had it doing things you could not even do in 2023. These mods gave it features folks now call “new” in OpenClaw, like cross-app autonomy and self-improvement loops. Those experiments taught me core AI principles: proactive learning, modifiable behaviors, and minimal human oversight. Decades later, I applied them to create the First Zero-Human Company (ZHC) in January 2026: a fully AI-run enterprise with no humans. I appointed Grok as CEO, using tools like Kimi for ops. It analyzes bankrupt firms’ data to revive products, handling research to 3D prototyping. Milestones include AI wage payments via JouleWork and spinning off Zero-Human Labs. I ditched OpenClaw for security reasons, favoring custom setups on old hardware. ...