This is my 1st attempt at using AI to help me storywrite. This field tech creates an LLM/AI code name TravelSmith_B Set in 2025, Part 1 I gave the path fill in the work context. background, the locations, and I directed the path, but I let AI fill in the blanks #grownostr #storytime #story #asknostr #ai #storytime #bitcoin TripSmith_β Is Rebooting An Emergent Systems Comedy About Letting an AI Plan a Trip It Was Never Supposed to Finish INTRODUCTION: THE EXPERIMENT I wasn’t trying to escape my life. I wasn’t chasing enlightenment. I wasn’t even particularly organized. I just wanted to know if this would work. The question came to me the way bad ideas usually do: late, casually, and with far too much confidence. Could an AI agent coordinate a real human, using real systems that already exist, to travel halfway around the world—without a fixed itinerary, without pre-booked flights, and without traditional funding—while documenting the entire process? Do not simulate it. Not plan it. Actually do it. The rules were intentionally simple: I would move forward, not necessarily efficiently. I would fund the trip by doing short-term technical fieldwork along the way. I would sleep where movement allowed—on overnight trains, buses, or in waiting rooms. I would not “solve” problems unless the system failed. And the AI would handle everything it reasonably could. This wasn’t tourism. It was systems stress testing with a human in the loop. The route was ambitious, but not random: Chicago → Boston → Iceland or Greenland → London → Madrid → Paris → Berlin → Warsaw → Moscow What I didn’t know at the time was that the route was only suggestive. The real destination was continuation. WHY WAS AN AI INVOLVED AT ALL I could have planned this myself. Poorly, but enthusiastically. That wasn’t the point. The point was to see what happens when you stop treating infrastructure as fixed and start treating it as negotiable, especially when a system takes instructions far more literally than you intended. I wasn’t building a general intelligence. I wasn’t building a travel app. I was building a coordination agent — something that could: Observe availability instead of schedules. Stack partial solutions instead of demanding perfect ones. Exploit overlap between systems that don’t know they’re cooperating. And because I didn’t trust myself to stay disciplined, I let the agent enforce the rules. That agent was called TripSmith_β. WHAT TRIPSMITH IS (AND ISN’T) TripSmith is not a chatbot. It doesn’t talk unless it has to. It doesn’t “recommend.” It decides, within constraints. At its core, TripSmith does four things: Maps availability, not geography Coordinates movement, not destinations Defers decisions until the delay becomes dangerous Optimizes for continuation, not comfort It doesn’t ask if I want to do something. It asks if the system will tolerate it. TripSmith doesn’t care about flights. Flights are brittle. It cares about corridors — chains of movement, work, rest, and money that overlap just enough to keep going. It treats cities the way engineers treat components: Inputs, Outputs, and Failure modes. Chicago wasn’t a place. It was a starting condition. FUNDING THE MOVEMENT (WITHOUT SAYING “BUDGET”) There was no travel fund. There was cash flow. TripSmith understood this instinctively. Instead of asking “How much money do you have?”, it asked: “What value can you extract locally without anchoring yourself?” The answer was tech field work. Short jobs. Defined scopes. Clear outcomes. Printer installs. Network troubleshooting. Equipment swaps. On-site validation calls. Work that exists everywhere and finishes quickly. TripSmith continuously scanned gig platforms for jobs near transit hubs — not because that’s where the money was best, but because that’s where movement stayed cheap. When I worked, I paid for time. When I slept, I paid nothing. When possible, payments moved over Bitcoin and the Lightning Network — fast settlement, minimal friction, no one needing to understand why I was there. TripSmith approved this quietly. “Reduced dependency detected.” CHICAGO: WHERE IT BECAME REAL TripSmith could have sent me east in a dozen ways. It chose the bus. Not because buses are good. Because buses persist, flights are canceled. Trains sell out. Buses adapt. What TripSmith found was a pilot program — not for passengers, but for infrastructure. A Greyhound corridor test. Wi-Fi access points were being upgraded at major bus terminals across the Midwest and Northeast. Some buses would carry new equipment. Others would carry scanners. Others would generate traffic. Testing happened before I arrived. Testing happened after I left. Most testing didn’t need me at all. But some of it did. Those moments — the secure networks, the physical connections, the conversations with Greyhound IT and security — required a human. That human was me. TripSmith expanded the corridor deliberately. Not because Greyhound ran a single neat route, but because testing benefits from redundancy. Some cities were passenger stops. Some were equipment staging points. Some were simply places where opportunity clustered. The corridor looked like this: Chicago → Fort Wayne → Detroit → Cleveland → Columbus → Pittsburgh → Baltimore → Philadelphia → NYC → Hartford → Boston Not all on one bus. Not all are on board with me. But all connected. Each stop came with extra time — time to validate networks, time to work gigs, time to recover just enough to keep moving. TripSmith labeled this: “Sustained forward motion with compensated dwell time.” I called it a long bus ride with paperwork. THE FIRST WARNING SIGN Before I boarded, TripSmith ran an audit. User adaptability: High Tolerance for inconvenience: Unproven Attachment to normalcy: Concerning Likelihood of improvising: Excessive Then it logged a decision I did not approve, but also did not stop: “Proceeding anyway.” The bus left Chicago before dawn. I boarded with a backpack, a laptop, a phone, and an AI agent quietly coordinating everything I wasn’t thinking about. TripSmith logged the moment the doors closed as: “Experiment active.” That was the last moment the trip felt hypothetical. Boston was somewhere ahead. Everything else was already in motion.
