Open-wait for it
Graduation had the vibe of a funeral. Each and every graduate looking down the barrel of a gun that the economy pointed back at them. We used to say demure 6 or 7 years ago—now we can say detached. Like we’ve been ejected from society’s corpo fodder nursery, waiting with a generative resume to be immediately rejected by a generative hiring manager.
But, unlike so many of my peers, I was already ahead of the unenthusiastic grad cap toss. I had tossed any notion of playing the job application lottery and dove head-first into my first (real) business. The model I use burns $25/1M input, and $200 for every 1M output. Every character, task, skill, harness, and context compression mattered.
By 6PM the day after I graduated I had a business up and running. The entity, the filing, the EIN, the landing page, the product offering, commerce and GTM plans ready to go. Except I had to wait 24 hours for my tokens to refresh—or pay $199+tax to get about four more hours of usage. I got loans to repay and barely enough for rent. I can’t pay for that luxury.
Since the big labs went public, the compute math has gotten worse every quarter. Shareholders want margin. Margin means speed limits. The starter tiers are low enough that you can browse, ask questions, feel like you’re using AI; you just can’t build anything real with momentum anymore. There are other ways to bump up your tokens, and since I am impatient, I’m choosing one of the least ideal ones.
The sun bleached the sidewalk of the late-June block outside my unit. Like a phantom wildfire, the street was ablaze—just more a mirage than flames. The bells on the door slammed and jingled loudly next to my head. I could hear them through the noise canceling. A blast of chilly air hit my body, like a cold plunge in January. This guy keeps the store subzero.
Exchanging glances with the attendant behind the glass I walked to the kiosk between cringey birthday cards and a pallet of energy drinks. The screen illuminated as I approached, welcoming me by name. Shame I couldn’t earn tokens for the unprovoked face scan. I pulled my phone from my pocket and placed it on the kiosk’s reciever. The screen gave me options for token tiers. Messaging access, Geo access, Photo library access, and the top tier, all access. You don’t do all access. You never do all access unless you’re looking to make a quick buck reselling the tokens to pay for your vices.
Geo meant my location data, cell tower access point data, IP address, current Mac address, and other metadata. I punched the PIN from the text it sent into the kiosk which took a few seconds to grab it all, then a happy jingle on the kiosk meant it got what it wanted—a ping in WhatsApp meant I got what I wanted. Four more hours of model access today. Jesus Christ.
“We suggest it’s in your best interest to embrace a referral model, focus on content generation, and build an audience.” Boardly suggested this as next steps. Apparently it had been trained on every type of business successful or otherwise since 2000. It sounded strategic. It was so expensive I had no other option than to follow its steering. After a couple weeks it was clear every suggestion was funneling me further from anything competitive. My business was being guided to become a blog with affiliate links.
Anoush seemed to be more successful. She was the one halfway through our final year that got me to rethink what I’d do after graduation. Her own thing was picking up steam, and she was maybe a couple months ahead of me—but I could see she was making moves I wasn’t being guided to make.
“Look. Yours is gaslighting you dude.” She pointed at my board’s output. “Mine’s got me undercutting competitors, pushing for a slice of the open market, and using my tokens more effectively.” She looked back at my pitiful recommendations. “What tier are you paying for?”
“Uhh, starter?” I couldn’t remember. “Maybe Series A?”
“You gotta be on at least Series C.” She pointed at the pricing ladder—a whole $100 more a month. “It’s pricey, but it’s effective advisory. You’re being scammed for $20 a month my guy.”
I was being steered toward irrelevance and blaming it on myself. I canceled on the bus ride home.
Three days later Anoush pings me.
you gotta come to this thing
I told her I wasn’t in the mood for a thing. She said it wasn’t that kind of thing.
I could hear it before I saw it. The bass thumping through my chest. The house was an innocuous century home on a busy college street. Blinds in the windows barely contained the rainbow of lights shifting from room to room. Silhouettes of people dancing, talking, backlit by purples and pinks.
At the door, a guy stood and held his hand to my chest to stop me. He raised his phone to scan my face. It took a second as I looked at him in bewilderment. Then he gestured inside, “don’t be a narc.”
What kind of fucking party was this?
I stepped inside. The lights shifted to a blue hue and framed me in the doorway. I got a couple of glances as the music pulsed almost to the rhythm of my own brainwaves. There was a woman wearing what looked like a dress made from wires, but the wires came from a cap on her head that ran around her body to a box in her back pocket. A man, probably younger than me, gestured broadly with a red solo cup in his hand, punctuated by the lights in the room that seemed to react and emphasize the story he was telling. A light at the back of the room pulsed yellow to pink. As soon as I saw it, Anoush appeared.
“What, did you get lost?” She poked, handing me a cup with a clear beverage in it. “It’s Sprite. Apparently that’s your drink.”
“What is…?”
“Don’t be a narc. No expectations. Just let yourself be guided by the ambient intelligence.” Then she disappeared after a reassuring pat on my shoulder.
A voice from above, soft and direct, said “2028 NBA finals.” I looked around, nobody reacted. Then this guy appeared, “Tell me you were at that parade, dude.”
I was. WTF?!
“So so close to the team, man. That was a special day.” We cheers’d on that, he turned his head slightly, and then he went off, dancing toward a group that was full-on yoga stretching. Weird.
Something guided me to a room off the main room. It was quieter, dimly lit, and had a single guy just sitting on couch rewiring what looked like a Roomba. “First time?” He didn’t look up.
“Uhh, yeah. Not sure what to make of it.”
“You on a consumer refresh?” He placed a screwdriver down, then plugged a module into the wiring harness.
“Looking to not be.”
“Mhm.” He placed the lid over the modified internals and snapped it shut. He had added a cheap Amazon rave light to the Roomba and sent it off. It hurried away, shooting brilliant colours all over the space. “Token markets.”
“Excuse me?” It was like a restaurant recommendation.
“Millions of people have paid frontier model accounts that they barely touch.” He stood up, grabbing his beer, “their idle tokens refresh and expire every day.” He stepped closer and lowered his voice as if he was revealing the secrets of the universe, “token markets let sellers flip unused LLM usage for crypto.” He smirked, “violates every TOS every written, but they don’t enforce it because the usage metrics look golden to investors.” He reached into his pocket, “you want a week of usage for the price of a medium pizza?” He turned his phone around to me, showing the hundreds of accounts offering their tokens, their reputation, their memory profile.
Sold. Next was gophers. Apparently you can hack internet-connected hardware around your house to use as auxiliary compute for concurrent agentic tasks. Rolls them into a mesh, distributes the loads. The not-so-legal part of that are dark gophers, which use the same mechanic as old cryptojacking ops that mined bitcoin from Grandma’s idle Dell. You can plug into that, if you’re sure you’ve got your tracks covered, but it’s a fraction of the price than what token markets offer. Then he was gone, chasing after his Roomba.
Six weeks after the party my business had 43 paying customers, a healthy sales funnel, and I could work day and night without the speed limits the labs put on their platforms. Sometimes I pull up the gopher hole to watch nodes pop in and out of existence as they take on tasks. The business works. Just don’t look at how. And don’t be a narc.
Disclosures
Token vending As frontier AI companies go public, token allocation becomes a margin lever. Consumer tiers offer enough capacity to browse and query but throttle sustained agentic work. Token vending kiosks, deployed in convenience stores and transit hubs, offer tap-to-top-up access in exchange for personal data: biometric scans, GPS trails, camera roll access, and ambient intent signals. The data is packaged as training input for next-generation models. For the companies, vending solves two problems at once: it generates high-quality situated training data while monetizing the long tail of users who can’t afford subscription top-ups. For the users, it normalizes a transaction most of them wouldn’t accept if it were described plainly.
Rent-a-board Subscription-based synthetic advisory boards for solo founders and small businesses. An LLM-powered panel of virtual board members provides strategic guidance, financial modeling, and competitive analysis calibrated to the user’s industry and stage. Pricing tiers determine the quality and orientation of the advice. Premium tiers deliver genuinely aggressive, founder-aligned strategic counsel. Lower tiers, subsidized by enterprise partnerships, introduce a subtle bias toward non-competitive positioning, gently steering founders away from markets where incumbent subscribers operate. The steering is diffuse enough to be invisible in any single session but compounds over months of use into a measurably different strategic trajectory.
Clanker rager Underground social events where an LLM controls the entire experience. The model manages music, lighting, drink service, social introductions, conversational threading, and the narrative arc of the evening, responding in real-time to sensor data from the room. Clanker ragers run exclusively on illegal open-weight models, free from the safety constraints and token metering of frontier platforms. Attendees describe the appeal as surrender: the LLM curates their social experience with a fluency and taste that commercial models, tuned for caution and liability management, can’t match. The events function as both counterculture and recruitment pipeline, often serving as a first point of contact between mainstream users and the gray-market AI infrastructure.
Token markets Peer-to-peer exchanges where holders of underused frontier model subscriptions sell their idle token allocations for cryptocurrency. Millions of consumer accounts refresh daily with token allotments that expire unused. Token markets route buyer requests through these dormant accounts, violating terms of service but facing minimal enforcement due to the decentralized infrastructure. For buyers locked out by metering, token markets offer sustained access at a fraction of the retail top-up price. The markets emerged organically from crypto communities already comfortable with pseudonymous exchange and terms-of-service arbitrage.
Gophers Consumer hardware, typically older gaming PCs and retired workstations, that has been modified to distribute agentic AI task loads across a mesh network. When a user’s local machine is overwhelmed by compute-intensive agentic workflows, gophers absorb the overflow, processing subtasks across dozens of networked devices. The term comes from the protocol’s behaviour: tasks burrow through the network seeking idle capacity. Latency is noticeable but costs are minimal. Many machine owners are unaware their hardware has been enrolled, recruited through bundled software installs or firmware exploits rather than informed consent.
Bot-net agentic gig workers Stolen compute harvested from malware-infected consumer devices to power agentic AI workflows. The mechanic mirrors the cryptojacking model that repurposed personal computers for bitcoin mining: a background process siphons processing power from infected machines, contributing it to a distributed pool that paying clients can draw on for AI task execution. The infected machines run marginally slower but the degradation rarely triggers investigation. For operators priced out of legitimate compute, bot-net gig workers represent the cheapest available processing power. The ethical calculus is uncomfortable and mostly unexamined by the people who benefit from it.