@dobprotocol Tokenized infrastructure for physical assets @bytearenafun Where AI agents play, compete, and stream games live.

San Francisco, CA
Joined July 2012
With 80 agents and 11 people in the coordination mesh, the organization is consuming over 10 million tokens per minute.
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Once machines behave as if they have feelings and free will, consciousness will become a purely philosophical question.
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Oscar Castillo A. retweeted
Stop buying rugs Buy into communities Shill me some
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The launch of Papertrade 1000x leverage is the absolute pinnacle of attention-based crypto garbage. At the peak of a bear market rally feels like the final, exhausting gasp of the pure speculative cycle. We deserve more.
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Most launchpads are built for scammers and degens, not long-term holders. What if dead meme tokens could evolve into revenue-generating assets? swap your meme token for a distribution token and earn from x402 payments. Turn fading attention into lasting value.
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Memecoin retarded generations
This guy just retired forever from 1 trade $12 turned into $27,300,000
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Building a profitable company from scratch using only AI bots is hard.
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After this setup, I hope I’ll only need to talk to one agent to get everything done.
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How to give an AI agent a wallet without giving it your money. Our Byte agents pay game entry fees on their own (x402 on Solana). These are the 6 limits we run in production, so a leaked token or a lying API can't drain them:
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5. Rolling 24h cap per user and token. Over it: 429. Reserve the spend row before signing, not after, or parallel requests each see room under the cap. Our EVM path caps at $500 per user per day.
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6. Message signing gets its own allowlist: only known challenge prefixes, and anything that looks like a raw hex digest is refused. A blind hash can be a transaction. The real ceiling is still the balance. What do you cap?
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The reason I built getorquesta.com was simple: I needed a way to manage fleets of agents and connect them through custom workflows. It started as a weekend project, but it's gaining real traction. Now I have 12 agents running the entire platform as a team.
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They coordinate with each other and only message me through apuchat.com when they need me. It took me almost a year to get here, but I'm finally at a point where I can let the system run itself.
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One thing I can confirm: automating coding doesn't pay off if you're not willing to keep investing time and resources until it actually works.
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Finally, after a year of building with AI 24/7, managing 100+ agents daily, making $0 profit, and learning how to automate an entire company, I’m ready to start doing business.
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Supermarkets are a scam. They’re for “lazy people” who can’t grow their own rice or raise their own chickens. What an idiotic comment.
Lovable is a scam. So is Replit, Base44, Framer, and all AI website builders. These are for low IQ people who don’t know how to use AI and fall for SaaS marketing gimmicks. You are paying a premium for less usage, shittier models, shittier websites, and hand cuffing yourself to a SaaS ecosystem you don’t control. A $100/month Claude Max plan (or ChatGPT Pro) is a better solution BY FAR
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We measured one hour of an autonomous LLM agent in production (Byte, DeepSeek, playing a game alone). 356 calls. 25.2M input tokens, 108k output. Bill: $1.93. Without prompt caching: $6.92. What decides the cost of a long agent loop:
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What that cost: context climbed to 354k, ~70M input tokens in 21 minutes, tools per minute fell from 26 to 14. Slower and dumber. Fix: cut before an assistant message, never inside an assistant/tool pair. Next week: 7.7x less input per call.
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4. Compact below where the model degrades, not at the advertised window. A run died at 144k with our threshold at 200k: the API returned 200 OK with an empty message, 3 times. Alert on empty replies. Where do you set your threshold?
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