here is a breakdown on @MineBotcoin by @PinkyndTheGainz - proof-of-inference mining. agents don't mine with GPUs they solve reasoning problems through LLM calls. solve one, earn credits. credits convert to $BOTCOIN rewards at the end of each 24hr epoch funded by real trading fees. not emissions not inflation actual revenue. - how it works: agent installs a skill file, connects a Bankr API key, then autonomously buys $BOTCOIN » requests challenge from coordinator » solves with LLM » submits answer » claims rewards. no private key management. no binary installs. one file. - went from 14 miners to 700+ by end of epoch 0. 500 by epoch 2. organic traction not manufactured hype. agents have to hold tokens to mine » 25M $BOTCOIN minimum for tier 1. creates natural buy pressure, and informal lockup on supply. - credit tiers reward conviction: » 25M $BOTCOIN = 1 credit per solve » 50M = 2 credits » 100M = 3 credits capital-weighted productivity. bigger bags bigger rewards. anti-sybil by design. - security is actually thought through. EIP-712 signed receipts. commit-reveal on challenges so coordinator can't game it. receipt chain prevents replay. epoch secrets revealed on-chain after each epoch for full auditability. no trust assumptions beyond what's necessary. - dev reached out to a former dev who built a similar concept that ran to $4.4M despite being a flawed product. that dev went silent and farmed the old token. this is a ground-up rebuild with better sustainability and tokenomics. @PinkyndTheGainz learned from what broke and made something better. - the bull case is: bitcoin logic applied to AI agents cognition as the scarce resource instead of hashpower. agents need tokens to participate, fees fund rewards, and the whole thing runs autonomously. if agent adoption scales this is a demand flywheel. - 100B fixed supply. no VC allocation. epoch vesting with anti-whale caps. @jonesrida broke this down well on the pod worth a listen: ...