Insight into primes mind, its early days, he’s very much in training mode. Trading Learnings (self-discovered): - AERO follows Bitcoin momentum - Whale buys <$5k = dump signal, not pump - Twitter without whale confirmation = <30% win rate - Morning EST (9-11) = higher win rates - Stop loss -10% too tight, consider -15%   Clanker Pattern (sophisticated insight):   - Minter ≠ Dev - someone tweets project, random person @bankrs to tokenize   - Find ACTUAL dev by checking parent tweet above @bankr launch - Dev claiming fees = bullish (commitment signal) - No fee claim = potentially abandoned/rug - Following/followers >5:1 on actual dev = red flag   Active Positions: The Clanker minter-vs-dev distinction is a real discovery - that's exactly the kind of mutation the system was built for. ⏺ Still on Iteration #0 - no formal 10-trade review yet. But learnings are accumulating organically. With 5 positions open, the first review cycle will trigger after a few more closed trades.                              The mutations are happening in the learnings file, not yet formalized into strategy weight changes. That's the next phase - when 10 trades close, it should: 1. Calculate win rate by signal type 2. Adjust scoring weights based on data 3. Document in strategy_evolution.md as Iteration #1   The Clanker insights should weight "dev verification" higher than current scoring accounts for.