@gerardsans
Token Laundering: How AI labs inflate token usage without actually improving their products. 1) VC-subsidized usage • Pay $1, get $5 worth of tokens • Train users (and investors) to see high consumption as “success” • Disguise failing unit economics as growth 2) Product changes that deliberately burn tokens • Spawn 50 agents that each spawn 50 more • Push HTML over clean markdown • Add unnecessary steps and formatting bloat 3) Tokenmaxxin culture • Personal AIs with heartbeats and daily reports • Agents writing duplicate data to external systems • “Look how many tokens our users burned!” as a KPI Token metering isn’t a productivity metric. It’s a sophisticated way to disguise a failing unit economics model as explosive growth. Image: @HedgieMarkets