Logan Kilpatrick

Erik Torenberg × Nathan Labenz × Logan Kilpatrick × Tulsee Doshi

Gemini 3.5 Flash leads with Tulsee citing roughly 280 tokens per second, about three times faster than other large models and significantly cheaper, prioritizing intelligence per dollar and second.Google is shifting its AI stack toward Antigravity’s shared agent harness, while preserving harness diversity; the payoff is a cross-product feedback loop, but co-optimization could still raise switching costs and pricing power.

Logan Kilpatrick × Nathan Labenz

Google’s AI usage rose 50× to roughly 500 trillion tokens monthly, strengthening the case that compute infrastructure, TPU scale, and organizational execution will increasingly separate frontier models.Application startups still benefit from speed and focus, while diffusion models and cheaper AI tools could create new software discontinuities even as frontier-model training consolidates.

Nathan Labenz × Logan Kilpatrick

Google put Gemini 2.0 Flash into production at 10 cents per million input tokens and 40 cents per million output tokens, targeting text-to-app products with an estimated 40x reduction in LLM costs.Flash-Lite preserves the 7.5-cent price point while Pro pursues capability-first coding and reasoning, but Live API co-presence remains constrained by cost, memory, state, and a 10-minute session limit.