GoKawiilThe bitter lesson tells us to scale compute to unlock frontier AI progress. The empirical record confirms this.
Focused, independent teams have demonstrated extraordinary output per unit of compute in recent years. Anthropic/Claude in code, Black Forest Labs/Flux in image generation, Luma in video generation, ElevenLabs and Sesame in speech and conversation - are all teams that have produced state of the art outputs in a rapid amount of time relative to non-bitter-lesson pilled approaches.
The optimal unit of frontier progress is a focused, talent-dense team with access to enormous compute.
This dynamic is accelerating. AI tooling is making focused teams radically more capable. What took a large team in 2022 can now be done by a five-person lab in 2026. Code generation, data pipeline automation, and open-weight models all compound the returns to talent density - and the penalty for organizational bloat. This also means the number of teams capable of frontier work is exploding.
The problem is that independence comes with a heavy structural cost - low compute utilization and uncertain access.
Frontier workloads are often unpredictable - massive training runs followed by periods of cyclical inference, interspersed with idle capacity, and many shades in between. It is difficult for individual teams to efficiently provision for this. They often have to overprovision for peaks and waste during troughs. They lack the dedicated multi-tenancy and scale to optimize job orchestration.
The result is that the field's most productive teams are also frequently its least efficient consumers of its most expensive input. Based on empirics, it is not uncommon for 30-40% of all FLOPs to be frequently unused within independent teams, and yet these teams feel perpetually under-resourced on compute.
This creates a brutal choice. To access compute at scale and use it efficiently, independent teams often have to accept that a significant fraction of their most critical resource is being burned, or they must reluctantly join larger, unaligned organizations that have secured compute access at scale.
In that timeline, humanity is worse off, since the number of teams who can develop at the frontier reduces. A healthy independent frontier technology ecosystem is good for innovation.
The Grid
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