Your Spreadsheet Can't Tell a Fact From a Guess
Ops decisions rot when actuals, estimates, and mocks share a cell with no tag. Provenance on every figure beats a prettier dashboard.
Ops decisions rot when actuals, estimates, and mocks share a cell with no tag. Provenance on every figure beats a prettier dashboard.
Frontier models stay spiky because useful work is contextual and counterfactual paths are ungradable. Post-training quality is a grader problem, not a pretraining-size problem.
The durable firm asset is not the model or the harness. It is the hill-climbing loop that turns a rented generalist into a company veteran you can keep.
MIT-licensed frontier-scale models make the cloud API tax optional. APIs already commoditized access to AI; open weights commoditize the price. Advantage...
AI is splitting into a commodity tier for routing and a sovereign tier for synthesis. Architect for infinite cheap frontier access and your margins are exposed.
As models improve, a growing share of enterprise value may move to the systems that let agents act safely, observably, and repeatably in real environments.
The first serious enterprise AI team should prototype a lower-cost version of one workflow, not decorate old org charts with tools.
Enterprise AI doesn't just shift the performance curve. In bad-faith hands, it becomes a control mechanism that punishes top performers for using judgment.
MiniMax hit GPT-5 performance at 10B active params via 100 autonomous optimization rounds. Xiaomi priced at $1/M via hardware integration. The benchmark race is the wrong race.
Open weights, world models, and state-level regulation are hitting the model layer simultaneously. The durable value has moved to orchestration.
Meta reportedly delayed Avocado. Apple pushed Siri. Neither has a compute problem. Frontier AI capability is organizational, not computational, and it doesn't transfer from a hiring spree.