How to evaluate decentralized AI compute
Design an AI pilot around reproducible workloads, data boundaries, useful output, and the complete cost of accepted tasks.
7 min readRead guide
LAB COLLECTION
AI & token design
Keep computation, payment, and governance distinct long enough to evaluate each one. These guides focus on testable workloads and explicit token functions rather than speculative value.
How to use this collection
Begin with a representative AI workload and a clear data boundary. Then review whether a token has a concrete job in the service, how accepted work is measured, and which administrative powers remain. Neither a model benchmark nor a token standard proves the whole operating design.
2 articles in this collection
Token utility: give the mechanism a job description
Separate payment, resource access, governance, and incentives before adding a token to a hypothetical compute marketplace.
7 min readRead guide