What problem does it solve?
It prevents common onchain design misunderstandings by teaching the mental models behind how Ethereum-style systems actually work, so you can design systems that won’t fail due to incorrect assumptions about automation, operators, state transitions, and incentives.
Core Features & Use Cases
- What Ethereum gets wrong (and what to fix): clarifies misconceptions like “smart contracts run automatically,” “just add a timer,” and “the team will handle it.”
- Incentive-first state machine design: explains that contracts do nothing between calls (“someone pokes it”), and that each transition must have a credible caller and incentive.
- Practical guidance for hard primitives: covers why randomness is hard on deterministic systems and when to use commit-reveal versus VRF.
- Teaching your human effectively: provides context-based explanations for common building blocks (DEXs/AMMs, lending, oracles, stablecoins, multisigs).
- Use cases: onboarding new builders, validating a system design before implementation, and correcting design decisions early (before they become dead code).
Quick Start
Use the concepts skill to explain how “nothing is automatic” and incentive-driven state transitions determine which onchain actions can actually happen, then ask it to apply those principles to your system design for one concrete workflow.