A simple feedback loop model can be summarized in 6 words:

Assumption, Small Bet, Calibration.

Assumption: What do I currently believe?

Small Bet: What low-cost actions do I use to verify?

Feedback: What results does reality provide me?

Review: Where was validated, where was contradicted?

Calibration: Should I adjust my judgment, position, strategy, or pace?

Consolidation: Can this feedback become a long-term rule?

Now let me give an example using Ethereum:

Assumption: I believe that ETH, as a smart contract settlement layer, can still recapture value through L2, ETFs, staking, and on-chain activities, achieving a risk-reward ratio not inferior to BTC.

Small Bet: Is this a fact or my imagination? It may not be correct, so I need to split my ETH from a belief position into a core observation position and an adjustable position, preventing a single narrative from controlling over 30% of my asset curve.

Feedback: Observe ETH/BTC, ETF inflows, mainnet revenue, burn, blob fee, L2 value recapture, market narrative strength.

Review: The importance of the ETH ecosystem is still validated, but the value capture of ETH tokens and relative returns are questioned by reality.

Calibration: If feedback improves, then consider increasing the position; if it continues to be weak, gradually reduce to 15%-20% or lower to align the position with reality, rather than with belief.

Consolidation: A strong ecosystem does not equate to a strong currency price; long-termism is not just holding blindly; positions must serve the future, not repair the past.

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