RMPL

Summary

RMPL launched on Ethereum in early August 2020 — presale on August 2, Uniswap listing on August 3 — as a direct fork of Ampleforth with one deliberate mutation: the rebase fired at a random moment. Where AMPL adjusted supply on a fixed daily schedule that traders learned to anticipate, RMPL's adjustment occurred at an unpredictable time within a window of up to 48 hours after the previous one, averaging roughly every 24 hours, triggered when price left a $0.95–$1.05 band around a $1 target. The anonymous team, which never published a whitepaper, framed the randomization as an anti-manipulation measure: the profitable strategy against AMPL-style tokens was to trade the known rebase clock, and a clock nobody can see should have no front-runners. The token rode the same August 2020 elastic-supply wave as Based and YAM and faded with it by the end of the year.

Design (Mechanism)

The inherited machinery is Ampleforth's: an oracle price, a target, and a supply change applied proportionally to every wallet so holders retain their share of the network. RMPL's contribution is confined to when. After each rebase, the next one became eligible at a random point inside the following 48 hours, with the randomization also applying a variable lag factor to the magnitude of adjustment, and a supply-dependent acceleration between 10M and 100M tokens. A rebase only executed if price sat outside the $0.95–$1.05 band, so a quiet market produced no adjustment at all.

The design question RMPL isolated is real and recurs across this Atlas: any mechanism with a public schedule invites optimisation against the schedule rather than participation in the mechanism. Randomizing the timing removes the focal point — there is no moment before which to buy and after which to sell — at the cost of removing the legibility that made the game attractive to play at all.

Outcome

RMPL traded actively through August 2020's rebase mania and declined with the cohort as attention moved on. The randomization worked as mechanism — rebases fired unpredictably, and the token could not be clock-traded the way AMPL was that summer — but it did not change the underlying economics: an elastic supply with no demand sink still redistributes value from late holders to early exiters, at random times rather than known ones. With an anonymous team, no whitepaper, and no development beyond the fork, the project wound down into inactivity within months. No exploit or rug is documented; it was abandoned rather than broken.

Why it worked

• The randomization addressed a genuine and precisely identified failure mode — schedule-trading — with a minimal, testable change to a proven codebase, which is good experimental method.
• Unpredictable timing did blunt the dominant AMPL strategy of the period: without a known rebase moment, the buy-before, sell-after trade had no anchor.
• Launching into the August 2020 elastic-supply wave gave the one-variable experiment immediate liquidity and attention that a standalone launch could not have bought.

Why it failed or underperformed

• Randomizing the clock treated a symptom. The value redistribution of a rebase token comes from the supply mechanism itself, not from its schedule; hiding the timing changes who wins the game without changing what the game is.
• Legibility was the product. AMPL's known cadence is what made rebase trading a mass activity; removing it removed the reason most participants were there, and the anti-manipulation feature was also an anti-participation feature.
• Anonymous team, no whitepaper, and no roadmap meant there was nothing to hold onto once trading interest faded — the experiment had no second act by construction.

Lessons

• Distinguish between a mechanism's rules and its schedule before randomizing either: unpredictability defeats timing strategies but cannot fix an incentive structure that redistributes rather than creates value.
• Randomness in onchain mechanisms is only as good as its source; a design whose fairness claim rests on unpredictable timing needs a manipulation-resistant randomness beacon, or the randomization becomes the new attack surface.
• A one-variable fork is a legitimate experiment, but it inherits every unfixed property of the original — including the ones that determine whether the project survives.

Redesign (EDITORIAL)

EDITORIAL — hypothesis, not fact. A stronger version of this experiment might (1) draw rebase timing from a verifiable randomness source (a VRF or a beacon) rather than contract-internal pseudo-randomness, so unpredictability is provable rather than asserted; (2) pair the random schedule with a demand sink — a fee routed to a reserve that supports the band from below — so the mechanism has something to stabilise besides sentiment; (3) publish the randomization distribution and its bounds as a first-class spec, letting participants price the uncertainty instead of merely being surprised by it; and (4) predefine success metrics for the single variable under test — deviation from target versus AMPL over the same window — so the experiment could end with a finding rather than just an ending.