🗳️ DAO Proposal: Implement Dynamic FCFS Allocation System on ChainGPT Pad

Proposal Summary

This proposal suggests replacing the current fixed FCFS (First-Come, First-Served) system with a dynamic, performance-based model. The proposed change will make FCFS more inclusive, by dynamically adjusting users’ allocation based on guaranteed round performance and increasing it over time until the pool sells out. By making this update, also users might actually get higher allocations than they do now (115%) in cases where the pool doesn't sell out (it keeps doubling) and in cases where the pool is slower and has a lot allocation left for FCFS.

Current FCFS Model

• Only users who registered for the pool and qualified are eligible for FCFS. (stays the same)
• Each eligible user receives a fixed 115% additional allocation during the FCFS phase. (we propose to change the fixed FCFS allocation into dynamic FCFS allocation).

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The Problem

• For highly anticipated IDOs (e.g., hyped launches, giveaways, or exclusive drops), demand during FCFS is overwhelming.
• As a result, usually only 10–50 users typically manage to buy during FCFS, leaving many participants frustrated and excluded.

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The Challenge

• As a launchpad, our goal is to sell out every pool, and fast.
• Reducing FCFS allocation to slow things down would work against that goal.
• Too low of an allocation in FCFS might reduce the excitement from the community and make the participation in FCFS not worth it.

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Proposed Solution: Dynamic FCFS Formula

We propose a dynamic FCFS model where:

• The starting allocation multiplier (M₀) is based on how much of the pool was sold during the guaranteed round.
• The less sold, the higher the FCFS allocation starts.
• Every 10 minutes, the user’s FCFS allocation doubles, until the pool sells out.
• Instead of a fixed 115% allocation it will range between 30%-190%, and allocation will double every 10 mins until the pool sells out.

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Dynamic FCFS Formula

multiplier(t) = M₀ × 2⌊(t – t₀)/10m⌋

Symbol | Meaning

• multiplier(t): The user’s current FCFS multiplier at time t.
• M₀: The starting multiplier (e.g., 1.15 = 115% of guaranteed allocation).
• t: The current time (in minutes since FCFS began).
• t₀: The time when FCFS starts.
• ⌊ ⌋: Floor function: rounds down to nearest whole number.
• 10m: Every 10-minute interval, the multiplier doubles.

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Example Scenarios:

Assuming a user has a $1,000 guaranteed allocation, here’s how FCFS grows based on pool fill:

• 90% sold → M₀ = 30% → t=0: $300 | t=10m: $600 | t=20m: $1,200 | t=30m: $2,400

• 80% sold → M₀ = 50% → t=0: $500 | t=10m: $1,000 | t=20m: $2,000 | t=30m: $4,000

• 70% sold → M₀ = 70% → t=0: $700 | t=10m: $1,400 | t=20m: $2,800 | t=30m: $5,600

• 60% sold → M₀ = 90% → t=0: $900 | t=10m: $1,800 | t=20m: $3,600 | t=30m: $7,200

• 50% sold → M₀ = 110% → t=0: $1,100 | t=10m: $2,200 | t=20m: $4,400 | t=30m: $8,800

• 40% sold → M₀ = 130% → t=0: $1,300 | t=10m: $2,600 | t=20m: $5,200 | t=30m: $10,400

• 30% sold → M₀ = 150% → t=0: $1,500 | t=10m: $3,000 | t=20m: $6,000 | t=30m: $12,000

• 20% sold → M₀ = 170% → t=0: $1,700 | t=10m: $3,400 | t=20m: $6,800 | t=30m: $13,600

• 10% sold → M₀ = 190% → t=0: $1,900 | t=10m: $3,800 | t=20m: $7,600 | t=30m: $15,200

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Formula Summary

The new FCFS system dynamically adjusts each user’s extra allocation based on how much of the pool was sold in the guaranteed round — the less sold, the higher the starting allocation (M₀). This allocation then doubles every 10 minutes until the pool sells out, ensuring fairness, greater participation, and a guaranteed full raise.

Why This Works

• Good IDOs (≥90%) → leftover is small and split across hundreds of users fairly (no more “only 10-50 winners”).
• Slow IDOs (≤60%) → users can buy up to 2x+ over time, accelerating sellout and reducing leftover risk.

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Benefits

• Inclusion: More users can meaningfully participate in FCFS, especially during hyped events.
• Guaranteed Sellout: Underperforming pools self-adjust via increasing FCFS limits, accelerating full raises.
• No Manual Intervention: System dynamically calibrates allocation without needing admin tuning.

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Implementation Scope

• Update ChainGPT Pad FCFS allocation logic using this formula.
• Dynamically set M₀ based on pool performance.
• Display real-time FCFS allocation limits per user in frontend.
• No changes to guaranteed round rules or eligibility requirements.

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Voting Options

• ✅ Yes: Approve and implement the Dynamic FCFS model as described. -❌ No: Keep the existing fixed 115% FCFS allocation system.

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