DeFi LPing is broken. @PositronFi wants to fix it Most #LPs still guess where to park liquidity — chasing “highest APR” pools without realizing dozens of better options exist for the same pair (like $SOL – $USDC) Each pool has different fees, tick spacing, and depth. Capital ends up stuck while better yields appear elsewhere That’s where Positron comes in👇
We’ve made the Jupiter for LPs In a single click, we route your capital across multiple AMMs to the highest performing pools across the entire @Solana ecosystem. This has never been done before We raised $500000 from @alliancedao to make it happen
@PositronFi will make your DeFi experience better How? Instead of locking your liquidity in one pool, Positron spreads it dynamically across Solana venues like @orca_so, @Raydium, and @MeteoraAG Your funds move automatically to where they earn the most It treats Solana as one unified liquidity layer, routing LP capital to the best-performing pools in real time
Sounds nice! But how does it work? It’s a bit on the technical side, but I’ll make it easy for you Positron runs an optimization engine built around 4 steps: Quality scoring → Band creation → Constraints → Optimization Let’s break that down👇
Step 1: The Quality Function Every tick in every pool gets a score Q(t,p) that measures how good that price point is for placing liquidity - Q(t,p) is the quality of tick t in pool p It factors in volume, fees, depth, volatility, and impermanent-loss risk - High Q = high yield potential It’s how Positron decides where each $1 of liquidity should go
Step 2: Bands (Price Ranges) Ticks are grouped into bands, or small price ranges like $950–1050 Each band’s total score is calculated from the sum of all its tick qualities Instead of scanning every tick manually, Positron uses prefix sums to compute band quality instantly — finding which ranges across pools perform best
Step 3: Band Constraints To keep things efficient, Positron adds 3 key rules: 1️⃣ Minimum band size — no ultra-narrow ranges that exit too fast 2️⃣ Stabilization window — avoids volatile zones near the market price to limit impermanent loss 3️⃣ Edge slack — small flexibility at pool boundaries for smoother allocation Together, these ensure LP capital isn’t wasted in unstable zones
Step 4: Optimization Finally, Positron solves a best-combination optimization: Out of all possible bands across all pools, pick the combination that maximizes total quality under a given “budget” It uses Dynamic Programming (DP) to efficiently find the best mix of bands — meaning your liquidity is always placed where it can work hardest For example, suppose we have two pools (A and B) with tick qualities: - Tick 1: Q(A) = 2, Q(B) = 3 - Tick 2: Q(A) = 4, Q(B) = 2 - Tick 3: Q(A) = 1, Q(B) = 5 Then the quality scores are:  A[1,2) = 6, A[2,3) = 5, B[1,2) = 5, B[2,3) = 7 If the budget K = 2, the best selection is A[1,2) (6) + B[2,3) (7) = 13 total quality, which represents the most efficient liquidity distribution under all rules
I’m bullish because this setup protects LPs By avoiding high-volatility ranges, @PositronFi reduces slippage and impermanent loss And with a 1% setup fee (no swap or yield fees), it stays LP-friendly while driving trading volume
Why it’s smart @Uniswap V3 gave #LPs the freedom to set custom ranges @PositronFi automates the entire process with a quantitative model No manual management, no guessing games. Just optimized yield across @solana
@PositronFi is the first LP aggregator on @solana Next up: advanced APR modeling and support for more venues — meaning even broader liquidity routing and higher efficiency It’s still early, but if Solana #DeFi keeps scaling, this kind of optimization layer could quietly become the infrastructure behind it all Looking forward to what’s coming from @srhposfi & @ademplabbers Winter Soldier, out
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