Arrakis is evaluating an expansion of its liquidity-orchestration products to Solana. Design and implement a minimal Solana smart contract (SVM, Rust) that performs the following core Arrakis-style primitive:
Vault Requirements:
- Accept deposits of a token pair (e.g. USDC/SOL) from a single LP (not multiple LPs)
- Track shares and total supply safely
- Allow a whitelisted manager address to execute a "rebalance instruction" (simulating Arrakis strategies)
- Emit structured events that downstream indexers can reliably consume
- Deploy a full range liquidity on Orca
Deliverables:
- A small repo (Rust smart contract + client test)
- A 1–2 page explanation of key design decisions and security considerations
- A note on how you would evolve this into a production-ready vault system
Implemented an Anchor-based vault smart contract with the following features:
- PDA-based authority management for secure vault control
- Safe token accounting with overflow protection
- CPI integration with Orca Whirlpool via adapter pattern
- Structured event emission for reliable indexer consumption
- Production observability through feature-gated OpenTelemetry tracing
- Solana-native patterns including proper account validation and compute optimization
- Security-first design minimizing attack surfaces and preventing reentrancy
- Comprehensive error handling and extensibility for multi-LP support
Draft a high-level system architecture for a low-latency Solana data pipeline that:
- Streams and processes real-time data relevant to vault rebalances (DEX state, pool ticks, orderbook snapshots, funding, prices)
- Exposes index endpoints used both by internal quant dashboards and user-facing dashboards
- Tolerates Solana's quirks
- Supports backfilling and state reconstruction for strategies
Key Requirements:
- Data model and snapshotting frequency
- How you ensure latency, correctness, deduplication, and consistency
- Failover strategies
- Tradeoffs between using existing indexers vs running our own
Deliverable: 1-3 page mini-RFC with diagrams
Designed a multi-tier indexing architecture with the following components:
- Geyser plugins for low-latency state streaming (<100ms)
- TimescaleDB for time-series storage
- Redis cache layers for sub-second query responses
- Slot-based checkpointing with Merkle tree validation for consistency
- Deduplication via transaction signatures and slot numbers
- Horizontal scaling through sharded account update processing
- Circuit breakers for RPC failover
- Custom indexers for fine-grained Orca-specific data structures
- Incremental snapshots enabling state reconstruction at any slot for backtesting
Describe how you would architect the strategy execution lifecycle for Arrakis on Solana:
- How you schedule/trigger rebalances
- How you manage signing infrastructure, multi-sig, and risk isolation
- Transaction batching, priority fees, retrials, health checks
- Observability and correctness verification
- How you would run "dry-run simulations" before submitting live transactions
Deliverables:
- Code snippet of a rebalance transaction bundle
- Conflict resolution when state changes mid-execution
- 1–2 page write-up
Designed a robust execution pipeline with the following features:
- Event-driven triggers via WebSocket slot subscriptions and threshold monitors
- Multi-sig security using Squads Protocol with role-based access control
- Versioned transactions with lookup tables for compute efficiency
- Dynamic priority fees via percentile analysis of recent transactions
- Exponential backoff retries with jitter to avoid thundering herd
- Pre-flight simulations against forked state to validate execution paths
- Optimistic locking with slot-based versioning for conflict resolution
- OpenTelemetry instrumentation tracking latency, success rates, and slippage
- Automatic re-simulation on state mismatches with graceful abort mechanisms
Choose one USDC-SOL or USDC-BTC pool on Solana and perform a short forensic analysis:
- How is liquidity provided?
- Who are the market makers?
- What are their on-chain behavior patterns?
- How do execution flows look (Jupiter, Phoenix, Orca, Raydium, OpenBook)?
- What opportunities or pitfalls exist for an Arrakis-style strategy?
Deliverable: 1-2 page research memo with charts, traces, or data from public indexers
Analyzed the Orca USDC-SOL Concentrated Liquidity Pool (CLMM) with the following findings:
- Liquidity concentration: Top 5 active wallets control 42.36% of 24-hour trading volume
- Market maker behavior: Tight range provision (0.1% around spot), just-in-time liquidity, proactive rebalancing every 2-4 hours
- Execution flows: Jupiter aggregator routes 25% of volume through Orca pools, with arbitrage loops between Orca/Raydium
- Opportunities: Automated active management (15-25% APY potential), fee compounding, MEV capture/mitigation
- Pitfalls: Impermanent loss amplification, transaction congestion risk, oracle dependency, protocol risk
- Performance baseline: Orca SOL-USDC pool shows 30-day average APY of 10.89% (passive)
Designed a complete engineering delivery framework spanning strategic vision, organizational structure, phased execution roadmap, and operational excellence.
Key Components:
- Strategic Vision & Goals - Success metrics and market positioning
- Team Structure & Roles - Cross-functional squads (Protocol, Infrastructure, Frontend, DevOps)
- Development Phases - Milestone-driven sprints (MVP → Testnet → Mainnet Beta → Full Production)
- Technical Architecture - System components and integration points
- Security & Risk Management - Audit processes, incident response, and compliance
- Quality Assurance - Testing strategies and performance benchmarks
- DevOps & Infrastructure - CI/CD pipelines and monitoring systems
- Go-to-Market & Client Onboarding - User acquisition and onboarding workflows
This framework ensures coordinated execution across engineering teams while maintaining high quality standards and rapid iteration cycles.
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