eng-performance

# Performance and Efficiency Awareness ## Intent - Treat budgets (frame time, network round-trips, server CPU, on-chain gas) as first-class requirements. - Prevent regressions by profiling early, not after user complaints. ## Inputs 1. Existing SLAs/budgets per platform (FPS, TTI, API latency, contract gas caps). 2. Representative workloads, datasets, replays, or load scripts. 3. Tooling: profilers, flamegraphs, shader analyzers, gas estimators, Lighthouse, etc. ## Workflow 1. **Establish baseline** - Capture metrics for the current implementation under realistic load/device tiers. 2. **Design with budgets** - Choose data structures, rendering strategies, and contract patterns aligned with constraints. - Consider caching, pagination, batching, and compression aggressively. 3. **Measure iteratively** - After each significant change, run targeted benchmarks or simulations. - Track results in the PR/issue; highlight deltas and why they are acceptable. 4. **Optimize where it matters** - Focus on user-facing bottlenecks; avoid premature micro-optimizations. - For web3, minimize storage writes and external calls; for mobile, monitor battery/thermal impact. ## Verification - Benchmarks or profiling output attached, showing no regression (or justified improvements). - Budgets documented; alarms/alerts configured if applicable. - For regressions that cannot be fixed immediately, open a follow-up issue with owner, impact, and mitigation.