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How we made claude.ai 3x faster in two weeks

3 hours ago
  • Claude.ai and desktop app improved about 3x in a two-week sprint by measuring and optimizing user journeys.
  • Four key user journeys (95% of activity) were targeted: launching app, starting conversation, loading existing conversation, sending message.
  • 75th percentile load times dropped from 3.1s to 0.55s (fresh web load), 0.8s to 0.3s (new Claude Code session), and 2.6s to 0.73s (cloud session).
  • Claude used an internal research model (comparable to Opus 5.5) to find bottlenecks, build benchmarks, and ship improvements.
  • Over 3,000 changes were merged without a single customer-facing incident or rollback.
  • A Slack channel with Claude as facilitator monitored performance, analyzed Datadog data, and proposed optimizations.
  • Initial 20 projects hit 12 of 13 targets within three days; Claude then identified additional opportunities exceeding original goals.
  • Measurements like instruction counts, V8 call counts, and layout shifts were used as deterministic benchmarks to drive optimization.
  • Claude cut instruction counts by 48% and 31% on hot paths, reducing wall-clock time by 78% and 44%.
  • Layout instability was addressed by mapping shifts to named regions and adding integration tests, fixing 31% of loads with unwanted movement.
  • Claude found and fixed issues: unnecessary React hooks, slow CSS selector, hidden location.reload() causing 500k daily reloads, and UTF-16 slowdown from em dashes.
  • Safety mechanisms included automated reviews, human approvals, unit tests, feature flags, and incremental rollouts.
  • Over 200 feature flags were introduced and cleaned up; dozens of guardrails protected performance wins.
  • A sidequest improved streaming reply performance: reduced main thread blocking from 750ms to 200ms, used 1/3 CPU, maintained 120fps.
  • The sprint loop: find measurable metric, Claude climbs it, guardrails prevent regression, all in open Slack threads.
  • Human team provided ambition, taste, and direction; Claude autonomously opened new threads for opportunities.
  • The approach saved tens of thousands of user-hours of waiting per day.