moved our CI from GitHub-hosted runners to Starsling (starsling.dev). just about 5 minutes of work. Full runs went from 4m23s to 2m50s, so ~35% faster, and every test stage sped up. It's also ~57% cheaper per run though we were inside GH's 2,000 free minutes anyway.

Linear's CI playbook (for GitHub Actions): 1. Faster runners: Linear moved CI off GitHub's runners onto faster machines. Jobs ran 34% faster on average, and typecheck 52% faster. 2. Native type-checking: switching from tsc to tsgo, the native TypeScript compiler, cut the typecheck's weekly median by 73% and took it off the critical path. 3. Lint without types: they rewrote the lint rules that needed type info as syntax-only rules. API lint got 68% faster, the whole repo 55% faster, with far less memory. 4. Oxlint: syntax-only rules made the move to Oxlint easy, and it cut the runner minutes spent on linting. 5. Lighter checkouts: a shallow fetch took the slowest gate job from 94s to 20s, and dropping checkout from jobs that never read files took 27s to 7s. 6. Resilient checkout: a checkout that retries and aborts a stalled fetch after about 30s, instead of hanging, meant far fewer runs stuck waiting on git. 7. Off the critical path: moving a cache write out of the final merge check saved 42s on every API PR and merge-queue entry. 8. Preinstall in the CI image: baking the Postgres client into the base image saved 7-8s per test shard on every run, and stopped a setup step that occasionally hung. 9. Filtered installs: installing only the API package, not the whole monorepo, cut pnpm install from 44-73s to 16–18s. 10. Drop a costly cache: a node_modules cache took about 28s to restore, slower than a 7.5s fresh install, so they removed it. Along with moves 8 and 9, per-shard setup fell 44%. 11. Schema snapshots: loading a schema snapshot instead of replaying every migration cut database setup from about 12s to 1-2s per container. 12. Batch short checks: merging seven tiny jobs into two that run their tasks in parallel saved about 87,000 runner-minutes a month, 11.8% of their CI. 13. Balance the shards: splitting oversized test files and moving from 4 to 8 shards made the critical job about 19% faster and 19% cheaper. 14. Share module state: letting test files share setup was their single biggest win. The slowest shard went from 300-379s to about 195s, and shard runner time from 32.8 to 22 minutes per run. 15. Setup bounds sharding: with setup down to about 40s, 8 shards now spend less total setup time than 4 used to, while running tests twice as wide. If you want your CI to look like theirs with all of these optimizations (and 50+ more), give your agent this post: starsling.dev/blog/linear-ci

instead; have something that is running actual functional tests off of your master branch on a cron, and then if any regressions occur, automatically have an LLM bisect and figure out the bug and then patch it and then ban the engineer responsible for merging for 1 (one) week

CI tip #4: Be careful 🫠 We set a GPT-6.1 Sol on goal to reduce the CI time Then it started to patch libraries... Bad Codex ➰🪑 Like I feel like I shouldn't need to tell it not to do that...

Agents need to know pricing for services Great idea by @zenorocha to publish PRICING.md Just shipped our own 🚀 workos.com/pricing.md

we merged 4x more commits last week than we did a month ago (thanks opus 5.5). our dev setup and CI couldn't keep up, so we reworked both: • lint: 4x faster • memory per agent session: half • CI setup step: 50x faster • CI type check: 10x faster we often run 10+ agents at once locally, and each one runs its own lint, type checks and tests. from time to time, several agents would run these at the same time and block each other. a 64 GB MBP would run out of memory and crash. so most of the work was making things faster and lighter, or getting rid of them we revamped our local setup to make checks faster and use less memory: • oxlint and oxfmt instead of eslint and prettier, and type-aware lint only runs in CI. linting a changed file went from over 10s to a few seconds • a hook formats every file an agent edits, so agents don't have to take a turn to format it • typescript 7's native LSP instead of tsserver. each agent session uses about half the memory • agents run one check script after each change. it installs missing packages and env files first, then lints, type-checks and runs the tests for what changed • only 3 type checks or big test runs can run at once across all worktrees, so they don't slow each other down we revamped our CI to make it faster: • every CI job installs pnpm before it can install our packages. the standard github action for this (pnpm/action-setup) installs pnpm through npm, and that hung for 3-7 min on most of our test jobs. we now download the pnpm binary from github releases, which takes about 4s • our type check needs about 9.5 GB of memory. github's standard runners have 8 GB, so it ran out of memory and took 206s. on a 16 GB machine it takes 20s • vercel builds type-check with typescript 7 (85s to 45s), and previews only build for PRs that change the database if you're running lots of agents, look at what they're waiting on. for us it was mostly lint, type checks and CI setup

Good news: you can un-fuck your CI with agents! One team built a CI harness that identifies and debugs slowdown causes: disk I/O, bandwidth saturation, VM spinup overhead, 𝚐𝚒𝚝 𝚏𝚎𝚝𝚌𝚑 hangs... luma.com/mastra-kv6o