Use case
A frontend or performance engineer who takes over a slow-loading open-source repo hands it to Makefaster.dev, which runs autoresearch loops that repeatedly edit the code against the Lighthouse score, and receives the sped-up result.
Engineers typically use Lighthouse or WebPageTest to locate bottlenecks by hand, then edit code and re-measure themselves, or rely on manual performance reviews and rule-of-thumb heuristics.
Performance work means measuring metrics, editing code and re-measuring over and over; the author reports spending about $10k in API costs to run the loop across 200 frontend repos, showing the loop itself is expensive and doing it by hand per repo costs even more.
xOcto's call
Demand is evidenced
Trend: performance work that used to be manual trial-and-error is being batch-run by autoresearch loops. Entry: start from open-source maintainers or outsourced performance tuning, charging per project or per result; pricing and how changes are delivered and accepted are not disclosed.
Reason to use it
Why users would choose it
Inference: versus manual item-by-item diagnosis, it automates the whole measure-edit-remeasure loop and uses the Lighthouse score as a checkable convergence target, removing repeated manual measuring and trial-and-error; so frontend teams facing many repos to optimize without dedicated performance staff would pick it when they need batch speedups. No user feedback or adoption record is public, so the motive is a structural inference.
Where the easy answer breaks down
The tension worth following
An English validation note will follow from the public evidence.
If this is your job
Worth trying. Inference: versus manual item-by-item diagnosis, it automates the whole measure-edit-remeasure loop and uses the Lighthouse score as a checkable convergence target, removing repeated manual measuring and trial-and-error; so frontend teams facing many repos to optimize without dedicated performance staff would pick it when they need batch speedups. No user feedback or adoption record is public, so the motive is a structural inference.
Entry and what to borrow
Trend: performance work that used to be manual trial-and-error is being batch-run by autoresearch loops. Entry: start from open-source maintainers or outsourced performance tuning, charging per project or per result; pricing and how changes are delivered and accepted are not disclosed.