Glean 拾遗
Recent picks

3picks · chronological

11-12

Shopify's 12-week rewrite: agents wrote code, humans rebuilt the loop

Thirty Shopify engineers moved a 300+ screen app from React Native to Swift and Kotlin in 12 weeks, with agents writing most of the implementation. The post is about what surrounds the code: business logic runnable without a device, the Reflex architecture and a CLI that loads any screen in milliseconds, one shared architecture across iOS and Android, an example and .md file per screen, and CI that fails when the two platforms diverge. Spec-driven development was abandoned because specs went stale in days; the legacy React Native app became the reference. The second half covers the bottleneck shift — laptops saturating on emulators, review and merge queues, tickets lagging behind Slack-reported fixes — and the responses: a remote dev environment for agents, adversarial agent-first review, and a self-healing loop that reproduces crashes every 15 minutes. Results: Android launch 1.71s to 0.87s, binary 80.4MB to 47.6MB.

shopify.engineering · 19 min · Agent Workflows · Agentic Coding · CI/CD
09-20

How Anthropic scaled test impact analysis as agentic coding broke CI

Anthropic's CI absorbed a 25x increase in jobs over six months: Claude now writes 80% of the code, per-engineer quarterly output is 8x the 2021-2025 rate, and the test suite grew 10x while headcount barely moved. The bottleneck moved from writing code to PR review to CI, landing on the test impact analysis service that picks which tests run on each change. Because v0 needed a single writer to keep per-test history ordered, it ran as one process and could not be sharded. Three patches followed: doubling cores bought 70 days, per-package sharding 29 days, and daily restarts under a day. The rewrite moved history into an in-memory data store: any listener worker appends results to a journal and exits stateless, a small consumer rolls the journal into per-test history every few seconds, and the selector queries it. One engineer finished in three weeks.

claude.com · 10 min · Agentic Coding · CI/CD · Engineering Productivity
06-23

From Prompting Agents to Loop Engineering

The AI coding community is shifting from prompting agents manually to designing loops that prompt agents for you. This is the most practical, production-oriented guide available: what an agent loop is, why it matters, and what one looks like in the real world. The author breaks down the six mandatory components (trigger, isolation, written-down context, tool reach, second-agent checker, on-disk state), then illustrates with two concrete examples: a PR babysitter that checks every 15 minutes and auto-fixes CI failures, and Claude Code's /goal command. It also covers where cost actually goes (iterations, not tokens), when not to loop (one-shot edits, unbounded exploration), and predictable failure modes (verification burden stays human, comprehension debt, silent drift).

x.com · 15 min · Agent Engineering · Agent Loop · CI/CD