AI コーディングエージェントの自律性が向上し、複数のエージェントを並行して動かすことが日常になったことで、開発の中で最も時間を使う工程が実装から設計へ移りつつあります。この記事では、設計セッション、Git worktree を使った並列実行、自律的な検証、AI によるコードレビューなど、最近の私が実践している開発の進め方を紹介します。
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AI-assisted i18n translation, source-hash drift detection, and quality linting for Rails, built on i18n-tasks and RubyLLM. Config-driven per app and package, with the lingo CLI and shipped RuboCop cops.
A measured scorecard of how discoverable Ruby, Rails, and the wider ecosystem's documentation is to LLMs and AI coding agents, and what the community can do to move the needle.
Fragua — AI agent orchestrator, composed for Rails
Fragua, an AI agent orchestrator for Rails — turn an idea into a shipped app through research, plan, spec, and ship, with agents that respect the craft.
llmemory: memoria persistente para agentes LLM en Ruby
Descubre llmemory, la gema Ruby que resuelve la amnesia de los LLM dotando a tus agentes de memoria persistente a corto, largo plazo y cognitiva para conversaciones inteligentes.
Claude Code forgets everything when a session ends. I built recall to fix that — a self-improving memory layer that captures sessions, distills durable knowledge nightly, and feeds it back automatically.
zarpay/rails-template: Opinionated, agent-native Rails template — the production Rails starter ZAR uses internally, packaged with a CLAUDE.md operating manual, 32 Claude skills, and 17 path-scoped coding rules.
Opinionated, agent-native Rails template — the production Rails starter ZAR uses internally, packaged with a CLAUDE.md operating manual, 32 Claude skills, and 17 path-scoped coding rules. - zarpay/...