エージェントネイティブなソフトウェアファクトリー
エージェントネイティブなソフトウェアファクトリーの構築・統制・拡大を解説するガイドと、その背景にあるポッドキャストや講演の内容を紹介します。
記事のタイトル、要約、本文は英語原文で掲載しています。
企業向けAI
ガイド
Agent readiness: fix the repos slowing your rollout
Use agent readiness to find the repositories blocking an AI rollout, prioritize fixes, and measure progress with Factory’s reports and dashboard.
記事を読むFactoryプライベート
企業向けAI
On-prem AI development inside your security boundary
On-prem AI development needs more than a local agent. Place the control plane, model endpoint, build tools, and telemetry inside the approved boundary.
記事を読むAIコーディングエージェント
企業向けAI
Context compaction must preserve the next step
Context compaction should preserve decisions and file state, not just shrink a transcript. Factory’s published study shows what to test after a long coding session.
記事を読む比較
企業向けAI
Droid vs Devin for enterprise engineering workflows
Compare Droid vs Devin for interactive coding, delegated multi-step work, and review handoffs. Separate saved instructions, persistent compute, and model configuration.
記事を読む比較
Factory Droid vs Cursor
Compare Factory Droid and Cursor through enterprise deployment, privacy, administrative controls, editor integration, and a practical pilot.
記事を読むAIコーディングエージェント
ガイド
Token efficiency starts with smaller tool results
Improve token efficiency by controlling tool output, search scope, and repeated context. Use Factory’s existing measurement and harness resources to test the result.
記事を読むFactoryプライベート
Modernization
Legacy modernization with private AI agents
Plan legacy modernization with private AI around behavior preservation, internal dependencies, and reviewable milestones. Keep code and validation inside the approved boundary.
記事を読むソフトウェアファクトリー
The architecture of a software factory
Follow a bug report through a software factory architecture, from context and planning to a tested patch, controlled release, and production feedback.
記事を読むFactoryプライベート
企業向けAI
Private AI package work needs durable context
Private AI package maintenance depends on repeatable builds and durable context. Chainguard’s published experience shows why long-running sessions deserve evaluation.
記事を読むAIコーディングエージェント
Developer Experience
Coding agents in monorepos, with clear boundaries
AI coding agents in monorepos need explicit package boundaries, local instructions, dependency graphs, and affected tests. Make large repositories easier to change safely.
記事を読むFactoryプライベート
企業向けAI
Factory Managed vs Private: choosing the boundary
Compare Factory Managed vs Private across control-plane ownership, model access, telemetry, and operations. Choose a deployment around your actual requirements.
記事を読むFactoryプライベート
企業向けAI
Factory Private architecture inside your boundary
Factory Private architecture puts the control plane in your infrastructure. Plan the model, network, telemetry, and operating boundaries before a pilot.
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