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。
Factoryプライベート内のタグ
Factoryプライベート
企業向けAI
Self-hosted AI agents and control-plane ownership
Self-hosted AI agents require clear ownership of the control plane, session data, models, and updates. Compare the responsibilities before choosing a deployment.
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データガバナンス
AI agent telemetry inside private networks
AI agent telemetry should answer an operational question without collecting unnecessary code. Choose metrics, identity detail, and content export deliberately.
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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.
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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.
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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.
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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.
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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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企業向けAI
EU AI deployment beyond the regional endpoint
EU AI deployment requires separate decisions about session content, inference, identity, and control-plane ownership. Compare regional Factory hosting with Factory Private.
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コンプライアンス
SOC 2 for AI coding tools: evidence to request
SOC 2 for AI coding tools requires a review of report scope, operating period, data flows, and customer controls. Evaluate evidence instead of relying on a badge.
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データガバナンス
AI code data residency beyond the repository
AI code data residency includes model context, session records, integrations, and telemetry. Follow the complete data path before approving a coding agent.
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エアギャップ環境への導入
Air-gapped AI development that works offline
Air-gapped AI development needs internal inference, offline artifacts, and enforced network isolation. Validate the full workflow before approving a deployment.
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データガバナンス
Factory vs Devin: where your engineering data goes
Compare Factory vs Devin on where code runs, which services receive model requests, and what sessions and telemetry retain. Understand the limits of private deployment.
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