Insights
Perspectives on modernization, intelligent systems, health technology, and the delivery disciplines that turn strategy into operating results.
Featured perspective
A practical review of where Checkov adds value in infrastructure delivery, how source and plan scans support release decisions, and why policy tuning, exceptions, and runtime evidence still matter.
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Editorial Insight series
Mission fit, model selection, readiness, data, privacy, security, and production operations for federal leaders.
Explore the AI seriesField Review series
Practical reviews of the cloud products, platform patterns, and delivery controls shaping secure software delivery.
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Selected delivery patterns that connect a complex operating challenge to measurable, supportable outcomes.
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Practical safeguards for using AI while preserving privacy, protecting sensitive information, and maintaining operational accountability.
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Every published TDG perspective appears below. Choose a topic or search for a specific subject.
A practical review of where Checkov adds value in infrastructure delivery, how source and plan scans support release decisions, and why policy tuning, exceptions, and runtime evidence still…
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A practical operating model for giving AI agents distinct identities, task-scoped authority, deterministic authorization, approval gates, and auditable evidence.
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A practical control model for keeping retrieved information within its authorized audience, preserving source integrity, and testing the complete retrieval path before release.
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A practical review of how AWS vulnerability and security findings become an owned remediation queue, with exposure context, clear decisions, and evidence that the fix worked.
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A practical pre-prompt decision model for classifying, minimizing, authorizing, and protecting information before it reaches an AI service.
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A practical review of how Artifact Analysis, provenance, attestations, and Binary Authorization can turn software-supply-chain evidence into governed deployment decisions.
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A practical operating model for writing bounded AI requests, separating trusted instructions from untrusted content, controlling outputs, and preserving human decision authority.
Read articleA practical operating model for limiting unnecessary data use, preserving accountability, and making privacy evidence part of the AI lifecycle.
Read articleA practical review of how posture, workload protection, DevOps context, ownership, and evidence can support a more coherent cloud-security operating model.
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A practical review of how GitHub code scanning, dependency review, secret protection, and remediation assistance support governed software delivery.
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A practical operating foundation for making federal AI data authoritative, governed, protected, testable, and fit for a bounded mission use.
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A practical outcome baseline for judging whether DevSecOps improves delivery flow, software trust, control evidence, and operational resilience in a cloud enterprise.
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A practical six-dimension assessment for deciding whether a federal AI idea is ready to become a bounded, evidence-driven use case.
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A mission-first framework for deciding whether a federal problem needs analytics, deterministic automation, artificial intelligence, or a controlled combination of the three.
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TDG introduces a practical DevSecOps operating model that connects mission outcomes, delivery teams, platform engineering, security controls, and decision-ready evidence.
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A practical foundation can help federal leaders evaluate AI tools and use cases in context. AI is a family of capabilities, and mission value depends on the complete…
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For federal agencies, disaster recovery must restore a trusted mission service rather than merely duplicate infrastructure. A sustainable cloud strategy aligns mission impact, recovery objectives, data protection, cyber…
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A practical executive framework for choosing an AI model against the mission task, operating environment, evidence requirements, and consequence of error rather than market visibility or model size.
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TDG Insights
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What we examine
Modernization choices, platform operations, security, resilience, and cost clarity.
Responsible adoption, data foundations, governance, automation, and practical value.
Interoperability, regulated data exchange, modernization, and mission continuity.
Decision systems, governance, risk, dependencies, operating models, and execution.
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