Nine Chain Patterns for LLM Applications
Most LLM applications are built from a handful of reusable patterns. Picking the simplest one that fits keeps cost, latency, and risk down.
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Five AI Agent Design Patterns
AI agents range from a single model call to multi-step planners that act on real systems. The right pattern depends on the task and on what happens if the agent is wrong.
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The Four Layers of a Production AI System
A demo needs a model and a prompt. A production AI system in an agency needs four layers working together, each with its own decisions and controls.
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Traditional AI, Agentic AI, and Agentic RAG
Not every problem needs an agent. Understanding the three approaches helps agencies match ambition to risk and to the data they can trust.
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Six Roles Every Agency AI Program Needs
As AI moves from pilots into mission processes, success depends on clear ownership of strategy, value, adoption, risk, and responsible use.
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A Lifecycle Governance Model for AI and LLMs
Governance works best as a lifecycle, not a one-time approval: lighter paths for low-risk productivity tools, stronger evidence and oversight for high-impact uses.
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