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Agentic Design Patterns

The article explores agentic design patterns—structured approaches for building AI agents that can autonomously plan, reason, and execute tasks. It covers key patterns like tool use, reflection, planning, and multi-agent collaboration, highlighting how these patterns enable more capable and reliable AI systems.

Background

- **"Agentic"** AI systems act autonomously — making decisions, using tools, and executing multi-step plans — rather than just answering one-off questions. This is a shift from passive chatbots to proactive AI agents. - The post is by Dan Wald, an engineer at Braintrust (an AI evaluation platform), distilling patterns for building such agents. It builds on guidance from Andrew Ng and Anthropic (maker of Claude). - Key patterns covered: **Prompt Chaining** (breaking tasks into sequential LLM steps), **Router** (a model that picks the right sub-agent or tool), **Orchestrator** (a central agent that delegates to workers), **Parallelization** (running agentic tasks concurrently), and **Evaluator-Optimizer** (one agent generates, another critiques in a loop). - Building reliable agents is hard — they can get stuck in loops or waste API costs. These patterns help developers design robust, efficient systems.

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Agentic Design Patterns

Background

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