Pogany treats agent patterns as reusable workflow shapes rather than products. A basic tool-use loop lets a model act and inspect results, while ReAct adds explicit reasoning and planning decomposes an open goal into steps that can be revised when intermediate results change the situation.
Reliability patterns add checks around generation. Reflection and evaluator loops critique outputs against explicit criteria, retrieval and memory patterns ground work in external or accumulated context, and sampling or search patterns compare multiple candidates instead of accepting the first response.
Multi-agent patterns help when work can genuinely be divided among specialists or explored from competing perspectives. Pogany demonstrates routing, debate and research configurations, but warns that extra agents add complexity and should not replace a simpler loop when one agent with tools can complete the task.
Safety requires deterministic control around irreversible actions. Dry-run simulation, capability routing and human approval can prevent destructive commands or prompt-injected browser actions from executing. The overall design principle is progressive structure: begin with tool calling, add reflection when quality is weak, add planning for uncertain multi-step work, and add teams only when parallel specialization is truly useful.
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