APIs, chat flows, memory, orchestration, and developer patterns explained clearly and visually.
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Simple LLM applications rely on predictable patterns. These patterns help developers build robust, modular, testable systems while keeping complexity low.
Direct calls to models, providing prompts and receiving responses.
Structured message sequences for guided or open-ended interactions.
Techniques for storing and retrieving history, context, or state.
Combining tools, steps, or multiple model calls into workflows.
Reusable approaches that improve readability and maintainability.
Clarify the user task.
Map conversation or steps.
Choose short-term or vector memory.
Define how tools or calls connect.
Refine prompts and flows.
Conversational interfaces that use memory and tool calls.
Workflow-based generation using templates and prompts.
Structured outputs driven by models and validation steps.
Fast to build, low complexity, limited structure.
Support conversation flows and memory out of the box.
Complex but powerful for multi-step workflows.
No. Simple single-turn apps often work without memory.
Begin with direct API calls and gradually add structure.
When your workflow spans multiple steps or tools.
Experiment with flows, memory, and orchestration for more powerful applications.
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