Building Simple LLM Applications
APIs, chat flows, memory, orchestration, and developer patterns
APIs, chat flows, memory, orchestration, and developer patterns
LLM applications are built with a small set of predictable components: API calls, conversational logic, memory, and orchestration. These elements let developers turn raw LLM capabilities into reliable product features.
Simple requests that send text and receive model-generated responses.
Multi-turn conversations managed through structured prompts and system roles.
Techniques to store and retrieve context so the conversation stays coherent.
Coordinating multiple model calls, tools, and logic steps.
Reusable structures that increase reliability and reduce complexity.
Define what the model should do.
System + user messages shape behavior.
Store key information for later turns.
Chain model calls and logic.
Expose as an API or product feature.
Interactive multi-turn support systems.
Search enhanced with vector memory.
LLMs controlling tools or APIs.
No. Simple APIs may not need memory, but chat-based systems usually do.
Only when you combine multiple model calls or tools.
Start with a single API call and expand to chat + memory as needed.
Use simple APIs and patterns to build powerful AI-driven features.
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