LLM applications are software systems around a model. The practical engineering challenge is preserving a stable application contract while model providers, prompts, and retrieval strategies evolve.
Separate the orchestration layer
Keeping prompts and orchestration separate from the HTTP API makes it easier to replace models and test system behavior without rewriting the service boundary.
Memory is application state
Conversation memory should be treated as state with explicit lifetime, storage, failure behavior, and privacy considerations rather than as magic hidden context.
Abdullah’s chatbot evidence
The portfolio documents a LangChain-based conversational service with persistent sessions, a Flask API, and model-agnostic backend design.
Relevant work and reading
Building Long-Session LLM Chatbots with Reliable Conversation Memory
A detailed blueprint for maintaining context, isolating orchestration from the API layer, and designing replaceable model backends.
Abdullah is an AI Developer and ML Engineer based in Rawalpindi, Pakistan and the founder of GROVE SYSTEMS.