𝗦𝘁𝗮𝘁𝗲𝗳𝘂𝗹 𝘃𝘀 𝗦𝘁𝗮𝘁𝗲𝗹𝗲𝘀𝘀 𝗔𝗜 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲
Your architecture choice defines your AI platform. You must decide if your system remembers data or starts fresh every time.
Stateless design treats every request as new. It stores no session memory.
- Scaling is easy.
- Recovery is fast.
- Infrastructure is simple.
Use stateless for batch tasks. It works for document classification or image analysis.
The trade-off is higher latency. You must send full context with every call.
Stateful systems remember user data and history.
- Better for chatbots.
- Faster response times.
- Supports complex workflows.
Use stateful for conversational AI. It works for personalized tools.
The trade-off is complexity. Scaling requires more work.
You do not have to pick one. Use both.
- Use stateless layers for routing.
- Use stateful layers for sessions.
Ask these questions:
- Does the request need past data? Go stateful.
- Is massive scaling critical? Go stateless.
- Do you need low latency for users? Go stateful.
- Is every request a one-off? Go stateless.
Match the pattern to the problem.
Source: https://dev.to/dorjamie/stateful-vs-stateless-architecture-making-the-right-choice-for-ai-systems-4818 Optional learning community: https://t.me/GyaanSetuAi