Key takeaways
- Conversation history
- User management
- Business logs
- Clear action status
Why this stack works well
It lets you ship quickly without sacrificing code readability. You keep a modern front-end experience, a simple database to expose, and backend building blocks that are robust enough for a serious MVP.
This combination also avoids over-engineering the architecture too early. You can validate a use case, collect feedback, and refine the product before introducing more complexity.
A coherent base for a small team
When the front end, authentication, storage, functions, and database stay close to each other, the team moves faster. Debug loops are shorter and the time spent stitching together disparate services drops significantly.
What the MVP should contain
A good agentic MVP is not limited to a chat box. It needs authentication, persistence, traces, simple permissions, and an acceptable error design.
This foundation makes it possible to move from a simple demo to a product that real internal or external users can test, with a minimum level of operational responsibility.
- Conversation history
- User management
- Business logs
- Clear action status
The minimum product pieces not to forget
Teams often underestimate the importance of empty states, generation errors, context persistence, and the ability to resume a conversation without ambiguity.
- Readable loading states
- Error handling
- Persistent context
- Basic permissions
Pitfalls to anticipate before connecting an LLM
The risk is not only technical. It also comes from poorly designed permissions, badly observed costs, prompts that are impossible to find in the code, and the lack of usable business logs.
The earlier these topics are addressed, the easier the MVP remains to maintain and explain to a client or a product team.
Maturity signals to aim for
Even at MVP stage, it is useful to know which prompt is running, which action was triggered, which user launched the request, and what approximate cost each flow represents.
- Prompt traceability
- Observed cost
- Action logs
- Explicit roles
AH
Author
AI HUB Editorial
Research Desk
