Design a prompt management platform
PremiumLLM systemEasy
- Prompt versioning
- Prompt templates
- Evaluation gates
Quick answer
This LLM system interview question asks you to design a prompt management platform. Aim for a design that uses language models to serve users well, then explain retrieval, prompting, serving, evaluation and trade-offs. Interviewers want to see how you control quality, cost and latency, and how you evaluate the results.
The problem
Design a prompt management platform where teams store, version, test and release the prompts their LLM features use. Services fetch the live version through an SDK, so a prompt can change without a deploy. The hard parts are shipping changes safely, rolling back in under a minute, and adding no latency or outage risk to 50 million LLM calls a day.
Today prompts live as strings in 60 code repositories, nobody knows which version is in production, and a bad edit can only be undone by a redeploy.
What must a prompt management platform do?
- Versioned prompts: Every change creates a new immutable version with author, message and diff.
- Templates: Prompts declare typed variables; RAG prompts also declare where retrieved context goes and the citation format they require.
How well must it do it?
- No added latency: Rendering a prompt adds no network call on the request path.
- Resilience: If the platform is down, services keep using their last cached versions.
What scale should you design for?
Use these numbers in your estimates.
The scale numbers unlock with this questionUnlock
Key concepts
- Prompt versioning
- Prompt templates
- Evaluation gates
- Canary releases
- Rollback
- SDK caching
How you’ll practise
- Problem framing
- Data and retrieval
- Prompting and orchestration
- Evaluation and safety
- Serving, cost and latency
- Wrap-up
Lala, personalized to you, gives a hint when you ask and reviews your design when you are ready.
What do interviewers look for?
In any LLM system design round.
- Defines the user task and what a good answer is
- Explains how relevant context reaches the model
- Plans evaluation before and after launch
- Controls cost and latency with caching and routing
- Covers safety, privacy and abuse
- Handles failures and fallbacks gracefully
Questions people ask about this interview question
- Which design type is this question?
- It is an LLM system question. You design a prompt management platform and explain your choices the way you would in an interview.
- Is this question asked at entry level?
- It is marked Easy, so it suits engineers who are new to LLM system interviews. It is also a good warm-up before harder questions.
- What should I cover first?
- Start with the user task, what a good answer looks like and how it will be measured. Agree on scope with the interviewer before you design anything.
- Can I practise it for free?
- It is a premium question. Sign up and unlock it once for 10 credits; it then stays unlocked. When you finish, Lala, your personalized AI mentor, can review your design for 30 credits.
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Updated · Written by the SevyDevy team