Prompt Engineering for Software Architects: The Context Game

As a software architect, you're not just building features—you're designing systems. Communicating complex architectural decisions to AI requires advanced prompt engineering skills.

This guide teaches you how to prompt AI for architectural work.

The Architect's Prompting Framework

1. System Context

Always start with the big picture:
> “I'm building a microservices-based e-commerce platform. It needs to handle 10,000 concurrent users, process payments, manage inventory, and send notifications.”

2. Technical Constraints

Define your technology stack and limitations:
> “Tech stack: Node.js, PostgreSQL, Redis, RabbitMQ, Docker, Kubernetes. Must be cloud-agnostic. Budget: $500/month for infrastructure.”

3. Specific Request

What do you need right now?
> “Design the database schema for the order management service.”

4. Success Criteria

How will you know if it's good?
> “The schema should support: order history, order status tracking, refunds, and multi-item orders. Must be normalized to 3NF.”

Advanced Prompting Techniques

Technique 1: The “Explain Trade-offs” Prompt

Instead of asking for a solution, ask for options:

> “I need to choose between monolithic architecture and microservices for this project. Explain the trade-offs considering:
> – Team size: 5 developers
> – Expected traffic: 1000 users/day initially, growing to 100,000/day in 2 years
> – Budget: Limited
> – Time to market: 3 months
>
> Recommend an approach and explain why.”

This forces the AI to think critically rather than defaulting to trendy solutions.

Technique 2: The “Challenge My Assumptions” Prompt

> “I'm planning to use GraphQL for this API. Challenge this decision. What are the downsides? When would REST be better?”

This helps you avoid confirmation bias.

Technique 3: The “Incremental Architecture” Prompt

> “Design a system that starts simple but can scale to handle 1 million users. Show me:
> 1. The MVP architecture (month 1)
> 2. The intermediate architecture (month 6)
> 3. The scaled architecture (year 2)
>
> Explain the migration path between each stage.”

Technique 4: The “Failure Mode Analysis” Prompt

> “For this architecture, what are the top 5 failure modes? For each:
> – How likely is it?
> – What's the impact?
> – How do we prevent it?
> – How do we recover if it happens?”

Real-World Examples

Example 1: Designing a Caching Strategy

Prompt:
> “I have a news website with these characteristics:
> – 100,000 articles
> – Articles rarely change after publication
> – Homepage shows latest 20 articles
> – High read traffic (10,000 requests/min)
> – Low write traffic (10 new articles/day)
>
> Design a caching strategy using Redis. Include:
> – What to cache
> – Cache invalidation strategy
> – TTL values
> – Fallback plan if Redis goes down”

AI Response:
The AI will provide a detailed caching strategy with specific Redis commands and configuration.

Example 2: Designing an Event-Driven Architecture

Prompt:
> “Design an event-driven architecture for an order processing system. Events include:
> – OrderPlaced
> – PaymentProcessed
> – InventoryReserved
> – OrderShipped
> – OrderDelivered
>
> Use RabbitMQ. Show:
> – Exchange topology
> – Queue bindings
> – Dead letter queues
> – Retry logic
> – How to handle out-of-order events”

Example 3: Database Sharding Strategy

Prompt:
> “I have a user table with 100 million rows. Design a sharding strategy. Consider:
> – Shard key selection
> – How to handle joins across shards
> – How to rebalance shards as data grows
> – How to handle user lookups by email (not the shard key)”

The “Diagram First” Approach

For complex architectures, ask for diagrams:

> “Create a Mermaid diagram showing the architecture of a real-time chat application. Include:
> – Frontend (React)
> – WebSocket server
> – Message queue
> – Database
> – Notification service
>
> Show data flow for: sending a message, receiving a message, user goes offline.”

The AI will generate a Mermaid diagram you can render.

Avoiding Common Pitfalls

Pitfall 1: Over-Reliance on Trendy Tech

AI might suggest the latest trendy technology even if it's overkill.

Bad Prompt:
> “Design a system for my blog.”

AI Might Suggest:
Kubernetes, microservices, event sourcing, CQRS…

Better Prompt:
> “Design a system for my blog. It gets 1000 visitors/day. I'm a solo developer. Prioritize simplicity and low cost over scalability.”

Pitfall 2: Ignoring Non-Functional Requirements

Bad Prompt:
> “Design an API for user management.”

Better Prompt:
> “Design an API for user management. Non-functional requirements:
> – Response time: < 200ms for 95% of requests > – Availability: 99.9%
> – Security: GDPR compliant
> – Scalability: Support 1 million users”

Pitfall 3: Not Specifying Constraints

Bad Prompt:
> “How should I store user sessions?”

Better Prompt:
> “How should I store user sessions? Constraints:
> – Must work in a stateless, horizontally-scaled environment
> – Sessions expire after 24 hours
> – Must support 10,000 concurrent sessions
> – Budget: Prefer open-source solutions”

Iterative Refinement

Architecture is iterative. Use follow-up prompts:

Initial Prompt:
> “Design a database schema for a social media app.”

Follow-up 1:
> “How would this schema handle 1 billion users?”

Follow-up 2:
> “What indexes should I add for optimal query performance?”

Follow-up 3:
> “How do I migrate from this schema to a sharded version without downtime?”

Conclusion

Prompting AI for architectural work is different from prompting for code. You need to provide more context, ask for trade-offs, and challenge assumptions.

At BYS Marketing, our architects use AI as a sounding board for design decisions. It helps us explore options faster and catch potential issues early.

—

Need architectural guidance?
Contact BYS Marketing. We design scalable, maintainable systems.