Architecture
🏗️ Step by Step
Building AI engineering architecture doesn't happen overnight. The most successful approach is to start simple and gradually add complexity as your needs grow.
👣 The Gradual Architecture Approach
1. Start Simple
Begin with the most basic setup: user query → AI model → response. No frills, no complexity—just a working system.
Add mechanisms to provide your model with relevant information for each query. This includes:
Retrieval systems for text, images, or tabular data
Tool integration for web search, news, or company APIs
External database connections
Protect your system and users with safety measures:
Input guardrails: Prevent private information leaks and prompt attacks
Output guardrails: Catch failures, irrelevant content, and harmful outputs
Policy enforcement: Define how to handle guardrail violations
Manage complexity and costs with smarter routing:
Router: Direct queries to the optimal model based on intent or type
Gateway: Provide unified, secure access to multiple models
Centralised security: Improve maintainability and logging
Reduce latency and costs using proven caching strategies:
Exact caching: Reuse identical query responses
Semantic caching: Reuse similar query responses based on meaning
System-level optimisation: Balance speed, cost, and accuracy
Add sophisticated workflows that go beyond simple processing:
Planning capabilities: Allow models to create multi-step strategies
Tool integration: Enable interaction with external systems
Write actions: Allow direct environment interaction (emails, transactions)
Complex flows: Support loops, parallel execution, and conditional logic
⚖️ Key Considerations
Trade-offs: Each step introduces trade-offs between reliability, latency, cost, and complexity. Consider your specific needs when deciding which components to implement.
Security: Steps 3 and 6 are particularly important for security. Guardrails and careful agent implementation are essential for production systems.
Gradual Implementation: Don't try to implement everything at once. This step-by-step approach allows you to validate each component before adding the next layer of complexity.
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