Free Resource
AI Development Guide
A compact field guide for shipping more reliable AI features without wasting time on shallow prototypes.
Start with the failure modes, not the demo.
Choose the smallest architecture that can survive real traffic.
Instrument the path before scaling the feature.
Discovery
- Define one job to be done and one success metric.
- List the sources of truth and trust boundaries early.
- Write down the edge cases before choosing the stack.
Implementation
- Separate prompt logic, model calls, and business rules.
- Keep retries and fallbacks explicit at the API layer.
- Add tracing around latency, token usage, and failures.
Launch checks
- Load test the expensive paths before launch.
- Protect sensitive operations with auth and rate limits.
- Add regression coverage for the most expensive failures.
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