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Coding

Practical coding notes for turning AI ideas into maintainable systems: APIs, workflows, tests, observability, and the engineering habits that keep software useful after launch.

Practice Tracks

NeetCode150

A focused roadmap for practicing core data structures and algorithms patterns.

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AI Application Patterns

  • Structured outputs and schema validation
  • Tool calling and workflow orchestration
  • Streaming responses and responsive UX
  • Error handling around model boundaries

Backend Engineering

  • API design and service boundaries
  • Queues, retries, and idempotency
  • Caching and latency reduction
  • Observability, metrics, and tracing

Code Quality

  • Testing model-powered features
  • Type-safe interfaces and contracts
  • Readable abstractions over clever ones
  • Deployment checks and rollback habits