Write-ups

Projects

Long-form notes on things I built on AWS, and the decisions that turned out to matter.

The Async Pipeline

  1. The Architecture of Not Waiting

    How Lumcast eliminates Lambda cold starts from the user-facing path by pushing every expensive operation into an async pipeline, and why that one decision shapes everything else.

    AWS / Serverless / Architecture / API Gateway / DynamoDB

  2. The Trigger Chain: From DynamoDB Row to Running Pipeline

    How a single DynamoDB write cascades through Streams, EventBridge Pipe, SQS, and a consumer Lambda to start a Step Functions execution, and the subtle data normalization problem hiding inside.

    AWS / DynamoDB Streams / EventBridge / SQS / Serverless

  3. Orchestrating AI: Step Functions as a Generation Pipeline

    Why Step Functions STANDARD workflows are the right orchestrator for a multi-stage AI pipeline, how Map states handle parallel synthesis, and how to treat error handling as a first-class state.

    AWS / Step Functions / Serverless / AI / Orchestration

  4. From Script to Audio: Chunking, SSML, and Parallel Synthesis

    How Lumcast turns a raw LLM script into a multi-chapter MP3: the 2900-character chunk problem, SSML voice matrices, parallel Polly synthesis, and lossless ffmpeg concatenation.

    AWS / Polly / Bedrock / SSML / Audio Processing

  5. Rate Limiting Without a Database Lock

    How Lumcast enforces weekly quota limits using DynamoDB conditional expressions instead of locks: a two-tier atomic update pattern that handles week rollovers without a scheduler.

    AWS / DynamoDB / Rate Limiting / Serverless / Concurrency

Outside the terminal

Alongside the cloud work, I'm grinding through a PPL. The full training logbook is here, flight by flight.

Flight log