Production-grade deep-dives on AI agents, MLOps on AWS, document intelligence - and what cognitive science teaches us about building better AI.
The hippocampal memory indexing theory, read as compression plus generative reconstruction, and what it demands of RAG, agentic memory and HippoRAG.
Build a working document AI pipeline on AWS in an afternoon: S3 upload, Textract OCR, Bedrock extraction, Pydantic validation, DynamoDB. Runnable code included.
Keep production RAG reliable after launch: hybrid retrieval, CI eval gates on recall and faithfulness, grounding guardrails, and true cost per query in USD.
AWS prices for serverless ML inference: Lambda vs SageMaker Serverless vs real-time endpoints, break-even math, and the CloudWatch bill nobody warns you about.
Cut AWS inference bills by 85% with an event-driven serverless MLOps pipeline using Lambda, Step Functions, and DynamoDB. Inspect the architecture and specs.
Deploying agentic AI in production? See how typed schemas and circuit breakers stop silent loops and tail latency spikes under load.