Agentic AI with Commercial Databases
summary
Claims agents will produce orders of magnitude more apps (speaker says "a thousand times"), and the focus is on controlling cost, security and latency. Architecture demo connects CloudFront/S3 frontend, API Gateway + Lambdas, Aurora Postgres, RDS for SQL Server and DynamoDB with agent MCP servers and agent memory stored in DynamoDB. Demo executes an agent workflow that upgrades a credit card and estimates a 686 annual benefit, showing the system actually runs end to end and responds interactively.
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chapters (13)
- 0:00Introduction and agenda
- 1:08Impact of agents on systems
- 4:40Efficiency in agentic workflows
- 7:16Choosing the right database
- 11:48DynamoDB use cases
- 14:52Data architecture for agents
- 18:01Integrating vector data
- 21:50Enterprise database migration
- 25:23Cost optimization and licensing
- 30:12Database savings plans
- 33:28Oracle Database at AWS
- 36:12Zero-ETL and migration paths
- 38:32Financial application demo
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