Memory-Aware Agent Harnesses for Anti-Money Laundering — Nacho Martinez, Oracle
Nacho Martinez walks through the full agent stack (agent loop, short- and long-term memory, context engineering, the toolbox and skillbox patterns, skill distillation and continual learning) and applies it to an autonomous agent that flags suspicious bank transactions around the clock.
Proof1 independent outlet
Key points
- The model is the part you can't change.
- 4:57 The use case: an AML agent for a mid-sized bank
- 9:16 What is an AI agent?
- 15:56 Agent memory: short-term, episodic, procedural, semantic
Sources (1)
- [1]Memory-Aware Agent Harnesses for Anti-Money Laundering — Nacho Martinez, OracleAI Engineer (YouTube) · Oct 17, 07:00 AM
Nacho Martinez walks through the full agent stack (agent loop, short- and long-term memory, context engineering, the toolbox and skillbox patterns, skill distillation and continual learning) and applies it to an autonomous agent that flags suspicious bank transactions around the clock.
The model is the part you can't change.
Extractive summary: sentences quoted from the sources.
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