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Moshe Scheiner - The Agent Isn’t the Hard Part. The Memory Is.
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Session show notes
Moshe demonstrates why better AI recommendations depend on preserving decisions, the reasons behind them, and observed results over time. He applies that memory model to an Amazon PPC workflow with rules, history, tests, and human approval gates.
Key learnings
- Understand why the same PPC report can produce poor recommendations without account strategy and history.
- Distinguish raw context from memory of what the business tried, what worked, and what failed.
- Onboard and correct an agent the way you would train an employee.
- Keep PPC rules, history, tests, and human oversight.
- Keep the decision and the reason; discard expired information.
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Moshe Scheiner
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