Data Science


Leading Indicators for AI Agents When Goals Happen Once

When the Goal Only Happens Once, Teach Agents With Leading Indicators


Why Agentic Systems don’t operate over a huge State Space

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Goals vs. Signals: What Agents really learn from

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Layering A/B Testing and Agentic Learning for Better Results

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Choosing Target Events for Agentic Learning

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Why Auditing a Single Agent Decision Misses the Point

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Learning, Not Guessing: How Aampe Aligns With Every User

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Understanding Decision-Making in Agentic Systems

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Alignment at Scale Beats Attribution at Aggregate

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How Aampe’s Agents Use Causal Analysis to Measure Impact Amidst External Messaging

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Agentic Architecture in Action: Aampe’s Dual-Path Personalization Strategy

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Building a Multi-Tenant Event Processing Pipeline: A Dive into Pub/Sub Architecture

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Evaluating Adaptive Systems: Beyond Short-Term Metrics

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