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Decision Models in Agentic Architectures: from Production to Agent Skills
Alex Porcelli explains how combining deterministic DMN decision models with agentic AI resolves enterprise AI challenges around accountability, rule governance, and non-deterministic logic.
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From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs
Cassie Shum shares lessons learned on using knowledge graphs as the foundation for agentic software systems, covering 4 key architectural patterns to optimize context, provenance, and team efficiency.
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Architecting the Data Layer for AI Agents: from Transactional Systems to MCP and Semantic Models
Fabiane Nardon explains how to architect enterprise data platforms for AI agents, balancing precision, security, and token costs using MCP, data mesh, and semantic web technologies.
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From Models to Agents: Building Context-Aware Consumer AI at Scale at DoorDash
Sudeep Das explains how DoorDash transforms e-commerce recommendations using LLM-driven semantic consumer memory, hierarchical semantic IDs, grounded agentic search, and multi-tiered LLM ranking.
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Architecting AI Systems for the Messy Reality of Enterprises: Why Agentic Compute is the Missing Layer
Arun Joseph explains how to successfully build and deploy enterprise-grade agentic platforms by leveraging existing teams, JVM stacks, and a "compute as the agent" architectural paradigm.
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From Copy-Paste to Composition: Building Agents Like Real Software
Jake Mannix explains how to mature AI agents using "virtual tools" for encapsulation, interface abstraction, and deterministic taint tracking to prevent lethal data exfiltration risks.
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