This unit examines how autonomous agents mature into enterprise-grade platforms and how they are architected, orchestrated, and operationalized for marketing and customer service. Students will study the Sense‑Reason‑Act model, multi‑agent orchestration, unified data foundations, market‑intelligence approaches, and human transformation and tiering considerations for pilot deployments.
Learning Objectives
- Analyze the autonomous agent ecosystem and enterprise platform evolution, citing examples from the Reltio proof-of-concept and the transition from Einstein GPT to Agentforce
- Apply the Sense‑Reason‑Act architecture to design agent workflows for a customer service use case, mapping inputs, decision processes, and actuator outputs
- Demonstrate multi‑agent orchestration by producing a simulated workflow that integrates at least two agents with enterprise data sources and platform touchpoints
- Evaluate unified data foundation requirements and human transformation factors to recommend a tiered deployment strategy for a customer service pilot
Curriculum
- 1 Section
- 12 Lessons
- 30 hours
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- Unit 2 — Enterprise Autonomous Agent Foundations12
- 1.1The Autonomous Agent Ecosystem Landscape20 mins
- 1.2Why Enterprise Platforms Represent Agent Maturation20 mins
- 1.3The Sense-Reason-Act Architecture: How Autonomous Agents Work20 mins
- 1.4Multi-Agent Orchestration20 mins
- 1.5The Reltio Results: Proof of Concept at Scale20 mins
- 1.6Notes20 mins
- 1.7The Two Paths to Market Intelligence20 mins
- 1.8The Evolution from Einstein GPT to Agentforce20 mins
- 1.9Building the Unified Data Foundation20 mins
- 1.10Human Transformation Requirements20 mins
- 1.11Notes20 mins
- 1.12Tier Selection: Starting with Customer Service20 mins
Instructor
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