Agentic, Assistive & Predictive AI Patterns

Building AI isn’t about plugging into an API — it’s about patterns, orchestration, and guardrails. This workshop equips architects, developers, and leaders to design enterprise-ready AI systems using the Big 3 patterns (Predictive, Assistive, Agentic), RAG grounding, and multi-agent orchestration with MCP.

You’ll work through real-world e-commerce scenarios and leave with a Smart Checkout Helper prototype, reusable decision frameworks, and a governance playbook that CIOs can trust.

Key Takeaways

Pattern Literacy → Know when to apply Predictive, Assistive, or Agentic AI.

Integration Skills → Wire up Salesforce Agentforce, OpenAI, Zapier, and Data Cloud into resilient flows.

RAG Mastery → Ground AI in facts to reduce hallucinations.

Multi-Agent Orchestration → Use Orchestrator, Pub/Sub, Blackboard, Capability Router, and MCP.

Governance Confidence → Embed privacy, bias checks, auditability, and resilience into every design.

Business Alignment → Use Jobs-to-Be-Done to link AI to ROI.

Agenda Module 1. Foundations of AI Patterns

Why AI patterns > tools.

Event-driven + API-driven + AI-driven systems.

Build: Hello World → OpenAI + Zapier trigger.

Module 2. The Big 3 Patterns

Predictive → foresight.

Assistive → guidance.

Agentic → autonomy.

Decision matrix for choosing patterns.

Build: Same use case in 3 ways (cart abandonment).

Module 3. Predictive AI → Foresight in Systems

Forecast churn, fraud, demand.

Salesforce Data Cloud predictive models.

APIs/events for embedding predictions.

Build: Predictive scoring in checkout flow.

Module 4. Assistive AI → Guiding Humans

UX patterns: nudges, cards, contextual insights.

Salesforce Next Best Action examples.

Build: Personalized promotion recommender for service agent.

Module 5. Jobs-to-Be-Done Framework

E-commerce jobs: Acquire → Convert → Fulfill → Support.

Map AI patterns to jobs.

Build: Convert job → predictive + assistive + agentic combo flow.

Module 6. Agentic AI → Autonomy in Action

Autonomy levels (assistive → semi → fully agentic).

Salesforce Agentforce: SDR Agent, Sales Coach Agent.

Fallbacks & escalation strategies.

Build: Refund bot with human-in-loop approval.

Module 7. RAG → Grounding AI in Facts

Why hallucinations occur.

RAG architecture: vector DB + retriever + LLM.

Build: Checkout FAQ bot (returns, policies, catalog).

Module 8. Multi-Agent Orchestration & MCP

Core orchestration patterns:

Orchestrator/Supervisor.

Pub/Sub.

Blackboard/Shared Memory.

Capability Router (Intent → Skill).

MCP (Model Context Protocol) → plug-and-play interoperability.

Build: Checkout Agent → Inventory Agent → Pricing Agent using Pub/Sub + Supervisor.

Module 9. Governance & Guardrails

Privacy by design, bias checks, audit trails.

Architecture resilience: retries, DLQs, idempotency.

CIO trust checklist.

Build: Add governance + logging to prototype.

Module 10. From Prototype to Production

End-to-end demo of Smart Checkout Helper.

Templates: pattern matrix, JTBD map, governance checklist.

ROI storytelling for business leaders.

Next steps for embedding AI into your enterprise.

What You’ll Leave With:

A working prototype of an AI-powered checkout flow.

A decision framework (Predictive / Assistive / Agentic).

A governance checklist for privacy, bias, and auditability.

A multi-agent orchestration playbook (including MCP).

A business mapping toolkit (JTBD → AI → ROI).