Course Objective & Scope
Bolting a chatbot onto a legacy workflow rarely delivers breakthrough productivity; true transformation happens when processes built around human copy-pasting and manual coordination are fundamentally redesigned around autonomous and semi-autonomous agents. This intensive 0.5-1 day workshop teaches process owners and architects how to deconstruct existing (As-Is) workflows and architect future-state (To-Be) agentic processes.
Working on a live process from their organization, participants map out exactly which steps remain deterministic code, where AI agents use reasoning and tool calling to gather context and take action, and where humans step in for judgment and approval. Teams leave with a complete Agentic Process Blueprint ready for technical implementation.
Who Should Attend?
- Operational excellence, business process management (BPM), and digital transformation leaders
- Department heads and process owners re-engineering how work gets done across their teams
- Product managers, business analysts, and solution architects scoping enterprise AI agent initiatives
Key Takeaways
- Shift mindset from screen-by-screen human workflows to agent-executed, human-supervised process architectures
- Allocate each process step across four execution modes: deterministic rules, single-turn LLM, tool-using agent, and human judgment
- Specify the exact tools, APIs, context sources, and permission guardrails an agent requires to operate safely
- Design risk-tiered
human-in-the-loopcheckpoints, escalation triggers, and audit trails - Produce an actionable To-Be Agentic Process Blueprint for a real enterprise workflow
Curriculum
The Paradigm Shift: From Legacy Workflows to Agentic Processes
- Why automating broken human steps ('paving the cowpath') misses the transformative potential of AI
- Comparing deterministic RPA/workflows, human-driven Copilots, and goal-driven Agentic Workflows
- Redefining the human role from routine data processor to exception handler and supervisor
Deconstructing the As-Is Process and Task Allocation
- Mapping the end-to-end steps, handoffs, information lookups, and decision gates of a real company process
- The 4-Way Allocation Matrix: Deterministic Code vs. Single LLM Call vs. Agentic Reasoning vs. Human Judgment
- Pinpointing coordination overhead, queue wait times, and manual verification bottlenecks
Designing Agent Roles, Tool Calling, and Autonomy Boundaries
- Choosing between a single workflow agent and orchestrated specialist sub-agents
- Defining the exact read-only context sources and write-action tools each agent can invoke
- Setting hard guardrails: monetary thresholds, read/write permissions, and policy constraints
Human-in-the-Loop (HITL) Checkpoints and Exception Handling
- Calibrating autonomy tiers using a Risk vs. Confidence matrix (auto-execute, draft-for-approval, escalate)
- Designing frictionless approval cards that present evidence, reasoning, and one-click actions to human reviewers
- Capturing human overrides and corrections as structured evaluation data
Building the To-Be Agentic Blueprint and Rollout Plan
- Constructing the multi-lane To-Be blueprint across User, Agent, Enterprise Systems, and Human Supervisor lanes
- Phased rollout strategy: Shadow Mode -> Assisted Copilot -> Bounded Autonomy
- Defining target KPIs (cycle time compression, straight-through processing rate, error rate) and peer review
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