Turn a validated AI opportunity into clearly defined agentic logic, workflow behavior, and a testable prototype.

I help businesses take a specific workflow or use case and define how an AI agent should operate. Together, we’ll establish the agent’s purpose, workflow states, decision logic, routing rules, human review points, escalation paths, and expected behavior before full production development.

Agent purpose and scope definition

Workflow state modeling

Entry and exit conditions

Decision logic and routing rules

Required inputs and expected outputs

Human-in-the-loop checkpoints

Confidence handling and fallback behavior

Escalation paths

Prompt and interaction structure

Tool and system interaction requirements

Prototype behavior and scenario testing

Defined agentic operating model

End-to-end workflow and state model

Decision rules and transitions

Input/output requirements

Human-review and escalation rules

Prompt and interaction guidance

Prototype demonstrating the agreed agent behavior

Test scenarios and implementation recommendations

Standard scope: one AI-agent use case focused on one primary workflow, with up to 3 user or stakeholder types and up to 10 representative scenarios or decision paths. Multi-agent systems, production integrations, enterprise deployment, or custom software development can be scoped separately.

Scope boundary: this service focuses on agentic logic, workflow modeling, decision rules, prompt structure, and prototype behavior. Production software engineering, enterprise deployment, custom integrations, authentication, hosting, and ongoing maintenance are not included in the standard engagement.

This service is ideal for teams that already have a promising AI use case and need help defining how the agent should actually behave before investing in full production development.