AI Operations
AI Workflow Mapping & Operating Design
Most teams don't have an AI problem — they have an operating-model problem. AI is one layer of Mantle OS™. I help founder-led teams move from scattered tools and founder-dependent routing to a coherent AI operating design: mapped workflows, clear insertion points, and human–agent handoffs that keep you in control.
How I design AI into operations
A five-step loop that connects AI pilots to the way your company actually works.
Map the workflow
Where does work actually happen today? I shadow the real workflow — inbox, docs, meetings, tools — and record each step, owner, input, and output. Most teams map the process they think they run; I map the one they actually run.
Identify friction
Where are people repeating, waiting, searching, copying, summarizing, routing, or manually coordinating? These friction points are the leverage points. AI can't fix a workflow with no owner — I fix the ownership first.
Identify AI insertion points
Where can AI prepare, synthesize, automate, recommend, or execute? Every step gets scored on repeatability, volume, data availability, and consequence of error. High-repeatability, low-consequence steps go first.
Define human-agent handoffs
Where must humans review, decide, approve, or escalate? Every handoff gets a trigger, an owner, and a quality gate. The line between agent and human is written down, not assumed.
Pilot and measure
Hours saved • cycle time • quality • adoption • capacity released. I sequence a 90-day pilot so adoption sticks, then expand use cases quarter by quarter.
What you get
- Current-state workflow map with owners, inputs, outputs, and cycle time — including the undocumented, repeatable work currently carried in people's heads
- Clear ranking of which workflows to automate, assist, or keep human so the first 30-day AI workflow is obvious
- Target-state operating design with named tools, prompt standards, context sources, and human checkpoints
- Human–agent RACI that removes the founder as the default router for approvals, context, and coordination
- 90-day pilot plan with measurable success criteria and adoption milestones
When this fits
Most teams don't have an AI problem — they have an operating-model problem. These are the signals that you're ready to move from scattered tools to a coherent AI operating design.
Tool sprawl
Signal: The team has more AI subscriptions than clear use cases, and AI use feels scattered rather than designed.
Founder still the router
Signal: Agents generate drafts, but everything still funnels back to the founder for approval, context, or coordination.
Repeatable work eating growth time
Signal: High-leverage people are stuck copying, summarizing, routing, reconciling, or collecting information before they can act.
Inconsistent output
Signal: AI results vary wildly because prompts, context, and workflows are undocumented and unmanaged.
Map your workflows before you automate them.
Book a free consultation. I'll find where AI can reduce drag, where humans must stay in control, and what the first 90 days look like.
Book a Free Consultation