Services
Three ways to work together. Start with the diagnostic; the other two build on it, or stand alone if you already have a process map.
01. Process Diagnostic / AI Opportunity Sprint (3–4 weeks)
Interviews, systems observation and documentation review on one high-value workflow. You get the full as-is process map, a four-bucket redesign, baseline KPIs and an estimate of the impact.
- As-is map with exceptions, loops and workarounds
- Step-by-step redesign: delete, plain code, agentic, human
- Baseline KPIs and estimated impact
02. Agentic Prototype Definition (2–4 weeks)
I define what an agent should and shouldn't do: scope, exception handling, human decision points, success metrics and how it connects to your existing systems of record. You receive an engineer-ready specification for your team or partners to build from.
- Agent scope and exception handling
- Human decision points and handoffs
- Engineer-ready spec with success metrics
03. Embedded Process Support (Ongoing)
Ongoing ownership of process mapping, stakeholder alignment and measurement inside a larger forward-deployed or AI transformation engagement, so engineers keep building on an accurate picture as it changes.
- Process maps kept current
- Stakeholder alignment across teams
- Continuous measurement and refinement
Questions
What is a forward deployed engineer, and where do you fit?
A forward deployed engineer (FDE) embeds inside a client organisation to build and deploy AI agents on real workflows. I'm not an FDE and I don't build production agents. I'm a service designer who does the process discovery, redesign and measurement that forward-deployed work depends on, and I work alongside engineering teams.
Do you build the agents?
No. I define the agent's scope, exception handling, human decision points, success metrics and integration points with your existing systems of record, and hand over an engineer-ready specification. Your engineering team or partners build it.