SERVICE
AI workflow architecture & control
Move from an impressive demo to a workflow your team can assess and operate.
I examine one real AI-supported task: its inputs, tools, outputs, review responsibilities and handover. I then recommend suitable controls and, if separately agreed, help put them in place. A better prompt can help; it cannot replace source discipline, tests or accountable decisions.
When this is useful
- Outputs are plausible, but sources and assumptions are unclear.
- The workflow depends on one person who knows all the prompts.
- An AI-built prototype needs a technical review before further use.
What the work can leave you with
- A workflow map with source and data boundaries.
- Tests, review points and escalation rules appropriate to the task.
- Recommended improvements and, where agreed, implementation with operating notes for handover.
How the engagement starts
First we clarify the objective, available evidence, access and responsibilities. Before work starts, we agree the scope, participation and terms. Limited ongoing support can be arranged separately.
Examples from my development work
PolicyMonitor connects source monitoring with topic-based selection. ShellAgents processes selected material into structured analysis; the Link22 briefing is a published example. Kim handles concrete document tasks by email.
Let’s discuss your question.
Tell me briefly what you would like to clarify, which ideas you want to explore or where you need a second opinion. We can then agree a useful starting point and a defined scope.