A force multiplier for delivery leadership.
I'm a delivery leader who uses AI, not an AI engineer. I understand delivery problems well enough to see where AI removes friction from requirements, documentation, estimation and reporting.
Where AI earns its keep.
- Problem
Requests arrive without enough detail
AI interventionRequirements agent built in Microsoft Copilot Studio
WorkflowRequirements gathered in detail at intake
ValueThe team understands each request before work starts
- Problem
Documentation takes delivery time
AI interventionMicrosoft Copilot and Claude for BRDs, documents and proposals
WorkflowAI-assisted first drafts
ValueAim: more time for stakeholders and decisions
- Problem
Standards are hard to write and keep consistent
AI interventionAI-assisted SOP and estimation framework
WorkflowDocumented, repeatable standards
ValueAdopted beyond my own role
- Problem
Meeting actions get lost
AI interventionAI-assisted meeting notes and action tracking
WorkflowActions captured with owners
ValueAim: reliable follow-through
- Problem
Reports eat into delivery time
AI interventionAI-assisted project reports
WorkflowDrafted with AI, alongside Jira and Power BI dashboards
ValueAim: clearer, faster reporting
I don't just use AI. I build delivery workflows around it.
I built and deployed a niche directory web platform with AI-based matching, an SEO content architecture and an enquiry workflow, on Cloudflare Pages and GitHub.
- PrincipleUse AI where it improves speed, clarity and consistency, not simply because it's available.
- Daily toolsMicrosoft Copilot · Claude · ChatGPT
- AgentsMicrosoft Copilot Studio
- ReportingPower BI · Jira dashboards
- LearningGenerative AI Overview for Project Managers · PMI
From vision to execution. From execution to business value.
Complex delivery needs structure. Let's talk.