One-to-one mentoring for business owners who have been figuring out AI on instinct. You have built things that worked once, then broke, and you cannot reproduce them. We fix the foundation, then you build on it properly. Every system already tested in a real business every week.

The conversations happening in every B2B software marketing leadership team, right now.
Your team is already using ChatGPT, Claude, and Gemini on company data, without any governance, oversight, or consistency. You just don't know the extent of it.
EU AI Act and GDPR obligations are real. The default fix is to hand it to IT. But governance that marketing teams ignore is not governance. It needs to be built for the people who will actually use it.
Ten people in the team, ten different approaches. AI results are inconsistent, quality varies wildly, and there's no way to scale what's working.
Content is getting produced faster, but messaging is drifting from your customer's actual language. Faster isn't better if it's amplifying the wrong message.
Teams with governed AI systems build capability that compounds. Without a system, your productivity gains stay individual and temporary.
You've tried external consultants who built things for you. When they left, so did the knowledge. Your team needs to own this, not depend on it.
Unsure where your team sits? The AI Readiness Assessment takes 4 minutes →
The frame we build toward
Which of your team's activities require a human to be physically present? Everything else is agent-ready. That's what we build toward.
Proof that I build what I teach. Every client engagement uses these same tools and patterns.
Built by Duncan
A digital twin of your prospect, built from scraped data. Practise before the real meeting. A live coaching layer runs during the call, updating deal stage, talking points, and objection handling every turn.
Built by Duncan
The operating system every engagement runs from. 15 packages, deterministic scoring. Governance audits, maturity assessments, programme designs, ROI reports, AI staff registries. Auth-gated: access is part of every engagement.
Built by Duncan
Syncs with your CRM. Dual-AI research returns a confidence-scored dossier per account: company overview, use-case matching, discovery questions, and software signals. Territory-scale intelligence without a research team.
Ask about any of these when we speak.
Methodology
Prompt → Refine → Deliver → Repeat is how we build AI systems with your team, not for your team.
Design prompt systems grounded in your customer's actual language, extracted from sales calls, support tickets, and reviews. No generic AI outputs.
Test, iterate, and tighten every workflow with your team until outputs consistently match your brand and your audience's expectations.
Deploy governed, documented AI systems into your team's real day-to-day. Not theory, not demos. Working tools your team actually uses.
Build repeatable, scalable systems that compound over time. Your team owns the capability. Productivity gains don't walk out the door.
The published methodology
Read Prompt. Refine. Deliver. Repeat.Meet Duncan
I'm Duncan Hendy, an AI mentor and practitioner, and author of Prompt. Refine. Deliver. Repeat. The systems I teach are the systems I run.
I ship AI tools daily, including the systems I bring to every client engagement. This isn't advice I read about. It's what I do in production, every week.
The difference: I co-build with your team, not for your team. When the engagement ends, capability stays in-house. Your team owns it, runs it, and extends it.


The Playbook
The second edition of the published methodology behind every Duncan Hendy AI Mentoring engagement. 29 chapters of practical AI workflows for B2B product marketers, built on Claude. No fluff, no theory. The prompts, patterns, and systems that work.
Prefer a physical copy? Get the book on Amazon for €11.99
Frequently Asked
before they engage.
Shadow AI is when your team members use AI tools individually (ChatGPT, Claude, Gemini) without any governance, shared methodology, or oversight. It's already happening in most B2B marketing teams. The risk: data leakage, inconsistent outputs, GDPR and EU AI Act exposure, and productivity that doesn't compound. The first step is always to surface what's actually happening before building a system around it.
There is no fixed length, because there is no fixed programme. Most people start with a couple of sessions to define the problem properly and agree a sequence, then the pace is theirs. Some work intensively for a few weeks. Others go quiet for a month while they build, then come back when they hit something. Both are fine.
Training tells you what AI can do. Mentoring builds systems your team actually uses. We co-build using real tools on real problems, so the capability stays in-house when the engagement ends. No dependency on continued consultancy. Your team owns everything.
The people I work with tend to be running their own business, expert in what they do, and self-taught with AI. They have got real results already and they have also got a mess they cannot untangle. Size does not matter much; one person or twenty makes little difference to how we would work. What matters is that you want to build the thing yourself rather than have someone build it for you and leave. If you would rather hand it over and receive a finished product, I am the wrong person and I will say so early.