AI Enablement with Claude
The Client
Hamilton & Waikato Tourism is the Waikato's official Regional Tourism Organisation, funded by four councils to market the region to the world. Caves, surf breaks, a hobbit village, and 400 kilometres of cycle trail. A small marketing team in Hamilton sells all of it to domestic and international visitors.
Like most marketing teams, they were already using AI. Also like most marketing teams, they were using it one conversation at a time. Open a chat, ask for a draft, close the chat, start again tomorrow.
The Goal
That approach had a ceiling, and they had hit it. Natasha Chevtchenko, their Digital Marketing Lead, had taught herself AI by using it. With no training and no developer, she had built a custom AI workflow, including one for LinkedIn posts and an agent wired into Asana to sort her tasks and set her day. Every attempt ran into the same wall:
Every tool started from nothing, and none of them knew anything about each other.
The brief, the personas, and the brand guidelines had to be re-explained in every session.
The copy still came back off brand, so the time saved drafting went straight back into rewriting.
Everything Natasha and her team built lived in a browser tab, in tools that could not see their files or each other's work.
More self-teaching was not going to close that gap. They wanted a straight answer on three things: what agentic automation actually looks like in a marketing workflow, what it takes to get there, and whether any of it is possible with no developer and no plan to hire one.
"This is something I tried to understand, and I was like, oh, I probably need to learn a little bit more."
The Journey
Enlighten Designs' Principal Technologist, Sam McKoy, ran an interactive session with Natasha to understand how Hamilton & Waikato Tourism actually work. Our approach began with:
Establishing why the existing tools kept stalling, rather than treating it as a prompting problem. The writing was never the weak point. The forgetting was.
A recommendation to write the context down once, in a file Claude reads before every session, so the briefs, the personas and the brand guidelines stop being re-explained.
Building on what Natasha had already attempted rather than replacing it, mapping each piece against the workflows she had been trying to automate.
Sam also showed Natasha his own everyday use of Claude, and how he takes the repetitive parts out of his week using chat, Cowork, connectors and skills. Everything that he demonstrated was something he had built for his own work.
The Solution
From there, the two of them worked through understanding the four building blocks that turn Claude from a chat window into working infrastructure, each one mapped against Hamilton & Waikato Tourism's own workflows.
A written brief Claude reads every time. So it already knows the organisation, the region and the brand guidelines before anyone types a word.
Skills. Repeatable instructions for the tasks that come round every month, written once and reused, so the tenth LinkedIn caption is as good as the first.
Projects. Keeping the work for a campaign together, with its own context, so nothing gets lost when someone else picks it up next month.
Scheduled tasks. Work that runs without anyone opening a laptop, which is where a marketing team of this size gets real leverage.
Sam covered every block against the team's own work, so the question was never "what could this do" but "which of these is worth doing first".
"I came in thinking we were already doing this fairly well. I left with a list of things we should have set up a year ago."
"It gave me a great guide on where to start and what to do next."
The Results
The two sessions were never going to end with a finished setup. The goal was narrower and more useful: give Natasha a clear direction she could act on herself, without a developer.
That mattered because of the scale she works at. Natasha produces six to ten posts a week across different social channels that each have a different audience and a different voice, and she is the only person on digital marketing in a team of six. Reporting takes her about a day, pulling and interpreting numbers from Google Analytics and Meta while the platforms keep changing. Her old setup ran one conversation at a time, so the AI often forgot what came before, and she would have to start again.
She left the sessions able to name which of her recurring jobs justify a skill, which belong in a project, and which parts of the monthly cycle should run on a schedule. Cowork was the piece she saw the most immediate use for, given the number of channels she runs and the different message each one needs.
The clearest sign it landed is what happened next, without anyone from Enlighten prompting it. Within a week, Natasha had moved to the paid plan, written her first skill, and started building her first scheduled task, with a request already into IT to get Cowork on her laptop.
She also came back with a list of questions from the session. On setup: what to configure before inviting the wider team, how to secure Cowork on her desktop, and whether Claude could connect safely to the organisation's SharePoint. On ways of working: whether to import her old context or start clean, and where brand guidelines belong in an organisation-wide instruction, or a shared skill.
Those are the questions of someone building, not someone still deciding whether to start.
Enlighten did not take the work away. Sam gave Natasha the four building blocks, and Enlighten Designs Marketing Associate, Drishti Ratna, showed her what they look like inside a marketing role, so she can apply them to the rest of her work herself.
What happens next
Natasha is building against the shortlist. The written brief and the skills for the weekly jobs come first, because those pay back fastest.
Enlighten is working through her questions on settings, desktop security, SharePoint and organisation-wide guidelines, which is the groundwork for bringing the wider team on.
We will check back in once Hamilton & Waikato Tourism have run a full monthly cycle on the new setup, to capture the numbers: how long reporting takes, how much of the weekly content load is running through skills, and which of the four blocks earned their place.
"We were already using AI every day. Enlighten showed us how to make it actually work for our team."
