Do I need to know what should be automated?

No. Most people arrive with a feeling rather than a specification — something takes too long, or only one person can do it, or it gets dropped whenever the week is busy. That is enough to start from. If you can point at one job you would gladly stop doing by hand, we can work with that. If you can’t point at one yet, start with the free diagnostic instead: it finds the constraint first, and the workflow follows from it.

What happens with the first workflow?

We build it. You describe the job the way you would explain it to somebody starting on Monday — what comes in, what you would check, what should go out, and what you would never let leave without reading it. That becomes a working workflow, connected to the tools you already use, running on your account. You watch it run on real work before you rely on it. One workflow, start to finish, so what you are judging is a thing that works rather than a proposal for one.

What happens after that?

It runs. Keeping it running is the recurring part — hosting, the models it calls, monitoring, and the fixes for when something upstream changes its mind about a field name. Most people then add a second workflow, and it is usually one they spotted themselves while watching the first one work. There is no bundle to commit to up front. The next workflow is a decision you make when you want it, and not before.

Can my team eventually build workflows themselves?

That is the intended end state, and the training exists for it. Once your team has watched a few workflows get built, the skill turns out to be the describing — knowing what the work actually involves and where the judgment sits — which is the part your team already has. Some businesses would rather we kept building, and that is a legitimate choice rather than a failure. Most want at least one person inside who can change something without picking up the phone.

Do I become dependent on hmn.plus?

It is the right question to ask any vendor, and the honest answer is that you can be for exactly as long as it is useful. Three things are deliberate: the workflows are described in plain language rather than locked in a format only we can read, they run on infrastructure that can sit in your own name, and we teach the building instead of keeping it. Being the only people who can change your systems would be a business model. It is not ours.

Can we eventually own the system?

Yes, and it is an option rather than a destination — plenty of businesses would rather we kept running it, and that is a reasonable thing to want. When you do want it, the workflows, their definitions and the infrastructure transfer to you, and your team keeps the training that makes them usable. We would rather you stayed because staying is worth it.

The first automation is a fixed price, so the first decision is a small one: NZ$500 + GST to map it and get it built. After that, the platform it runs on is NZ$150 + GST a month for each person who builds workflows — everyone else who uses it is free — and that covers hosting, running your workflows, monitoring and support. Workflows you build yourself cost nothing extra; the ones we build are quoted one at a time, on what each actually involves. No annual lock-in, and nothing larger to sign before you have seen something of your own working.

Why not use ChatGPT, Claude, Zapier or n8n?

They answer a different question. Chat tools put something capable on the other end of a conversation, and then nothing happens unless a person types — every session starts again, and what the business knows ends up living in whoever writes the best prompt. Zapier and n8n wire apps to each other; the wiring holds until a field name changes, and it never makes a judgment call. Both leave the work depending on a particular person. What we build has a fixed shape: the same steps in the same order, your rules written in, a record of every action and the reason for it, and a person standing where a person should stand. The thinking inside a step can be as sharp as it needs to be. The path through it does not change because somebody phrased something differently. That is the difference between a tool one person is good at and a system a business runs on.

Where should AI actually be used?

On the judgment inside a step, not on the whole step. Reading an enquiry and working out what kind it is: yes. Drafting a reply in your voice, from your own past replies: yes. Moving money, or telling a client something binding, with nobody looking: no. What we build to is that anything with consequences waits for a person, and everything in front of it does not have to. A faster version of a bad process is still a bad process, which is why deciding where AI belongs happens before anything gets built, and is most of the value.

Harnessing creativity with AI post-automation

Unlimited AI resources - now what?

After implementing countless automations and maximizing AI capabilities, most business founders stumble upon an unexpected dilemma. They've gotten so used to letting artificial intelligence handle routine operations that they find themselves asking, 'What now?' That's not a problem, though—quite the contrary. It signals a transition into a more profound, more strategic phase of using AI. So let's talk about why this is good.

Bringing it back to basics

Imagine, for a moment, that it's the pre-AI era and you're a founder with access to endless business resources. How would you allocate those resources effectively? What challenges would you tackle? Just because technology has evolved doesn't mean these questions are any less relevant. The challenge isn't about having enough resources; it's about deploying them creatively and intelligently.

Before AI, the efficient allocation was about tangible logistics. Now, it’s about leveraging (not the AI buzzword—old-school leveraging) creativity.

The power of creativity in AI resource allocation

Execution has become abundant—or even cheap—thanks to AI. The true scarce skill lies in creativity: the ability to think artistically, solve problems innovatively, and reframe challenges in ways others haven't considered. Visionaries don't just look at a task list and find ways to automate; they ask which new problems are worth solving in the first place.

Think of creativity like an art form. It’s the brush that lets you paint on a new canvas. You may have all the paints, but without a brush, your vision remains unrealized.

So where do you start? By redefining problems and tapping into new opportunity areas where AI can shine. Here’s how:

Define the impact: Identify where AI implementations can create genuinely transformative outcomes. It’s not just about doing things faster but doing things that matter.
Explore intersections: Use creativity to merge fields. Where does AI meet customer experience? Where does it enhance storytelling in marketing or revolutionize human resources?
Challenge norms: Question existing processes and assumptions. Could AI enable a completely different way of handling customer service? What about product development?

The soul of your operations

Tapping into creativity lets you pour your AI resources into the areas that align with your values and goals. It's not about automating for automation's sake; it's about creating a masterpiece that represents your brand's soul.

In the end, the real skill for today's business owners isn't finding more to automate. It's identifying where their AI-driven tools can be most impactful. It's about shifting from being an executor to a creator, from asking 'what can I automate?' to 'what should I build?' And within that shift, you'll find the surprising answer to 'now what?':

Create, define, and disrupt— with purpose.