01
They automate the wrong task
The impressive demo is rarely the expensive problem. The task actually worth automating is usually boring, frequent, and invisible in any strategy deck.
Not chatbots for the sake of it. I find the tasks your team repeats every week — follow-ups, reporting, content production, lead routing — and build systems that handle them reliably, with a human still in the loop wherever that matters.
None of them are technical. All of them are decided before a single tool is chosen.
01
The impressive demo is rarely the expensive problem. The task actually worth automating is usually boring, frequent, and invisible in any strategy deck.
02
A system that is right eighty-five percent of the time and left unsupervised is worse than no system. The other fifteen percent reaches customers, and trust is expensive to rebuild.
03
An automation built by whoever was enthusiastic, undocumented and unowned, breaks the first time a tool changes its API — and nobody left knows how to fix it.
Useful automation is unglamorous. It does one repeated task reliably, tells you when it fails, and is documented well enough that you are not dependent on whoever built it.
Starting from where your hours actually go, not from a list of tools someone wants to sell you.
We map where your team’s hours actually go, then rank tasks by frequency, tedium and risk. What gets automated is what scores high on all three — not what demonstrates well in a meeting.
Lead capture through to CRM and follow-up sequence, wired so no enquiry sits unanswered overnight and every source is attributed correctly when you look at the numbers later.
Drafting pipelines that produce content in your brand voice from your own material and positioning, with a human editing step standing between the model and anything published.
GA4, Search Console and ad platform data pulled into a single scheduled summary, so the weekly numbers arrive on their own instead of costing someone an afternoon.
Multi-step processes where an AI agent handles research, drafting and routing across tools — with defined checkpoints where a person approves before it proceeds to the next step.
Every automation documented: what it does, what it touches, how it fails and how to fix it. Built so your team owns it rather than renting it back from me indefinitely.
A working session to list what actually gets repeated each week, how long it takes, and what it costs when it is done late or badly.
The highest-value candidate gets chosen and scoped alone. One workflow, done properly, beats a transformation programme nobody finishes.
Built on your existing tools where possible, then run against real historical cases to see where it breaks before it touches anything live.
Handover documentation, failure alerts and a review after a few weeks of real use — then we decide whether there is a second one worth doing.
The fastest way to waste money on AI is to buy a strategy. We pick the single most expensive repeated task in your week, automate that, measure the hours it returns, and only then decide what comes next.
Everything is built in your own accounts under your own credentials. If we stop working together, nothing switches off and nothing needs to be handed back.
One workflow scoped, built, tested against real cases and documented before we discuss a second.
Built on the stack you already pay for. New subscriptions only where there is no reasonable alternative.
Documented, in your accounts, under your credentials. No dependency on me to keep it running.
Almost never. A chatbot is one of the least valuable things you can build with AI, and it is usually the first thing people ask for.
The work that returns real hours happens behind the scenes: follow-up that happens without anyone remembering, reports that assemble themselves, drafts that arrive ready to edit. I would rather automate the task you dread on Monday morning than add a widget your customers will try to close.
It will if you point a generic model at a generic prompt. The systems I build are grounded in your own material — your existing writing, your positioning, the language your customers actually use — and every piece passes through a human editing step before it publishes.
AI is used to remove the blank page, not to replace judgement about what is worth saying.
It will, eventually. Every system does. That is why anything customer-facing has a human approval step, and why every workflow reports its own failures instead of failing silently.
The design question is never "will this be perfect" but "what happens on the day it is not" — and that answer is part of the build, not an afterthought bolted on after the first incident.
Usually the opposite. Small teams feel repetitive work most sharply, because the same person does the admin and the actual job.
If a task takes two hours a week and can be reduced to ten minutes of review, that is close to a hundred hours a year returned to a business that does not have a hundred spare hours. Small scope is the point here, not a compromise.
Everything is built in your accounts, under your credentials, and documented — what each automation does, which tools it touches, how it fails and how to repair it.
You should be able to hand that documentation to any competent person and have them maintain it. An automation that only works while I am reachable is a liability I have sold you, not an asset.
Tell me the task you dread most. If it is worth automating, I will tell you roughly what that takes — and if it is not, I will tell you that instead.