Useful AI without the theatre
Marketing teams are expected to use AI and are rarely told what for. I help a team work out which parts of its process improve with a model in the loop, which get measurably worse, and how to tell the difference without risking the brand to find out.
What results has AI consultancy produced?
The AI content system I built for a regulated digital-asset firm runs 53 task-specific skills, covering research, drafting, SEO, design and compliance review.
Numbers I’m proud of
- 53Task-specific skills covering research, drafting, SEO, design, and compliance review
- 74Eval cases across the six skills where a bad prompt change would do the most damage
- 45Checks a piece passes before it can publish, 8 of which block it outright
Workflow audit
I map how the work actually gets done now (the real process rather than the documented one) and mark where a model in the loop would help, where it would hurt, and where it would just add a review step. Most teams are automating the wrong half.
Tooling and setup
Which tools, configured how, with what context. Most of the value is in the setup rather than the subscription: the prompts, the source material, and the connections into the systems you already use.
Quality standards
An explicit floor for what gets published, who reviews what, and which categories of work never go out without a human decision. This is what stops the slow drift toward generic.
Enablement
Training your team to do this themselves, with worked examples from your own work rather than a generic deck. The goal is that you do not need me afterwards.
A fixed fee of £4,000 covers one product in one market, over three to four weeks. A second product, another region or interviews with your customers are quoted before we start.
What you get
How the work runs
Week 1
Diagnose
How the team works now, what it spends time on, and where the genuine constraints are. Often the answer is that AI is not the highest-value fix available, and I will say so.
Week 2–4
Pilot
Pick two or three workflows and rebuild them properly, with a quality bar agreed up front and a way to tell whether it worked. Narrow and real beats broad and theoretical.
Month 2
Standardise
Turn what worked into something repeatable: documented prompts, review steps, and the standards that keep quality from sliding once the novelty wears off.
Ongoing
Hand over
Train the team, document the decisions, and leave. Check in periodically as the tools change, because they will.
After the handover your team runs the plan, or I run it with them. Full pricing
Teams that want measurable gains and a working process at the end of the pilot.
- Teams told to “use AI”
- A mandate from above, no brief, and no idea which parts of the job it should touch.
- Small teams, wide remit
- Two or three people covering what ought to be six roles. This is where AI saves the most time.
- Regulated businesses
- Where the upside is obvious and the failure mode is a compliance incident, so the guardrails have to come first.
- Founders doing their own marketing
- You are the strategist, the writer and the analyst. Getting the workflow right buys back the most time.
- Content teams under volume pressure
- Being asked to publish more without more people, and wanting to do it without the quality collapsing.
- Teams that already tried
- Adoption stalled, output got blander, and people quietly went back to the old way. That is a workflow problem rather than a tooling one.
Who will I work with?
You work directly with me throughout the engagement.
I lead marketing at a regulated digital-asset firm, and led it at Improbable before that. At eBay’s KnownOrigin I led the digital marketing strategy. Agency-side, I ran digital strategy for clients in finance, travel and energy, among them Liontrust Asset Management and Aldermore.
Questions before an engagement
Something not covered here? Ask me directly.
Is this going to replace my team?
No, and I would be sceptical of anyone selling it that way. What it reliably does is remove the parts of the job people are worst at and most bored by: first drafts, reformatting, summarising, research legwork. The judgement, the taste and the relationships are the job, and none of that is automatable yet.
Won’t our content just sound like everyone else’s?
It will if you skip the quality standards, which is exactly why they are half of this engagement. Used badly these tools produce fluent, confident prose that nobody remembers. Used properly they get you to a good draft faster and leave more time for the editing that actually makes it yours.
Which tools do you recommend?
It depends on the work, and the honest answer is that the specific tool matters far less than the setup around it. I use Claude, Claude Code, Codex and Cursor daily. I will recommend based on what you are trying to do rather than what I happen to like.
We’re regulated. Is this even viable?
Yes, with the guardrails designed first rather than retrofitted. That means being explicit about what never goes out without human review, what source material a model is allowed to draw on, and where the audit trail lives. I have worked with Legal and Compliance in the approval path and it is workable.
Are you an AI specialist or a marketer?
A marketer who uses these tools to do marketing, rather than an AI specialist looking for marketing problems to apply them to. That means I am more likely to tell you a particular workflow is not worth automating, because I have to live with the output.
What if the tools change in six months?
They will. That is why the deliverable is a way of working rather than a fixed toolchain. The judgements about what to automate and where the quality floor sits outlast any particular product.
How much does it cost?
The audit and pilot are a fixed-fee project. Enablement is priced by team size. I will give you a number after the first conversation.