What you say
“We need this training built properly, and we needed it last quarter.”
AI implementation for UK firms
AI implementation for UK firms
It has to work, it has to land on time, and it has to stay on budget. Your team is already at capacity. That is the problem we solve.
AI should be making this faster and cheaper. Instead it is one more thing nobody has had time to learn properly. You do not need another vendor explaining the opportunity. You need the work delivered.
We build it with you, then hand it over. And because we build training for a living, this page is a short course rather than a sales pitch. You will work a real problem on the way down, and leave with yours written down.
You are short of four specialists, and every project is waiting on all four of them.
Click each role to see what breaks when one person carries all four. This is the same pattern we build into your training. Learners reach the answer instead of being handed it.
Without it, training looks finished and changes nothing.
Without it, learners get lost and quietly give up.
Without it, good design dies in a slide deck.
Without judgement, AI just makes more mediocre content faster.
Four specialisms, one calendar. Something always gets the leftovers.
What you say
“We need this training built properly, and we needed it last quarter.”
What it feels like
“Everyone is using AI to move faster and we are still deciding where to start.”
Why it is wrong
Good training should not be out of reach just because you cannot hire four specialists.
That is the gap. We close all four of them with one team.
Two ways to get this built. Open both and see which one you recognise.
A designer, a developer, a UX contractor and an AI consultant. Four contracts, four timelines, four versions of the truth. You become the project manager, and the work slows down between every handoff.
Design, build and AI in the same hands. Nothing is explained twice, nothing waits in a queue, and the person who designed it is the person who ships it. That is the whole model.
You already know which one you would rather manage.
The difference is not effort. It is the nine weeks lost to handoffs, re-briefing, and waiting.
One session to find the real problem. One team to build it. Then your team runs it without us.
Open each step. Same principle as good training: short, sequenced, nothing hidden.
One working session. We find where the training is actually failing and where that is costing you money. No discovery theatre, no six week audit.
Design, build and AI handled by the same team. You see working versions early, not mockups. It gets done right the first time because nobody is guessing what the last person meant.
We hand it over with everything your team needs to keep it going. If you never need to call us again, we did the job properly.
Fifteen years of too much to build and not enough people to build it. Which is why you are getting evidence here, not a strategy deck.
Everyone claims training expertise. Everyone claims AI. So ask for the numbers, and ask what they have actually shipped. Here are ours.
15+
Years building training
1,000s
Hours designed and delivered
1M+
People trained
26
Countries
8
Languages
“AI-enabled” is a claim. This is what AI-native looks like.
Four years building with AI in production, not reading about it.
Advisory work at board level on how AI gets adopted, not commentary from the sidelines.
The system that produces the work is ours, built and run in production.
And at every stage, the AI is held to four things.
This is the part most AI workflows skip. Every output gets checked against all four before it goes anywhere near a learner.
If we cannot show you the evidence behind a decision, it does not ship. No trends, no guesswork dressed up as innovation.
We start from the behaviour that has to change. Everything that does not serve that outcome gets cut, however good it looks.
Real people, mid-shift, on a phone, short on time. Adult learning principles applied properly, not assumed.
If it does not reduce errors, speed up ramp, or cut support load, it is decoration. We would rather build less and shift the number.
Fifteen years of craft, four years of AI in production, and every AI decision tied back to evidence, outcome, learner, and impact. That is the difference.
You are already in one of them. Here is what each looks like twelve months from now.
IF NOTHING CHANGES
IF YOU FIX IT
Direction of travel across the training we have shipped. Your numbers get measured against your business, not our portfolio.
“Most people in the AI space talk about what’s possible. Goodsell Consulting has already built it.”
Sam Singh, Founder/CEO, Sentium Labs
“He was able to synthesize it all into a recommended tech stack and approach, fully street-ready to start building things.”
Keith Schroder
“He doesn’t help you plan. He helps you launch.”
Tony Dina
What is bad training actually costing you?
Choose any answer to see the marking.
Partly. Onboarding is the visible cost, and the smallest one.
Correct. Every avoidable error was a gap in what someone was taught.
Correct. Weeks of slow ramp is revenue you never invoiced.
Correct. Your support team is absorbing the cost of unclear training.
All of it counts. Training is not a cost centre. It is revenue you are either capturing or leaving on the table.
A real situation with four plausible explanations. Pick the one you would investigate first.
THE SITUATION
Twelve new sales hires complete a two-week onboarding programme. Completion is 100%. Every one of them passes the end-of-course quiz. Ninety days later, nine of the twelve are still missing quota, and your support team is answering questions the training already covered.
What is the actual failure here? Choose the one you would investigate first.
Unlikely. Twelve people all failing the same way is a design fault, not twelve individual attitude problems. Blaming the learner is the least defendable conclusion available.
Strong. They proved they could remember it in a quiz, never that they could do it under pressure with a real customer. Assessment aligned to the wrong outcome makes failure invisible until quarter end.
Strong. Front-loading everything ignores how people actually retain and apply skill. Without practice and support at the point of work, the ninety-day drop is predictable.
Tempting, and mostly wrong. Better production values on the wrong outcome just makes an ineffective programme more pleasant to sit through.
THE DIAGNOSIS
Options two and three are the same root cause: the programme was designed around finishing, not around performing. That is the failure we are hired to fix, and it is why we start from the behaviour that has to change and work backwards.
CLARIFY YOUR OWN PROBLEM
This is the same intake we use on a real project. Answering it will sharpen how you describe the problem internally, whether or not you ever work with us.
Now imagine it built for your team, in your language, on your deadline.
You worked a real problem, made a judgement, and got feedback that explained itself rather than scoring you. That is what we design, and it is the difference between a course people finish and a course that changes what they do. Book fifteen minutes and bring the problem you arrived with.
1 OF 6
Design, build and AI sit in the same hands. Nothing is explained twice, nothing waits in a queue, and the person who designed it is the person who ships it. Every AI output is checked against four things before it goes near a learner: defendable learning science, the desired outcome, the learner, and what moves the needle.
One hire covers one of the four specialisms. Instructional design, UX/UI, development and AI all have to land for a programme to change behaviour, and a single calendar cannot carry all four. You get the whole team for the length of the build, then your team runs it.
No. We work to a fixed scope agreed in the first session, and we tell you at that point what will land and what will not. A typical build runs in weeks rather than months because the work does not stop between handoffs.
You see working versions early rather than mockups, so progress is visible from the first week. The comparison we publish is five weeks for one team against fourteen weeks across four vendors on the same project. The nine week difference is handoffs, re-briefing, and waiting.