Emma Sexton founded Inside Out, a creative awards community with a membership built around it, and runs it with a team of 4. She was weeks from launching a paid content tier built on the quality of the content her team produced. The problem was not a missing tool. The team used AI, but in silos.
We were sort of in that doom cycle - you know things need to change, but you don't feel like you've got the time, because you're too busy, but you know the stuff you should be doing will give you the time. So you keep going round in that loop.
The shift came from an outside view of the whole operation. The assessment talked to all 4 people, not just the founder, and surfaced 11 interlocking pain points across the team - the kind of friction a founder cannot map from inside the day-to-day. The result is a team that once used AI in silos, now building its own workflows.
The diagnosis
The biggest finding was not a workflow problem. It was a knowledge problem.
One thing that surprised me was that the team told you stuff they hadn't been telling me. I realised I had quite a one-dimensional view - there were friction points that hadn't actually been discussed.
The report named the pattern plainly: these were not separate problems. They were the same tax, paid in different currencies by different people.
Before the assessment, the team was using AI in silos - each person in their own chat, without the shared memory or structure to make it useful at a team level.
The recommendations
The report ordered 22 recommendations by leverage, not by ease. Quick wins first - the changes that would clear the most drag with the least build time - then bigger builds sequenced for after the foundation was in place.
The roadmap did not hand Emma a pile of tasks. The keystone was a tone-of-voice Claude Project - a shared workspace trained on Inside Out's voice, so content arrives in the right register without a re-tone round-trip, targeting the exact friction the diagnosis had named. From there, each team member had their own sequenced next steps, and 5 custom agents were scoped into shared Claude Projects: the team owns the system, not just the recommendations.
Other quick wins included CRM status and field tidy-ups - the foundation the nurturing and disengagement list both sit on. Most of the plan runs on tools Inside Out already owns, rather than new software.
We didn't know what the first 1% was, because everything felt like a priority. Seeing 'these are your quick wins, these are your longer-term things' gave us a roadmap. It just made it more digestible.
The outcome so far
Inside Out is 12.5 hours a week back so far, of 16 identified. On a 7-hour working day, that is roughly 1.8 days a week reclaimed. 13 of the 22 recommendations have been actioned.
The most striking result is something that did not exist before the assessment: Inside Out now produces a monthly Global Insights Report for their paid members. Built on a shared Claude team account with Projects, the report mines a month of recorded member conversations, then Claude designs and formats the finished piece. Inside Out built this themselves. HoursBack supplied the assessment and roadmap that made it possible.
We've used Claude to create a monthly insights report - it looks at all the conversations from the month, and Claude designs and formats it. No heavy lifting for the team, but enormous value for our paid members. That came out of the work we did with you.
The four-person team diagnostic is priced at £1,999 (a standard team diagnostic is £1,199). Asked whether it was worth it, Emma did not hesitate:
Yes, I would. 100%. Honestly, I don't think you can do this piece of work yourself - if I could have done it myself, I would have done it.
The takeaway
Inside Out started with no idea where to begin, a wheel spinning between 4 people, and AI sitting unused in separate chats. Today they have a shared system the whole team builds on, 12.5 hours a week back, and a monthly member report that did not exist before. The assessment did not hand them a to-do list. It surfaced the friction they could not see, then showed them exactly where to start, so more of the week goes to the work only they can do.
The AI tools were like a racehorse locked in the garage - we didn't even know if we had the right racehorse. Now we know we've got the right one, we've opened the gates, we're in the paddock. That's progress.
That is what an AI workflow assessment does for any business that runs on conversations: it finds where your time is actually going and gives you a sequenced plan to win it back.
Case study subject: Emma Sexton.