Most AI training fails for a boring reason: it’s built for everyone, which means it’s built for no one. A marketing team doesn’t need what a data team needs, and both can smell a generic exercise a slide away. So we don’t run one workshop with the department names swapped. We build each track around the work your team did last week: the briefs, the tickets, the backlog. A short planning call gets us those samples, and the examples on screen are yours from the first minute.
The session itself is mostly building. We teach in short bursts and build in long ones, and everyone builds, managers included, because a manager who has shipped a workflow judges AI work differently forever after. By mid-session every person has something running. By the end, the team has working prototypes and something rarer: agreement on which ones are worth keeping, what good output looks like, and who owns what next. The first draft of that playbook gets written in the room, not promised in a follow-up.
We’re honest about what one day can do. A workshop won’t stand up production infrastructure; that’s what automation builds are for, and we’ll tell you when you’re ready for one. What a day can do is move a team from curious to competent on the work it already owns, with prototypes running and a professional habit of checking the output. Zero people replaced is still the stance. The team gets faster. The team stays.
When several teams need this at once, the multi-team day keeps it honest: one shared kickoff so everyone hears the same principles, then parallel tracks so nobody sits through another department’s examples. Same method, scaled sideways. And when one team wants more than a day gives, the bootcamp is the long version of exactly this.