A corporate AI bootcamp is an intensive training engagement in which teams learn AI by shipping with it: each team builds one real, working system from start to finish, in AI accounts the organization owns. The deliverable is double. You get a system your people built and can run the day after we leave, and you get people who understand it well enough to change it and to build the next one.
That second deliverable is the durable one. Tools keep changing under everyone’s feet. A team that has taken one system from blank page to working build can repeat the trick on whatever ships next year.
How is a bootcamp different from a course or a workshop?
The three words get used interchangeably. They name different formats with different outcomes, and confusing them is how training budgets get spent on the wrong one.
A course teaches concepts. Someone presents and the slides advance. People take notes, and the notes go where notes go. Courses build awareness, and awareness has real value early on. Capability is a different substance. Watching a system get built and building one are as different as watching swimming and swimming.
A workshop is a working session scoped to one role. People practice patterns on their own tasks and leave with individual fluency. We run those as role-based workshops, and they are the right size when the goal is a function that uses AI well in its daily work.
A bootcamp is organized around a build. The team is the unit. The system is the syllabus. The schedule bends around getting the thing working, and lecture exists to serve the next step of the build. When the engagement ends, the proof of learning is a system doing its job.
What happens inside a corporate AI bootcamp?
The shape stays consistent even as the build varies.
It starts with a choice. Each team picks its build from a preset catalog of seven systems that teams can realistically take from zero to working inside the format. The catalog is a feature of the pedagogy, since scoping a brand-new system from nothing is its own skill and a bad first rep. Removing the blank page sends the team’s effort where we want it: into the build.
From there the build runs end to end in your organization’s own AI accounts. Accounts get set up, data questions get answered, prompts get written and rewritten, and the system gets wired together and tested against real cases from your own work. There is no demo environment at any point. A demo environment produces a system that works in the demo environment. Your accounts produce a system that works where you work, under access and billing you control.
A note on who belongs in the room. Bring the people who do the work the system will touch. The person who runs the intake queue knows the edge cases that will break a first draft of the build, and a system with their fingerprints on it is a system the team will actually trust. Seats go to builders before observers.
You will see demos from us along the way, and a word on those. Every demo we show is recorded from a real build and cut into slides. We never promise a live demo. A live demo proves the venue wifi works. A recording proves the build did.
What do teams actually build?
One system per team, chosen from the catalog. Two if the reps run fast. The cap is deliberate: full understanding of one working system beats a sampler of four half-finished ones.
The right scale of build sits between a prompt trick and a platform migration. Picture an operations team that loses hours every week to inbound documents. The system that team would want reads each document, pulls out the fields that matter, and routes it with a draft summary for a person to approve. A team can build that scale of system inside the engagement and understand every part of it.
A support team might pick something different: an assistant that drafts replies from the team’s own documentation. A person still reviews before anything sends.
Notice the person still in the loop in both hypotheticals. That is a habit of ours. Bootcamp builds augment the team that runs them. Zero people replaced is a line we hold, and the measured ROI comes from hours handed back to your people.
Bootcamps are our flagship service. The format details live on our Hands-On AI Bootcamps page.
What does everyone walk out with?
Four things, concretely:
- A working system in your own accounts. Nothing about it belongs to us, so nothing about it stops when we leave.
- The people who built it. They can explain every decision in the build because they made every decision in the build.
- Sometimes a second system, when a team’s reps ran fast.
- Thirty days of support, included. The useful questions arrive after the room empties, when the system meets a case nobody predicted, and we are reachable while that happens.
One footnote for anyone comparing formats: bootcamps include that 30-day window, while our workshops offer the same window as a paid add-on.
There is also a quieter asset that never fits on a deliverables list. Call it shared vocabulary. A team that has shipped together can say “add a review step before anything goes out” and everyone pictures the same change. That sentence is worth a lot the first time the build needs to grow.
How do you know a bootcamp fits your team?
Teams that get the most from the format share two traits. There is a process that costs real hours every week, one the team could name without thinking. And there are named people who will own the system afterward, because a system nobody owns becomes a system nobody trusts.
Some situations call for a different door, and we will say so. Leadership still deciding what AI should mean for the organization gets more from an advisory engagement or a keynote than from a build. A team that needs a system delivered without the training layer wants an automation build instead. Sorting that out is what the first call is for. It runs 30 minutes and costs nothing. Pricing for a bootcamp is fixed scope, and the numbers come out on that call.
Preparation for that call is light. Come knowing the process that hurts and who would own the fix. That is enough for us to tell you whether a bootcamp fits, and enough for us to put a number on it.
The pedagogy behind all of this is autobiographical. Our founder, Dexter Brocks, taught himself from the support desk up to cloud engineering, and a decade in tech never changed his read on how people learn tools: by building something they need with one. He teaches the same way on stage, including at the University of Chicago Polsky Center, and the same way in your conference room. Based in Chicago, traveling wherever your team is.