SwarmOS Training
Six weeks to an AI-fluent team.
A hands-on enablement program for organizations. The usage policy is written before staff touch a tool, every session runs on your team's real work, and trained champions keep the practice alive after we leave.
What your team walks away with
Not a certificate. A working practice: rules your organization agreed to, libraries your teams built, and people inside the building who keep both current.
The data boundary comes first: what never enters an AI conversation, agreed with leadership and signed before any staff session runs.
Built live during the sessions, on your templates and your recurring work, so good practice belongs to the organization rather than one person.
Each team leaves with a short playbook for the drafting work it actually does: reports, correspondence, summaries, translations.
Two or three of your staff learn to run the practice: keeping libraries current, fielding questions, spotting the next use worth building.
A standing 45 to 60 minute session where champions bring real edge cases, and the policy and libraries stay current as the tools change.
Every session is recorded for staff who could not attend live. The recordings and all materials are yours to keep.
How the program runs
Three audiences, in the order that makes adoption stick: the rules get written, your in-house experts get built, then every team learns on its own work.
Platform setup and governance, what the tools can and cannot do, and the usage policy co-authored at the table. This is also where we scope which teams train and in what order.
Two or three of your staff, ideally one per site or team. They build the real shared workspaces and prompt libraries they will maintain long after the program ends.
Grouped by team or role. Hands-on from the first minute, on the work each cohort already does, with the review habit practiced until it is automatic.
What the sessions cover
The curriculum is adapted to your teams during scoping. The spine stays the same.
What these models are and are not, where they fail, and the verification habits that catch it before it costs you.
What never enters an AI conversation, why, and how the policy holds up under real deadlines. Taught first, to everyone.
Structuring a request, giving the right context, iterating on drafts, clearing context between tasks, and what the context window means in practice.
Reports, correspondence, meeting notes, program materials, and translation first drafts, practiced on your own templates with review discipline.
Choosing the right model for the task, keeping costs predictable, and knowing when not to use AI at all.
In the final weeks: which recurring work is ready to become an automated, human-approved workflow, and what that path looks like.
Security, privacy, and compliance
The part we refuse to rush
The rules exist before the habits do.
The data boundary is co-authored with leadership and signed before any frontline session runs. Staff learn the rules and the tools together.
Every exercise runs on your templates and realistic stand-in examples. Client, customer, and patient records are never part of training.
We train on the enterprise AI platform your organization adopts, and help you configure workspaces, retention, and access to match your rules.
Privacy law in your sector is treated as a design constraint, not an afterthought. Your privacy officer rules; nothing we teach is legal advice.
For workloads that must never reach a cloud service, we advise on fully local AI setups, where the models themselves run on your own hardware, including the honest trade-offs that come with them.
Who teaches it
Your sessions are led by practitioners who run governed AI systems in production for a commercial business, every day.
The policies, habits, and workflows in this program are the ones we use ourselves, refined against real deadlines and real stakes. Nothing here was assembled for a course.
For teams that want to go further, the same practitioners design governed, human-approved AI workflows that run on your own infrastructure. That conversation starts once your team is fluent.
Common questions
Which AI platform do you train on?
The one your organization adopts. The program is platform-agnostic: the data boundary, the drafting craft, and the review habit transfer across every major enterprise AI tool. If you have not chosen a platform yet, the leadership sessions include an honest comparison for your situation.
How many people can the program cover?
The default program covers leadership, champions, and up to four staff cohorts, which suits most organizations up to a few hundred people. Larger teams add cohorts; we scope that with you before anything is signed.
What does it cost?
Pricing is scoped to team size, cohort count, and delivery format. Tell us about your team below and we reply with the full program outline and a quote within one business day.
Do you need access to our data or systems?
No. Training runs entirely on your templates and stand-in examples. The only things we ask for are your recurring document types and, for the leadership sessions, whoever owns your privacy and IT decisions.
Can sessions run in person?
Yes. Live virtual is the default because it schedules cleanly around service delivery, and in-person delivery is available. Tell us where your team sits and we will include it in the quote.
Is six weeks fixed?
Six weeks is the default cadence because habits need spacing to stick. Condensed and extended schedules are both possible, and sessions are scheduled around your operations, not the other way around.
The program details · one business day
Tell us about your team.
We reply with the full program outline, a proposed cadence for your organization, and a quote.