The lab teaches the supervisor role as a working course. Participants bring real tasks from their own organizations and leave with completed canvases.
A role definition rather than a job title. Organizations adopting agentic systems keep discovering they need someone to do a particular kind of work, and keep giving that work to whoever is nearest: an automation lead, a product manager, an engineer who is good with prompts. The results are uneven because the responsibility has never been stated.
The lab teaches this as a course for practitioners, taught first by Sravan Ankaraju and later by others. Participants work on real tasks from their own organizations and leave with completed Work Composition canvases rather than a certificate of attendance.
The agentic AI supervisor course is delivered directly to corporate cohorts. There is no open cohort for individuals scheduled yet, and we would rather say that than take a waitlist deposit. Write to the lab and you will be told when one is scheduled.
One open course by the same instructor runs now: Knowledge Manufacturing for Learning and Development, on Maven. It is a different course with a different subject. It is listed here because it is the one thing on this page an individual can buy today, and because the instructor is the same.
Not a worked example from a slide. A description of a task you are actually accountable for, precise enough that a colleague can disagree with it.
Which decisions in that task require a person, and the reason, written down rather than felt.
What evidence the task should produce, so that its performance can be assessed later rather than asserted.
The course does not issue a certification, and the lab holds no partnership with any certification body. What you leave with is the work you did, not a credential attesting that you attended.
Write with the question you are trying to answer. A paragraph is enough to tell whether this is a fit.
Mail to hello@euler.center is read by Sravan Ankaraju, who founded the lab. Expect a reply within 48 hours, and a straight answer about fit rather than a discovery call.
