Status: first draft. Bare-bones structure. Hypothesis → Actions → Expectations. Everything else earns its place later, or not at all.

Hypothesis

Teaching a local cohort to understand and build AI agents — two hours a session, in public, on a real system — will speed up my own iteration rather than slow it down, and will produce the first version of a team in my own town.

Three claims sit inside that, and each can fail on its own:

H1. Explaining a system to people without the vocabulary for it improves my own model of that system. Teaching is a compression test, not a detour.

H2. A cohort in Bhiwani / Hisar can produce build capacity I could not otherwise hire — the beginning of a team.

H3. Local businesses hold undocumented process worth encoding, and a town agent has a real user rather than a hypothetical one.

Load-bearing: H3. If there is nothing real to build, H1 and H2 have no substrate.

Actions

• Two free sessions on alternate days — 12 and 14 October. Visitors decide by the end of session 2, and register with the ₹500 application fee.
• Two hours per session. Ring-fenced. Not borrowed from #015.0.3.
• Bhiwani / Hisar. Software engineering ability assumed, AI knowledge not.
• Track A — Foundations. Career-beginners. Learn what an agent is, then learn to navigate the system being built. Building comes when they are ready.
• Track B — Build. Three to five years in. Own a piece and ship it.
• Track A reads what Track B builds. Track B explains it.
• Define the town agent as an opportunity, then build it — in the same session, in front of the cohort.
• One town. One business category. Depth over breadth.
• Log every day.

AI Agent Training Program — Bhiwani / Hisar (Curriculum)

Expectations