Institutional AI engineering workshop · Team path
Workshops that turn AI engineering into shared practice.
For colleges, schools, bootcamps, and engineering teams that need a scoped two-day program with shared language, exercises, artifacts, and review.
VS Code
OpenAI
Microsoft- Price
- INR 2L–5L
- Support
- Workshop
- Fit-check
Fit-confirmed support
Workshop
INR 2L–5L
quoted after scoping
Decision lens: Choose workshops only when a group needs a shared operating language and participant artifacts, not individual course access.
Current status: Institutional scoping only
Ready now: A 2-day agenda is drafted after a no-cost scoping call; on-site delivery outside Jodhpur requires separate travel and lodging.
No automated checkout: WhatsApp fit-check before payment.
Fit audit
Before choosing Workshop, compare the support surface.
The right support path is not the most expensive path. It is the smallest support layer that changes the work you can finish, review, and explain.
Read first: The public syllabus stays available without signup, email gate, checkout, or login.
Choose optional support only if it changes output: An optional support path must improve the learner artifact: repository, demo, roadmap, project review, or workshop output.
No outcome promise: The page may describe support and proof, but not placement, salary, hiring access, or hidden partnership claims.
Public proof
Stay public if reading is enough.
Use the 20 lessons, blog, glossary, and reading paths first. Do not pay before you know what support would change.
INR 0
Lower layer
Architecture Review may already be enough.
If Architecture Review can produce the needed proof outcome, start there instead of overpaying for founder time.
INR 24,999
This path
Workshop changes one specific layer.
A college, school, bootcamp, or engineering team with 20-60 participants and a clear AI-engineering capability goal. Proof outcome: Custom agenda, participant workbook, command sheets, working-session artifacts, and post-workshop review call.
INR 2L–5L
Scoping route
Compare before committing institutional budget.
For institutional work, the next step is a scoped conversation, not a checkout flow or generic fixed-plan claim.
Fit call
Operating model
Workshops work only when an institution needs shared practice.
This path is for colleges, schools, bootcamps, and engineering teams that need a scoped 2-day program, not an individual learner checkout.
No support path is sold as magic. The learner or institution brings context, ABCsteps provides the support surface, and the final standard is inspectable proof.
Input
What you bring
Bring audience size, current skill level, target outcome, delivery mode, date constraints, and any academic or team requirements.
Fit-check
What gets confirmed first
The scoping call confirms audience fit, module mix, travel or remote needs, and whether the workshop should proceed at all.
Delivery
How support is delivered
Delivery runs through a custom agenda, workbook, command sheets, two full teaching days, and a post-workshop review call.
Proof
What should exist after
The outcome should be a custom agenda, participant workbook, working-session artifacts, and institutional review notes.
Stay lower if
Architecture Review already solves it.
Do not choose Workshop if Architecture Review can already create the proof outcome you need.
Choose this if
Workshop changes the artifact.
Choose this path only when it improves the expected proof outcome: Custom agenda, participant workbook, command sheets, working-session artifacts, and post-workshop review call.
Scope carefully
Institutional budget needs scope.
For workshops, the next responsible step is a scoped conversation, not a generic checkout or vague institutional claim.
What changes in practice
Workshops make AI engineering visible for a whole group.
The institutional path should feel scoped, not generic. It starts from audience level and goals, then turns AI tools, code, cloud, and delivery into a shared practice session with inspectable participant output.
Decision lens: Choose workshops only when a group needs a shared operating language and participant artifacts, not individual course access.
Audience design
The agenda changes with the room.
A school, college, bootcamp, and engineering team do not need the same workshop. The module mix is scoped before dates are locked.
Working lab
Participants touch tools, not just slides.
The session can cover editor workflow, AI pair assistance, command sheets, lightweight cloud demos, and practical debugging routines.
Institutional proof
The institution receives artifacts.
The output should include a custom agenda, workbook, command sheets, working-session artifacts, and a post-workshop review.
Before you message
Make the first WhatsApp message useful.
The fastest enrollment conversation is not a sales call. It is a fit-check with enough context to decide whether the public syllabus is enough, or whether Workshop will actually change your output.
This is still a static page: no form, no checkout, no account, no hidden learner database. Send the context directly on WhatsApp only when you are ready.
01 · Level
Audience starting point
Share the institution or team context before discussing dates, delivery mode, and the support scope.
Send: institution/team name, audience size, skill level, target outcome, and location or remote preference.
02 · Time
Delivery runway
Institutional delivery depends on calendar, audience size, delivery mode, and decision owners.
Send: preferred dates, remote/on-site choice, audience count, and who will approve the workshop.
03 · Proof
Target workshop output
Name the participant output: workbook, command sheet, working-session artifact, or institutional review note.
Send: the participant artifacts and institutional outcome expected from the two-day workshop.
04 · Boundary
What you expect from support
Be clear if the need is a one-off workshop, a longer institution program, or a team enablement session.
Send: whether this is a one-off workshop, semester program, or team training conversation.
Current delivery
Choose only when this delivery solves the need.
These pages state what can be delivered now, who the right-fit learner or institution is, and what proof should come out of the engagement.
Current status
Institutional scoping only
Ready now
A 2-day agenda is drafted after a no-cost scoping call; on-site delivery outside Jodhpur requires separate travel and lodging.
Right-fit learner/team
A college, school, bootcamp, or engineering team with 20-60 participants and a clear AI-engineering capability goal.
Proof outcome
Custom agenda, participant workbook, command sheets, working-session artifacts, and post-workshop review call.
Value split
What the support changes.
Every support path must earn its price by changing the learner's work, institution output, or project decision, not by hiding the syllabus. Use these four checks before choosing this path.
Ready now
Current delivery is explicit.
A 2-day agenda is drafted after a no-cost scoping call; on-site delivery outside Jodhpur requires separate travel and lodging.
Support value
The fee buys guided support.
A custom 2-day intensive for institutions — colleges, schools, engineering teams. Modules tuned to the audience and stack.
Proof outcome
The engagement must leave evidence.
Custom agenda, participant workbook, command sheets, working-session artifacts, and post-workshop review call.
Fit guard
This support path is not for everyone.
Individual learners — the learner support paths above are designed for individuals
Best for
- Colleges (BCA / B.Tech / MCA) building practical AI / cloud capability in their CS department
- Schools introducing senior students (class 11-12) to AI-native engineering
- Engineering teams at companies onboarding to a new stack
- Bootcamps and finishing schools that need a guest senior instructor for a 2-day intensive
Not the right fit if
- Individual learners — the learner support paths above are designed for individuals
- Audiences below class 9 — the curriculum is calibrated for higher secondary and above
What you receive
Included with Workshop
2 full days of structured teaching (16 hours total) — on-site or remote
Custom module selection from the ABCsteps curriculum based on audience
Pre-engagement scoping call to understand the cohort and goals
Workbook and command sheets for every participant
Post-engagement review call with the institution lead
Honest exclusions
- Travel and lodging (if on-site outside Jodhpur) is billed separately
- Ongoing curriculum delivery is a separate engagement (we discuss it after the workshop if there is fit)
Delivery proof
What this support path actually helps you practice.
The support path is useful only if it turns study into inspectable work: repositories, demos, review notes, deployment decisions, and project explanations.
Tool and platform logos are context references only: no affiliation, endorsement, interview access, hiring promise, salary promise, or placement guarantee.
Shared workspace
Participants learn one operating language.
The workshop aligns learners around editor workflow, AI assistance, and small code changes they can inspect together.
Cloud lab
Demos become reachable.
The delivery can include a lightweight deployment or tunnel path so participants understand localhost versus public demos.
AI literacy
Teams separate product claims from tool reality.
The AI layer is taught through provider boundaries, enterprise context, and realistic limits rather than hype.
How a typical engagement runs
From enquiry to outcome.
- 01
Initial enquiry
Email or WhatsApp the institution / company name, audience size, current skill level, and what outcome you want from the workshop.
- 02
Scoping call (45 min)
A no-cost 45-minute call with the institution lead to understand the audience, agree on module mix, and confirm dates.
- 03
Custom curriculum draft
A 2-page draft of the 2-day agenda, with the modules selected, time allocation, and the working artefact each participant will leave with.
- 04
Workshop delivery
Two full days, 8 hours each. On-site (anywhere in India) or remote via video. Workbook and command sheets distributed at start.
- 05
Post-workshop review
A 30-minute review call with the institution lead one week after, to capture feedback and discuss any follow-on engagement.
Honest answers
FAQ
What audience sizes do you work with?
20–60 participants per cohort works best. Beyond that, we either split into multiple cohorts or scope a different format.
Are you NEP 2020-aligned for schools?
For higher secondary (class 11-12), the agenda can be mapped to NEP 2020 skill-development language during scoping. The institution should review and approve the final academic alignment before announcing it publicly.
Can you cover topics outside the standard ABCsteps curriculum?
Yes, within reason. The standard modules are AI tools, cloud foundations, DevOps practice, and full-stack basics. Anything beyond that, we discuss in the scoping call.
What is the price range?
Use INR 2L-5L as the planning band, not a checkout price. A remote 2-day workshop with up to 30 participants starts near the lower end; on-site delivery, larger cohorts, or custom curriculum work move higher. Travel and lodging are quoted separately for on-site work outside Jodhpur.
Do you offer ongoing curriculum delivery for colleges?
Possibly. After a successful workshop, we discuss whether a longer engagement (one semester, with weekly contact) makes sense for your institution.
Decision gate
Decide from fit, not urgency.
These support paths use real founder time. The right answer is sometimes to keep using the public proof layer, sometimes to ask one focused question, and sometimes to choose the support surface.
Choose only if
This support changes the work.
Choose Workshop only when the support surface helps you produce the proof outcome: Custom agenda, participant workbook, command sheets, working-session artifacts, and post-workshop review call.
Stay lower if
A lower path already solves it.
Individual learners — the learner support paths above are designed for individuals
Ask first
Fit is confirmed directly.
Send the page you read, the blocker or goal, and the outcome you expect. The next step can be reading, one question, or enrollment.
Direct fit-check
Message or call Divyanshu when this support would change the work.
Every support enquiry is intentionally human-confirmed: a short WhatsApp conversation matches the learner, founder time, and expected proof outcome before any payment step.