Product delivery apprenticeship · Jira + Confluence + AI
Build. Manage. Deliver. Grow a Product — Hands-On with Jira, Confluence & AI
3+ Week Live Project Mentorship for Business Analysts, Product Owners & Product Managers
PSPO 1 Certification Exam Pre-requisite · 3+ weeks · Jira, Confluence & AI
Don't just learn how to write requirements or manage a backlog. Build and operate a real product from problem discovery to MVP, roadmap, backlog, Sprint delivery, stakeholder feedback, release and product metrics — using Jira, Confluence and AI. One continuous live project for Business Analyst, Product Owner, and Product Manager capability — with the option to rejoin the next batch for free. Pre-requisite path for PSPO 1 exam prep.
- 3+ weeks · weekday live classes
- One continuous live product project
- Jira + Confluence + AI throughout
- Interview-ready product case study
Price, schedule & enrollment
- Price: ₹29,990 (India) · $499 (international)
- Duration: 3+ weeks
- Batch: 6 Oct – 26 Oct 2026 · Batch 1 · 7:00 AM–8:30 AM IST
- Batch: 6 Oct – 26 Oct 2026 · Batch 2 · 7:30 PM–9:00 PM IST
Key benefits
- Product thinking at the center — Agile and Scrum are the delivery context — you practice discovery, value, MVP, roadmap, and outcomes
- One continuous live project — An AI-enabled Employee Service Platform case — from ambiguous request to measurable delivery
- Jira, Confluence & AI as your systems — Use Jira as the delivery system, Confluence as the knowledge hub, and AI at each relevant stage
- Finish with a demonstrable case study — Not notes — an end-to-end product case you can defend in interviews
A product delivery apprenticeship — not a requirements lecture
Don't just learn how to write requirements or manage a backlog. Build and operate a real product from problem discovery to MVP, roadmap, backlog, Sprint delivery, stakeholder feedback, release and product metrics — using Jira, Confluence and AI.
The journey every cohort runs
Discover → Define → Prioritize → Build → Deliver → Measure → Improve. You take an ambiguous business problem, discover the need, define the product, create the MVP, build the backlog, prioritize work, manage stakeholders, plan releases, run delivery in Jira, document product knowledge in Confluence, use AI throughout the lifecycle, and finish with a complete product case study.
What you can expect
BA + PO + Product Manager capability in one continuous project: discovery and requirements, product vision and MVP, backlog architecture, INVEST and BDD, prioritization trade-offs, refinement and planning, stakeholder communication, metrics and quality, release readiness, and responsible AI copiloting. This is a non-certification course, with support to prepare for PSPO 1 or other certifications after training.
- 3+ weeks BA / PO / Product Manager mentorship · weekday cohorts
- 15 sessions Live weekday classes · ~1.5 hrs each (Mon–Fri)
- 4–6 Small cohort size for personal attention
Why this masterclass is different
Traditional learning teaches roles and features in isolation. This cohort asks you to discover a real problem, act as the PO, build a connected backlog, define an MVP, handle conflicting stakeholders, and finish with a demonstrable product case study.
BA + PO + Product Manager capability set
Learn discovery, requirements, backlog ownership, prioritization, strategy, MVP, roadmap, and product metrics — and the decision boundaries between these responsibilities.
Certification preparation and exam support
Strengthen product ownership knowledge and prepare for PSPO 1 with guided review and exam-oriented support.
Outcomes depend on participation, preparation, and exam eligibility; certification is taken separately.
Handholding and job support
Get mentor guidance, query support, and practical job-search help as you work toward a BA, Product Owner, or Product Manager role.
Hands-on Jira, Confluence & recordings
Practice backlog architecture, refinement, boards, JQL, dashboards, versions, and a Confluence product hub on your own system — with recordings to revisit.
Rejoin live sessions and the inner circle
Rejoin a future live batch at no extra cost and continue learning with the alumni inner-circle community.
Interview-ready product portfolio
Leave with a product case study, vision/MVP/roadmap artifacts, Jira backlog evidence, BDD stories, prioritization rationale, dashboards, and an AI use-case portfolio.
What you'll learn
What you will be able to do — translate ambiguous problems into product opportunities, operate delivery in Jira and Confluence, and explain a complete product case study in interviews.
- Translate ambiguous business problems into product opportunities
- Define Product Vision, Product Goal, MVP, and roadmap direction
- Build and maintain a high-quality Jira product backlog with INVEST stories and BDD acceptance criteria
- Prioritize work, explain trade-offs, and facilitate refinement and Sprint Planning
- Use Jira boards, workflows, JQL, dashboards, reports, and versions — plus Confluence as the product knowledge system
- Manage stakeholders, quality, risks, dependencies, and release readiness
- Measure product outcomes as well as delivery performance
- Use ChatGPT, Claude, and Rovo as product-management copilots with human validation
- Explain a complete, interview-ready product case study
3 weeks · 15 sessions of product apprenticeship
Week 1 turns an ambiguous business problem into product direction, MVP, and initial backlog. Week 2 turns intent into high-quality, prioritized, executable work. Week 3 operates the product through delivery, feedback, quality, measurement, and continuous improvement.
Week 1 · Session 1 — Business problem → product problem
Product vs project thinking, outcome vs output, problem framing, customers/users, stakeholders, assumptions and constraints. Create your Jira project and Confluence hub; use AI to challenge the problem statement.
- Problem framing and constraints
- Jira project + Confluence hub setup
- AI: challenge the problem statement
Week 1 · Session 2 — Customer & stakeholder discovery
Personas, jobs/needs, customer journey, pain points, stakeholder mapping, interview questions, and conflicting needs — with discovery evidence in Confluence.
- Personas, journeys, and pain points
- Stakeholder mapping and conflicting needs
- AI: synthesize evidence and challenge bias
Week 1 · Session 3 — Product vision, goal, value & outcomes
Product Vision, Product Goal, value proposition, business vs user value, outcome metrics, and success hypotheses — connected to Jira Epics/Features.
- Vision, Product Goal, and value proposition
- Outcome metrics and success hypotheses
- AI: critique vision and outcomes
Week 1 · Session 4 — MVP, release & roadmap
MVP vs prototype/pilot, MVP boundaries, release hypothesis, Now/Next/Later, outcome-based roadmap, and dependencies — using Jira Versions/Epics and Confluence roadmap pages.
- MVP scope and explicit exclusions
- Outcome-based roadmap and release hypothesis
- AI: challenge scope
Week 1 · Session 5 — Product backlog architecture
Epic → Feature → User Story → Task/Sub-task, plus Spikes, Enablers, Risks, Dependencies, and Defects — with full traceability in Jira.
- Backlog hierarchy and work types
- Create and link backlog items in Jira
- AI: detect gaps, duplicates, and oversized items
Week 2 · Session 6 — User stories + INVEST + story splitting
User voice, who/what/why, INVEST, vertical slicing, story splitting, and user vs system stories — created live in Jira.
- INVEST and vertical slicing
- Story splitting workshop
- AI: rewrite and challenge stories
Week 2 · Session 7 — Acceptance criteria + BDD
Given/When/Then, happy/alternate/negative paths, edge cases, business rules, testability, and traceability — with human-validated AI-generated scenarios.
- BDD acceptance criteria in Jira
- Edge cases and business rules
- AI generates candidates; you validate
Week 2 · Session 8 — Prioritization & trade-offs
MoSCoW, business/customer value, risk, urgency, dependencies, cost of delay, value scoring, and stakeholder trade-offs — implemented as priority/ranking in Jira.
- MoSCoW and value/risk/urgency scoring
- Stakeholder trade-off conversations
- AI: compare options
Week 2 · Session 9 — Backlog refinement + Definition of Ready
Refinement purpose, readiness, INVEST/AC/BDD review, dependencies, estimation readiness, and Ready/Not Ready facilitation in Jira.
- DoR and readiness checks
- Facilitate refinement in Jira
- AI as independent reviewer
Week 2 · Session 10 — Estimation, capacity & forecast
Fibonacci, relative estimation, capacity, velocity, Sprint Goal, Sprint Backlog, forecast vs commitment, release forecast, and scope/de-scope — using Jira Sprint + Version.
- Estimation, capacity, and Sprint Goal
- Release forecast and de-scoping
- AI: challenge planning assumptions
Week 3 · Session 11 — Stakeholder management & product communication
Influence, expectation management, conflict and negotiation, executive/team/customer communication, product demos, and Confluence decision context.
- Conflict, negotiation, and expectation management
- Product demos and decision records
- AI: prepare difficult conversations
Week 3 · Session 12 — Sprint execution, review & product feedback
Sprint Goal, PO participation in delivery, acceptance decisions, Sprint Review, feedback, backlog adaptation, scope changes, and defects — on the live Jira board.
- Acceptance and Sprint Review practice
- Feedback → backlog adaptation
- AI: synthesize product feedback
Week 3 · Session 13 — Product metrics, Jira dashboards & quality
Product outcomes, adoption, engagement, satisfaction, business value, velocity/predictability, cycle/lead time, defects, and a PO/PM dashboard with AI trend interpretation.
- Product + delivery + quality metrics
- Build a PO/PM dashboard in Jira
- AI: trend interpretation
Week 3 · Session 14 — Risks, dependencies, release & product ops
Risk probability/impact, owners/mitigation, dependencies, release readiness, version management, roadmap change, decision log, and Confluence product ops hub.
- Risk and dependency dashboards
- Release readiness and version tracking
- AI: challenge release risks
Week 3 · Session 15 — AI-powered PO/PM + capstone
ChatGPT, Claude, and Atlassian Rovo across discovery, requirements, prioritization, refinement, stakeholder communication, and metrics — plus responsible AI and the final product case presentation.
- End-to-end AI copiloting with human validation
- Responsible AI practices
- 10–15 minute product case study and decision defense
One continuous product — from discovery to measurable release
All major exercises connect to one product case: an AI-enabled Employee Service Platform. Teams progressively transform an ambiguous business request into product strategy, MVP, roadmap, prioritized backlog, release plan, and measurable delivery.
- Online live product project on every participant’s system
- Jira as the product delivery system + Confluence knowledge hub
- AI (ChatGPT, Claude, Rovo) at each relevant lifecycle stage
- Class recordings provided
- Non-certification course — take PSPO/certification after training
- Inner-circle community support after the cohort
Who benefits most
Built for people who must create measurable product value — not just document requirements. Real organizations combine BA, PO, and PM responsibilities differently; this cohort teaches the capability set and decision boundaries.
- Aspiring Business Analysts — Want discovery, requirements, process analysis, user stories, BDD, and acceptance criteria practiced on a live product
- Aspiring & practicing Product Owners — Need Product Goal, backlog ownership, prioritization, refinement, acceptance, and stakeholder collaboration — not slide theory
- Product Managers & product thinkers — Want market/customer discovery, strategy, vision, roadmap, MVP, value hypotheses, and product metrics with delivery evidence
- Career changers & returners — Moving into BA / PO / PM roles (including from non-IT backgrounds) and need an interview-ready product case study
Everything in your enrollment
- Online live product project on every participant's system
- Class recordings provided
- End-to-end product lifecycle: Discover → Define → Prioritize → Build → Deliver → Measure → Improve
- Jira as the product delivery system — backlog, boards, JQL, dashboards, and versions
- Confluence product knowledge hub and decision trail
- AI (ChatGPT, Claude, Atlassian Rovo) at each relevant lifecycle stage
- Stakeholder simulations and product decision practice
- Interview-ready product case study capstone
- Trainer support for queries for 3 months after completion
- Pay once, attend multiple batches (rejoin next batch free)
- Non-certification course — certification exam taken after training
- Inner-circle community for continuous support after the cohort
Learn with the mentor who runs every cohort
Dhirender Verma — SAFe Program Consultant (SPC), SAFe Authorized Trainer and Enterprise Agile Coach.
SPC · large-scale transformation consultant · Scrum/XP/SAFe trainer. Not sure this is your next step? Book a short call — role fit, cohort timing, and whether mock interviews or SAFe add-ons help your BA / PO / Product Manager goal.
Frequently asked questions
Fees & schedule
What is the fee for the BA / PO / PM Mentorship Masterclass?
₹29,990 for learners in India or $499 for international learners for the full live programme, including class recordings and free rejoin of the next batch. Instalment options appear at checkout where available.
What are the batch timings?
Live weekday classes of 1.5 hours over 3+ weeks. Next batch: 6 Oct – 26 Oct 2026 · Batch 1 · 7:00 AM–8:30 AM IST; 6 Oct – 26 Oct 2026 · Batch 2 · 7:30 PM–9:00 PM IST. Timings are shown in your local time zone on this page.
About the program
What is the BA / Product Owner / Product Manager mentorship program?
A 3+ week live product-delivery apprenticeship. You discover a real problem, define product direction and MVP, build and prioritize a Jira backlog, run delivery with stakeholder feedback, document decisions in Confluence, use AI throughout, and finish with an interview-ready product case study. Optional add-ons include SAFe certifications, mock interviews, and resume preparation.
How long is the program?
About 3+ weeks of intensive weekday classes (about 1.5 hours each, Monday–Friday) across 15 sessions, with the option to rejoin the next batch free.
Do I need prior experience or certifications?
No. The program accommodates beginners through experienced practitioners — including successful career switchers from non-technical backgrounds.
Is this a certification course?
No — this is a non-certificate mentorship/masterclass. Certifications (e.g. PSPO) are taken after training. SAFe certs can be enrolled separately.
What tools does the course use?
Practical activities are designed around current Jira Cloud, Confluence, and Atlassian AI/Rovo capabilities, plus ChatGPT and Claude. Exact screens and AI availability can vary by Atlassian plan and site configuration; where a capability is unavailable, an equivalent manual implementation can be used. The goal is capable product professionals — not tool dependency.
Delivery & support
How does the continuous live project work?
We help you set up a live Jira project and Confluence hub on your laptop. Every major exercise connects to one product case so discovery, MVP, backlog, delivery, metrics, and AI practice stay coherent — not disconnected drills.
What is the class size?
Intentionally small (about 4–6) for personalized attention: lectures, exercises, discussions, and project work.
Can I rejoin a future batch for free?
Yes. Pay once and you may rejoin a future batch at no extra cost. Trainer support for queries continues for 3 months after completion.
Do I get materials after the program?
Yes — recordings, course docs, templates, and your product portfolio artifacts stay available so you can review at your own pace. Alumni join the inner-circle community for ongoing support.
Enrollment
Do I need a schedule before checkout?
Yes. This offering is schedule-bound — select a cohort so your cart line carries the right batch.
Who teaches the sessions?
Dhirender Verma — SPC, large-scale transformation consultant, and Scrum/XP/SAFe trainer.
Can I change my batch?
Contact support if scheduling conflicts arise. Batch transfers are accommodated when seats allow — and rejoining the next batch free remains available.