Learn how to discover AI use cases, shape AI products, write better requirements and create AI-ready backlogs — without needing to code.
Sunday session · date coming soon
POs · BAs · Delivery Leads · Scrum Masters · Product Managers
No theory, no hype — register interest and we'll confirm pricing
Date coming soon · Start with the free 60-min taster · No coding required
"By the end, you'll know how to take a business problem and turn it into an AI-ready product backlog."
Not "what is AI?" — but how to do PO and BA work in the AI-native world.
LLMs, RAG, agents, automation, confidence scores, human review — what these mean for product teams and why they change how you write requirements.
Good use cases, bad use cases, risky ones. Move from "we need AI" to a specific, justified problem AI can actually solve.
The core mindset shift: writing requirements when outputs are probabilistic, not deterministic. Cited sources, fallback behaviour, audit trails, human escalation.
Personas, journey map, epics, user stories, acceptance criteria, NFRs, risks, MVP scope and test scenarios — all from a single business problem.
Enough vocabulary to collaborate confidently: RAG, prompts, agents, guardrails, hallucination, evaluations, privacy. Not deep technical — just the right questions.
Where human review is non-negotiable. Privacy, bias, data quality and safe use — the things your stakeholders will ask about.
Minimal slides. Maximum doing. Each part builds on the last.
What is different when a product uses LLMs, RAG, agents or automation. Why outputs are not guaranteed. Why human review, confidence and fallback behaviour matter — and how that changes your artefacts from day one.
How to spot good, bad and risky AI use cases. A simple framework for moving from "we need AI" to a clear, justified product opportunity — with the right scope and the right questions for your stakeholders.
The core mindset shift. Instead of only writing "the system shall return the correct answer," you now need to think about:
Take one business problem. With AI as your assistant, produce the full artefact set: problem statement · stakeholder map · user personas · journey map · epics · user stories · acceptance criteria · NFRs · risks · MVP scope · test scenarios.
Enough vocabulary to ask better questions and collaborate confidently: RAG, prompts, agents, model selection, evaluations, hallucination, guardrails, cost, observability, privacy and security. Not deep technical — just enough to be useful.
Take a real business problem and leave with:
problem statement · stakeholder map · user personas · journey map
epics · user stories · acceptance criteria · NFRs
risks · MVP scope · test scenarios
Learn how to shape AI products, write AI-ready epics and manage backlogs for AI-enabled systems.
Understand how AI changes requirements, process mapping, acceptance criteria and stakeholder communication.
Know what AI-native products demand from your team and your delivery process.
Go from "we should use AI" to a justified, scoped, deliverable product opportunity.
Sunday workshop · 3 hours · Date coming soon · Register your interest and we'll confirm everything by email
Questions? ai@chocolateminds.com
Haven't seen the free taster yet? Start with the free 60-minute session — see the approach before you commit.
AI Lead & Educator | London
Madhusudhan trains product teams, business analysts and developers to work effectively in the AI era — practical skills, clear thinking and human judgement where it matters.
With 20+ years of software experience he bridges the gap between business and engineering — helping POs and BAs write better requirements, ask better questions and build better AI products.