AI context systems for BAs & POs

This workshop is about the context layer — the part that decides whether AI output is usable or just fluent.
Skip it, and you get specs that are polished on the surface and empty underneath: generic phrasing, invented fields, rules your product never had.
Overcorrect — "just give it all the context" — and it's worse. Do you even have all the context in one place? Would you want every Confluence page, every PRD revision, every deprecated business rule shaping the answer?
The usual fixes all carry a bill:
RAG pipelines — powerful, but now you build and babysit infrastructure.
Mega-prompts — thorough, but every answer comes out diluted.
Docs dumps — comprehensive, but light on the specifics that matter.
Letting AI manage its own context — convenient, right up until it takes the wheel.
This workshop gives you a Context Engineering system that costs the least to start and grows with your product.
You leave with a working starter context base, your own agents.md, your SKILL.md files, one real feature specced end to end — and a system you shape as you go, not a framework you serve.
I spent years sharpening this. Now it saves me days.
Engineer a compact context system that turns a four-line brief into a spec draft your team trusts — on your product, in your template.
Decompose any requirement into the context blocks an AI can address — users, data, workflows, processes, domain, business rules
Separate context-dependent quality (valuable, testable, relevant) from prompt-dependent quality (unambiguous, readable)
Diagnose why a "complete-looking" spec is actually hollow
Construct the addressable folder structure your AI reads from
Teach the AI to maintain the content itself, so they never go stale.
Compose a `SKILL.md` and your own `agent.md` that turn the context base into a working system
Lock the AI to attributes it can actually see — no invented fields, no hallucinated rules
Promote new business rules, user groups, and entities from each ticket back into the base — without bloating it
You'll leave able to tune and rebuild this system for any product you own
Join 5 minutes before to say "Hi" and set up for the session.
Share the use case you're bringing! That will be the foundation for the whole session.
Tools + the LLM you already use, wired and ready. → You leave with: a working setup — no "install later," you build today.
Rules for context management applied to requirements. → You leave with a solid understanding of why this set up works
Align on what makes a requirement good, then dissect a real one together. → You leave with: the quality split — what a better prompt fixes vs. what only context can.
Build the addressable base + the extraction skill, live. → You leave with: your own agents.md + extraction SKILL.md, running on your product.
30 min break
Turn a four-line brief into a spec draft the model grounds in your base. → You leave with: a draft skill + template that drafts specs from your context
Promote new rules, roles, and entities from the draft back into the base. → You leave with: the flywheel skill that keeps your context alive without bloating it.
Bring the example that didn't fit — we work it live. → You leave with: your stuck case unstuck, and the pattern to rebuild this for any product you own.

AI-assisted requirements engineering | 15 yrs PM in Banking, Aviation, MedTech

You're a Business Analyst or Requirements Engineer who owns product documentation, and you want a system for AI-assisted requirements work
You're a Product Manager or a PO who needs AI as a specification sidekick, not a chatty assistant you re-brief from scratch on every task.
You've tried "shove all the context in" — and watched the output get more generic, not less. Ready for a tested framework that fixes it.

Live sessions
Learn directly from Illia Shapoval in a real-time, interactive format.
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8am–1pm EDT