A founder-focused workshop on using AI as product strategy infrastructure: not just as a content tool, but as a way to test product assumptions, simulate stakeholder feedback, and sharpen early product direction.

Context

Delivered at The Collective AI: Hacker House Bali, the session trained founders on prompt building and product strategy methods for working backwards from market, user, investor, and operator perspectives.

Approach

The workshop showed how LLMs can be used to impersonate key stakeholders in the product process, including prospective users, advisors, investors, internal operators, and domain experts. Participants explored how mock user data, synthetic interviews, and AI advisory councils can help pressure-test product concepts before expensive build cycles.

Frameworks and Tools

• Persona Builder: using AI to synthesize research-grade persona cards and role-play stakeholder feedback.

• Gap Finder / Investor Lens: comparing today’s product state against a stronger six-month vision, then ranking the highest-leverage gaps.

• Futures Coach: mapping first-, second-, and third-order consequences of product decisions, features, pricing changes, and market shocks.

• Working backwards from facts, skills, and individuated meaning toward product clarity, founder judgment, and creative strategy.

Outcome

Founders responded strongly to the workshop because it changed how they thought about product development: AI became less of a shortcut for output and more of a thinking partner for strategy, feedback, and decision-making.