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Instead of asking customers to evaluate 50 options, use AI as a "BS layer detector" to identify the top three contenders. This saves time and budget by focusing human-led research on a pre-vetted, smaller set of choices for final validation.

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Instead of immediately seeking interviews, founders can build an AI persona of their ideal customer. By feeding it documents and archetypes, they can rapidly query the persona to test value propositions, pricing, and features, compressing months of traditional customer discovery work into days.

The goal isn't to build one perfect prototype quickly. The real strategic advantage of AI tools is the ability to generate three or four distinct variations of a feature in a short time. This allows teams to explore a wider solution space and make better decisions after hands-on testing.

Instead of asking AI for a final answer, use it as a sophisticated focus group. Prompt it to embody different customer personas (e.g., "a left-leaning feminist," "a conservative male") and provide feedback on your messaging from those perspectives. This helps refine copy before market testing.

Go beyond using AI for data synthesis. Leverage it as a critical partner to stress-test your strategic opinions and assumptions. AI can challenge your thinking, identify conflicts in your data, and help you refine your point of view, ultimately hardening your final plan.

To avoid generic brainstorming outcomes, use AI as a filter for mediocrity. Ask a tool like ChatGPT for the top 10 ideas on a topic, and then explicitly remove those common suggestions from consideration. This forces the team to bypass the obvious and engage in more original, innovative thinking.

AI can generate hundreds of statistically novel ideas in seconds, but they lack context and feasibility. The bottleneck isn't a lack of ideas, but a lack of *good* ideas. Humans excel at filtering this volume through the lens of experience and strategic value, steering raw output toward a genuinely useful solution.

Instead of adopting AI as a simple tooling exercise, identify where decision-making is slow or fragmented. For instance, during planning, AI can synthesize inputs and draft reports. This elevates product teams from low-value "busy work" to high-value strategic debate and tradeoff analysis.

The best use for AI-generated customer personas is for early-stage concept validation, not initial need-finding. Use them to quickly screen many potential solutions before validating the most promising ones with real people. This speeds up innovation and keeps ideas confidential from competitors.

AI tools can drastically increase the volume of initial creative explorations, moving from 3 directions to 10 or more. The designer's role then shifts from pure creation to expert curation, using their taste to edit AI outputs into winning concepts.

Top performers don't use AI to produce more mediocre documents. Instead, they use the time saved to go deeper—aggressively interrogating AI output, fixing underlying logic, and having critical strategic conversations they previously skipped. This transforms generated 'slop' into exceptional work.

Use Generative AI as a Filter to Narrow Options, Not to Make Final Decisions | RiffOn