Jobs to Be Done in AI: Stop Building Features, Start Solving the Job

AI products are changing faster than traditional product management playbooks can keep up. In this episode of the AI Product Management Podcast, we explore how the Jobs to Be Done (JTBD) framework can help product managers identify what users actually need—and avoid building AI features simply because the technology makes them possible.

The key question isn't “What can AI do?” It's “What job is the user trying to get done?”

We break down how to apply JTBD thinking to AI products, where conventional product discovery can go wrong, and how understanding the underlying job can lead to simpler, more useful, and more differentiated AI experiences.

• The AI Solutionism Trap — why starting with AI capabilities can lead teams in the wrong direction
• The Jobs To Be Done Lens — understanding the outcome users are actually trying to achieve
• How to Uncover the Job — practical ways to move beyond feature requests and surface the real user need
• Why AI Needs a Job — distinguishing genuinely valuable AI applications from technology looking for a problem
• From Job to Product — translating the desired outcome into product experiences, workflows, and AI capabilities
• Your New PM Playbook — using JTBD to make better product decisions in an AI-first world

Whether you're a product manager, founder, designer, engineer, or AI practitioner, this episode offers a practical way to think about AI product opportunities: start with the job, understand the outcome, and then decide where AI belongs.

AI doesn't automatically create value. Solving the right job does.

🎙️ AI Product Management Podcast
Ideas • Products • People • A Brighter AI Future

In this episode: