Jobs to Be Done
A framework that defines customer needs as functional, emotional, and social jobs people hire products to accomplish. It shifts focus from demographic segments to the underlying progress customers are trying to make in specific circumstances.
Jobs to Be Done (JTBD) reframes product thinking around the outcomes customers seek rather than the features they request. Instead of asking what users want, you ask what progress they are trying to make and what obstacles stand in their way. This prevents building features nobody needs and keeps the team aligned on genuine customer value.
In AI product development, JTBD is especially powerful because it helps teams avoid the trap of shipping AI for its own sake. Rather than adding a chatbot because competitors have one, you identify the job: perhaps users need to quickly surface insights from large datasets. That job might be best served by an intelligent search feature, an auto-generated summary, or a conversational interface. JTBD keeps the conversation grounded in outcomes, which makes prioritization clearer and experiment design sharper for growth teams iterating on AI features.
Related Terms
Product-Market Fit
The degree to which a product satisfies strong market demand. Achieving product-market fit means customers are actively seeking, using, and recommending your product because it solves a real and pressing problem for them.
Minimum Viable Product
The simplest version of a product that can be released to test a core hypothesis with real users. An MVP delivers just enough functionality to gather validated learning while minimizing development time and cost.
Minimum Lovable Product
An evolution of the MVP concept that emphasizes delivering enough quality and delight that early users genuinely love the product. It balances speed-to-market with the emotional engagement needed to drive organic word-of-mouth growth.
Design Sprint
A five-day structured process for rapidly prototyping and testing ideas with real users. Developed at Google Ventures, it compresses months of debate into a focused week of mapping, sketching, deciding, prototyping, and testing.
Lean Startup
A methodology for developing businesses and products through validated learning, rapid experimentation, and iterative releases. It emphasizes reducing waste by testing assumptions before building fully-featured solutions.
Build-Measure-Learn
The core feedback loop of the Lean Startup methodology. Teams build a small experiment, measure how users respond with quantitative and qualitative data, then learn whether to iterate, pivot, or scale the approach.