Beyond brainstorming: how AI is reshaping innovation work
What AI has already commoditised in innovation work, why loading context matters more than writing a clever prompt, and a live run of one brief through competing models to find the disagreement worth paying attention to.
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Why knowing your customer still isn’t enough
Why most customer understanding still leaves teams guessing. A practical introduction to JTBD, job mapping and turning vague customer pain points into opportunities precise enough to build against.
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Jobs to Be Done Template
The most-used JTBD template on Miroverse. Four stages, from scoping the job to a full outcomes library, with an AI Flow that turns interview transcripts into structured evidence and a worked example throughout.
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Why segmentation keeps producing the same roadmap
Colin and Rory Keddie of Miro on why segmentation and feature requests keep producing the same roadmap, and what changes when a team organises around the job customers are actually trying to get done.
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Selling Jobs to Be Done
JTBD often stalls before the research starts because somebody hasn’t bought the premise. How to make the case internally, win over sceptics and stop it being dismissed as another research technique.
Watch the webinar →Why good innovation ideas die inside big companies
Why good ideas stall inside large organisations, and what to do about it: a practical case for small wins and removing decision friction rather than running another round of ideation.
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Transforming your company’s culture
The practices that separate companies who talk about innovation from the ones who get things into market: how to get beyond innovation theatre, and build a culture that works rather than just performs.
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How AI is redrawing the consulting price list
A Fortune 100 client asked every consultancy on its roster to justify its rates in an AI world. The three things that moved upstream: framing the problem, reading disagreement, deciding what deserves resource.
Read on Miro →Where breakthrough insights actually come from
Challenging the norms of a category, going after the segments everyone else has written off, and why qualitative work earns its place alongside the numbers.
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What happens when you put AI inside a JTBD workflow?
We rebuilt our 8,000-user JTBD template around AI. Here’s what we automated, what we deliberately didn’t, and why traceable evidence matters more than faster output.
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