Danielle Rosenthal

Practice

A few things I’ve learned

  1. When code gets cheap

    The part that doesn’t get cheaper

    As AI makes building software cheaper, the advantage moves to deciding what to build and settling the open questions around it. The teams that move fastest bring a proposal to each of those questions.

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  2. When no-code isn’t

    Business users are experts at their own subject

    The person configuring a no-code tool is usually already an expert in her own subject. The tool works when it asks about that subject in her words and leaves the engineering to the system.

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  3. Modeling a person

    Our users do not arrive in their best state

    I’ve learned a great deal from psychology that product and design teams can use. The most useful part so far is that people move between states, while our words for them describe traits.

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  4. Teams

    Capacity comes before capability

    As humans we like to think we have an unlimited capacity for good things. However, experience and research shows our nervous systems disagree.

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  5. Designing for misuse

    Close the pathway

    Most misuse runs through steps a product already allows, taken from an ordinary account. Changing one of those steps can make the whole route stop paying.

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  6. Why people don’t use it

    What was in the way

    People use a system when the team behind it understood what stands between them and the safe way of working. The answer is rarely on the roadmap.

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  7. How people actually use software

    Designing for humans

    Good design starts from how people actually meet software, in the middle of a busy day with whatever attention they have left.

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  8. The mechanism

    Who carries the complexity

    Every feature comes with some complexity, and somebody ends up holding it: the product team, the engineering team or the person using the software. The best products leave as little of it as possible with the person.

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  9. The second product

    A customer is not a product

    To have a seamless experience across a portfolio of products, it’s important that the data model represent the full complexity of what’s possible, as early as possible.

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  10. Information software

    The view is the product

    In software where people read, scan, compare and decide, the arrangement of the data is the product.

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  11. On AI, and tools generally

    Power-ups don’t pass levels

    AI is a power-up, and it’s still the player who passes the level.

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  12. Keeping users safe

    What your users are up against

    Your users need to be safe while they use your product. The people who know best what could harm them are the ones who have already been burned.

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  13. On shipping

    Thyme to market

    Whoever ships first gets paid to learn from real buyers. I’ve learned that a launch usually loses to somebody who sold a rougher version to the same buyers first and used the money to catch up.

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