Since launch, the iPad has seen several marketing thrusts to position it as a device that can ‘do a lot’ – primarily to counter the talk of it being merely for consumption of content. In May last year, Apple released the ‘Everything changes with iPad’ ad – ‘take on a new project, pick up a new skill, or start a new hobby’.
A key segment where the productivity aspect can be showcased is education. Apple has had a strong presence in US schools, though that is being challenged of late by the Chromebook. With iOS 9.3 announced earlier this month, Apple has tweaked the OS significantly to make it more school-friendly. A host of interesting features caught my eye: shared iPad for students, a new Classroom app, Apple School Manager, managed Apple IDs, students pick up where they left off, four-digit PIN on the Lock screen for younger students and more.
Of the lot, I found the multi-user support the most interesting. Apple has not allowed multiple profiles on a single iPad as yet. So this feature – albeit in schools could be rolled out to others in the future. While on the subject of education and apps, it is important to remember that this is a tough segment to cater to. Children can be the harshest of critics and getting the strategy and user experience right is doubly important when addressing this audience; Interesting developments ahead in the education section after the launch of iOS 9.3 – it will be a learning for the entire mobile app development ecosystem.
By Srinidhi Rao
RESOURCES
By Ivan Pinto
Most conversations about AI delivery focus on what the delivery partner brings to the engagement. The methodology, the toolchain, the engineering practice, the governance standards. We have written elsewhere about what Robosoft brings, and about the standard we have built ARIA around.
By Srinidhi Rao
Most organizations evaluating AI delivery partners are asking the wrong question. They tend to ask which tools a firm uses, when the question that actually matters is what standard the firm is operating to.
A tool is a productivity bump. A standard is what shapes whether the work compounds or stays flat. It is, in our experience, much of why AI projects fail to move past the productivity bump. Firms producing genuinely different outcomes with AI today are doing so because the same operating rules run through every decision, every gate and every phase of the work.
By Srinidhi Rao
The most consequential decisions in software delivery have always been made by people, and AI has not changed that. Deciding what a product should be, what trade-offs are acceptable, what is good enough to ship and what is not, these are human acts that require judgment and accountability. Intelligence can accelerate almost everything around them, but it cannot do them on its own.
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