The Age of Imagineering

What happens when a laboratory can use the results of one experiment to help decide what to try next? In this episode of The Age of Imagineering, Justin Thompson explores how scientists are connecting AI, robotics, and laboratory equipment to test ideas and learn from the results.

From a mobile robot that ran 688 experiments in eight days to newer systems that help plan and carry out chemistry tasks, these early examples offer a glimpse of how discovery could change. We look at what’s already been demonstrated, why reliable measurements and human judgment remain essential, and what it could mean if more worthwhile scientific questions got a serious test.

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What would more healthy time make possible for you?

Justin Thompson grew up in a medical family and lost his father to pancreatic cancer. That history shapes his hope for what AI could help medicine achieve.

This episode follows the work from an overlooked pattern in DNA, to computer-designed molecules tested in a lab, to an early clinical trial. What have researchers actually learned? What still needs testing? And how do we make sure a breakthrough reaches the people waiting for it?

A conversation about better questions, careful evidence, and the families at the other end of scientific progress.

Read the essay and subscribe: https://ageofimagineering.com/articles/whats-coming-for-medicine

You've spent years learning the work. You know where the software gets in the way, which exceptions matter, and what would make a genuinely useful tool.

In this episode of The Age of Imagineering, Justin Thompson explores what changes when that experience can help shape the software itself. An imaginary accountant's invoice-review tool shows how a rough idea becomes something worth testing, how a colleague makes it better, and why good judgment still matters at every step.

What is the software you wish existed because you know the work well enough to see what's missing?

Read the essay and subscribe: https://ageofimagineering.com/articles/the-software-you-wish-existed

An AI tells you a factory machine is about to fail. It recommends shutting down the line. What would you need to know before you trusted it?

Through this imagined decision, I explore how we test AI against reality. We look at past failures, ordinary days, false alarms, and the possibility that a model has already seen the answer. As AI gains the ability to act, the work of earning trust becomes more important.

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What have you been saving for later because you didn’t think you could make it real?

In this opening episode, I explore what changes when more people can follow an idea far enough to try it. We start with the excitement of building something, then follow it into ordinary life: a small business, a laptop that closes a little earlier, and more room for the things that matter.

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What would have to be true before you let an AI spend money and arrange real work in your name?

An imagined neighborhood courtyard project takes us through the questions behind dependable AI: what it needs to know, what we’ve given it permission to do, and how we establish that the work is actually finished. The goal is a place for people to sit together. Getting there reveals how much we still need to build.

Follow the show, read the essays, and subscribe at https://ageofimagineering.com/