Living in fast forward

On a Monday in late spring, Samantha watched a week’s worth of marketing work unfold before lunch.

The pilot dashboard feeling new, clean, and a little too cheerful refreshed every minute. Concepts that would once crawl through a maze of meetings now propagated like ivy. Someone in the media team spun up a hundred audience variants while a data scientist nudged a model toward a tone that sounded “warmer, but still premium.” Copy options multiplied. Visual tests bloomed and died. The board filled with green checks and gray Xs. Samantha blinked and the day had jumped an hour. Blinked again and a quarter’s worth of iteration had happened inside the space of a morning.

This is what “temporal compression” feels like from the inside: the past still happening, the future already here, and the middle, where you used to catch your breath, thins to a tightrope. We will all be living in fast-forward. The reels that once took decades to change will splice new scenes into our roles in weeks and sometimes days. The old rhythm was generational. We would learn a craft, master a craft, and then pass it on. The new rhythm is a within-lifetime upheaval, and often within-role mutation. The question isn’t whether this will happen; it’s how we can meet it without losing ourselves.

Samantha’s team felt the shift through their calendars. The Tuesday brainstorm, once a ritual of markers and coffee rings, transformed into a 45-minute prompt lab. Instead of starting from anxious silence and a joke about “no bad ideas” instead they began with a wall of AI-generated “good enough” ideas. The work evolved from the old way: genesis to a new way: curation and improvement. The value slid from making something new to deciding what would be important and training the system to make more of these important things.

“Wild how fast this is,” someone said.

Samantha nodded. Wild wasn’t the whole word. The speed was a relief and also a threat. The cadence of her career which had been weeks to research, days to draft, a slow climb to consensus wasn’t just faster now. It was different.

When Centuries Became Seasons

For most of human history, new tools arrived on a scale of generations. A new agricultural idea might spread farm by farm over decades or even centuries. In Europe we called the beginning of this acceleration “the renaissance.” And then in the late 18th century, the industrial revolution. Both of these moments were about acceleration. Gas light gave way to electric light over a generation or two. Cars replaced horses over a single generation. Before the modern era a grandparent and a grandchild could do roughly the same work with roughly the same methods, and the identity tied to being a blacksmith, mason, weaver as well as the knowledge to do these jobs was steady enough to pass on from one generation to the next.

That rhythm has shortened from centuries to decades to years and now to seasons. You learn a tool in spring and, by autumn, it has quietly rearranged your workflow. By winter, your job title may be the same, but the way you create value has slid to a new place: into how you judge machine-generated outputs, how you frame the right questions, and how you connect human purpose to automated loops.

Add network effects and data feedback loops, and tools don’t just help with tasks, they reshape the tasks. Reporting becomes real-time dashboards and then transforms into specific insights and recommendations ; creating and writing becomes reviewing and editing; research becomes asking; programming becomes orchestrating agents. The center of gravity moves from “doing the thing by hand” to “specifying, supervising, and improving the thing” as it’s done by increasingly capable systems.

The result is a shift in where your value lives. Less in memorizing procedures; more in problem framing, constraint setting, ethical judgment, verification, and integration. These are the skills that will travel well as the underlying tools keep changing. Roles used to be fixed bundles of tasks. Now the bundles re-sort themselves every few months, and the people who thrive are the ones who can keep adapting to the rebundling.

Adoption Time Is Shrinking (and Why That Rewrites Work)

When Samantha’s company trialed their “BrandGPT,” the plan was three months of cautious pilots. By the end of the first month, teams in three regions had quietly routed everyday tasks through it. By the end of the second, creative, CRM, and media were sharing a single prompt library. By the end of the third, the VP who’d asked for a “small proof of concept” was asking why every team wasn’t already there.

Reducing time to adapt doesn’t just speed up deliverables it requires a rewiring of our institutions. It is a mistake to just think of generative AI as automating tasks. There is a more fundamental change occurring. You might feel it in the texture of meetings: decisions moved from “what’s your opinion?” to “what did we learn?” The new system provides options, scores, traces and shifts work from individual contributors to a continuous conversation through coordinating a combined team of humans and machines.

Stability as Liability

It may be that like Samantha your “superpower” has been the human stuff. Things like reading the room, hearing the unfinished story, noticing the small dignity in how customers described themselves. In an AI-integrated workflow, taste alone, unarticulated, isn’t a strategy. The system needs to be trained on specifics. It needs to be fed data over and over to train it to know “What did you mean by better?” “Which variable moved?” “What should we reward next time?” Systems need specifics. They learn from examples, criteria, and feedback loops not from vibes.

In that context, “I know it when I see it” leaves value on the table. The work had not become heartless. This is what is called “tacit knowledge.” But for it to become valuable in this new world it has to become explicit. The old stability becomes a liability if it can’t be expressed as teachable criteria. This doesn’t make the work heartless. It is about how you translate the heartfelt part into teachable pieces so that it will scale.

Your human judgment is still the engine. The upgrade is making that judgment legible so you can teach it to teammates and tools, audit it, improve it, and scale it. In this world, compassion, discernment, and taste don’t disappear; they become datasets, rubrics, and feedback loops and that’s how your superpower multiplies. That is the new bargain. Your value doesn’t vanish. It migrates into how quickly you can convert tacit knowledge into explicit signal.

Second exercise

One of the key things you will need on this journey is to have a set of AI tools at your disposal to test out your ideas and learn more about what is possible. Start with free versions of the tools but also understand that free versions will be limited by comparison to paid versions. This exercise will help you understand some of these choices by having you do three tasks with three AI models and record the results:

Click for Exercise 2: Three Initial AI Tasks

• The exercise will record your results in your journal (you must be registered and logged in)
• You’ll run 3 tasks without trying to perfect them: Summarize a long article, Draft an email/text message, Plan something real (trip, meal plan, schedule)