Efficient at what?
There seems to be an unspoken rule in modern work culture: everything must happen faster.
Emails arrive faster. Decisions are expected faster. Strategies are produced faster.
If you pause to think, somebody inevitably asks whether you're still working on it. Speed has quietly become one of the highest professional virtues.
Thoughtfulness, craftsmanship, and usefulness still matter. They simply seem to matter less than speed.
If you cannot move quickly enough yourself, don’t worry. There is now an entire industry ready to promise that artificial intelligence will do it for you.
Faster emails. Faster reports. Faster presentations. Faster thinking.
The assumption seems to be that more output automatically produces better outcomes.
The cult of speed
Speed used to matter in situations where time genuinely mattered:
- Emergency medicine
- Disaster response
- Firefighting
Most forms of knowledge work do not involve emergency conditions. Why do we behave as if every Slack message, every email, or every WhatsApp ping is a life-or-death situation?
People apologise for replying after three hours. Meetings are scheduled within minutes of a question being asked. Documents are rushed out simply so that something exists.
Speed has quietly stopped being a tool and turned into a cultural obsession.
The faster you move, the more productive you appear. The fact that the output may be mediocre is treated as a secondary issue and so we produce an endless stream of quickly assembled slide decks, shallow reports, and forgettable content.
The speed of production often becomes more important than the quality of what is produced.
The AI productivity fantasy
We now arrive at the latest chapter in this story: AI. AI tools are genuinely impressive. They can help with research, editing, coding, brainstorming, and plenty of other tasks.
The way they are being used says a lot about the culture they are entering, though.
Instead of asking how AI might help us think better, the dominant question seems to be: “How can we produce even more stuff even faster?”
People proudly demonstrate how they generated an entire strategy in five minutes or automated large parts of their communication.
What interests me most is the assumption behind the output.
Producing a strategy has rarely been the difficult part. Evaluating it, challenging its assumptions, and anticipating second and third-order consequences are where the hard work begins.
AI can accelerate production. It cannot outsource judgement.
When output becomes effortless, the value shifts to deciding what deserves to be produced in the first place.
The efficiency trap
The obsession with speed and automation hides a rather uncomfortable question.
Efficient at what? Efficiency is only valuable if the thing being produced actually deserves to exist.
Producing mediocrity faster does not make it valuable. It simply increases the volume of mediocrity. Many AI-generated outputs share the same strange characteristic. They look polished and sound professional, but they feel oddly empty.
Insight tends to emerge through exposure to different perspectives, careful observation, experience, and reflection.
Most of those things require time.
When speed becomes the goal
Speed becomes a problem when it becomes the primary measure of value.
A mediocre strategy delivered in an hour is still a mediocre strategy. A poorly considered decision made quickly remains a poor decision. Producing more content does not automatically produce more understanding.
The question is never how quickly something was created. The question is whether it improves the situation it was created to address.
Doing the work yourself
Another uncomfortable idea is that not everything should be automated.
Yes, AI can help, but sometimes the process of doing something manually is precisely where the value lies.
Writing often clarifies thinking. Research exposes assumptions. Design reveals constraints that are easy to ignore when discussing ideas in the abstract.
Outsourcing all of that thinking to tools may produce faster outputs, but it also produces shallower ones.
The craft quietly disappears and with it, much of the meaning of the work.
The bottleneck
The barriers to producing information have fallen dramatically. Insight still depends on judgement, experience, and careful thought.
Most of us can recognise the difference between work that was assembled quickly and work that has been thought through carefully.
Thinking takes time. Craftsmanship takes time. Understanding takes time.
The goal is not to reject technology or efficiency. The goal is to remain clear about what they are for.
Producing more has become easier. Deciding what deserves to be produced remains the hard part.