No More Collaboration

Let’s be honest. “Collaboration” is one of those words that sounds noble but often masks inefficiency. In reality, it frequently means smart people get bogged down, their pace dictated by the group’s average, not their own potential. Meetings, alignment, consensus-building – necessary evils, perhaps, but evils nonetheless when they slow down real work. The cost of collaboration is often a tax on the most productive.

Software developers stumbled upon a better model decades ago: “low coupling, high cohesion.” Build modules that do one thing well and are self-contained (high cohesion). Ensure these modules interact through clean, simple interfaces, minimizing messy dependencies (low coupling). This isn’t just good for code; it’s good for getting anything complex done.

AI now offers the chance to apply this principle to organizations at a scale never before possible.

Think of AI systems not as a single monolith, but as a collection of highly specialized agents. One AI for deep market analysis, another for generating surprisingly good first drafts, a third for handling 90% of customer inquiries. Each is a highly cohesive unit, tasked with a clear job. Their “collaboration” happens through APIs and data feeds – efficient, machine-to-machine, no tedious meetings required.

The implication is revolutionary: a vast amount of what we previously had to call “collaboration” simply evaporates. The need for large teams to painstakingly coordinate every step of a complex workflow diminishes. Instead, smaller, highly-skilled human teams can direct and integrate these powerful AI agents.

So, what’s left for humans? The interesting stuff. The strategy, the truly novel problem-solving, the ethical oversight, the creative leaps that AI (at least for now) can’t manage. We move from being players on the field, often getting in each other’s way, to being the coaches and game designers. We define the “what” and the “why” at a higher level, and increasingly, AI handles the “how.”

Of course, this isn’t a panacea. An army of poorly understood, black-box AI agents can create its own kind_of_ nightmare – a new form of unmanageable complexity. The point isn’t to just throw AI at problems, but to consciously design AI-native systems that embody that LCHC ideal, making them more agile and robust.

Ultimately, AI provides a path to radically more efficient ways of working. It allows us to strip away the friction and overhead of much traditional human-to-human “collaboration,” freeing up our best minds to focus on what truly matters. It’s not about avoiding people; it’s about enabling peak performance and making the necessary interactions far more meaningful and productive.

This is less about “no collaboration” and more about “no forced, inefficient collaboration.” And that’s a future worth building.