- AI
Disclaimer: Member posts reflect personal views, not necessarily those of the Page Society.
When Eric van Hall founded CopyRobin, the idea was simple: connect companies that needed content with a network of professional writers and editors.
The model worked because writing — good writing — was scarce. Businesses needed it, and professionals produced it.
Then generative AI arrived and made one thing suddenly clear: the capability the business depended on was becoming radically abundant.
Eric first encountered generative AI the way many professionals did — as a tool that might make work faster. But within weeks, the implications became impossible to ignore.
AI could generate outlines, summaries, and complete draft articles almost instantly. Tasks that once took a freelance writer half a day could suddenly be produced in minutes.
For a company built around freelance copywriters, that realization was uncomfortable. If machines could produce text so quickly, what exactly was CopyRobin selling?
This was not simply a productivity improvement. It was a challenge to the core assumption behind the business.
For Eric, the turning point was recognizing that writing had never been the real value.
The visible output of the company was text — but the real expertise had always been somewhere else: understanding a client’s context, structuring ideas, asking the right questions, and ensuring quality and accuracy.
AI could generate words, but it still depended on someone to frame the problem, provide context, and judge the output.
In other words: the scarcity was no longer writing. The scarcity was thinking.
That realization shifted Eric’s perspective entirely. The future would not belong to those who could write the fastest. It would belong to those who could design the best systems for producing meaningful outputs.
Once that shift became clear, Eric began redesigning how the company worked.
Instead of a traditional process — brief, writer, editor, delivery — the workflow evolved into a structured system built around AI. Client materials were organized into knowledge bases. Prompts defined tone and structure. Drafts were generated quickly, then evaluated and refined by human editors.
In this model, people were no longer primarily writers.
Their role shifted to orchestrating the system.
Their job was to guide the system, assess its outputs, and ensure the final result met the strategic intent of the client.
What emerged was not simply a faster workflow, but a different operating model for producing communication at scale.
One discovery during this transition surprised Eric more than anything else.
When different people used the same AI tools for the same task, the results varied dramatically. The difference was not the technology — it was the framing.
The people who provided context, clear instructions, and strong editorial judgment consistently produced better results.
In an AI-driven environment, thinking had become more valuable than typing.
The phrase “crossing the Rubicon” describes the moment when a decision makes turning back impossible.
For Eric, that moment came when it became clear that CopyRobin could no longer operate as a traditional copywriting platform. The company had to evolve into something different — a system designer for AI-assisted content creation.
The destination remains uncertain. AI capabilities continue to evolve at extraordinary speed.
But one thing became clear through the transition: survival would not depend on resisting the technology, but on redesigning around it.
The real question was no longer whether AI could write.
The question was what becomes valuable when writing itself is no longer scarce.
Crossing the Rubicon meant accepting that the old model was gone — and discovering what the business could become on the other side.
What happened to a copywriting platform may soon happen to communications departments as well.
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