Gen AI and The Need for Galapagos Island

I am a former NLP Engineer. Yes the very word NLP now sounds pretty ‘Dinosauric’. I can’t believe within a decade we have moved from one hot encoding as embedding model to transformers-on-Steroids model.

At Aryma Labs, apart from building MMM and Marketing Experimentations, we build cutting edge Gen AI products focused on Marketing Measurement. Almost all our team uses Claude or Cursor to enhance their code.

Claude Code is genuinely impressive.
We refactored legacy modules in days instead of weeks. It suggested optimizations and patterns we hadn’t considered, perhaps ideas borrowed from other domains and surfaced instantly.

Which raises a deeper question:

📌 Has Claude Code Learnt Everything?

For those of you who are programmers, you might have have experienced that Claude almost has all the ‘Design patterns’ of most programming languages.

It may even have been trained on the public repos of so called ’10x – 100x Engineers’.

These 10x Engineers (I have been lucky to work alongside few in the past), are the Da Vinci or Mozart of programming. I have seen them do functional programming while thinking how to efficienize memory utilization.

This breed of programmers are shrinking and I wouldn’t be surprised if we have <10,000 of them now worldwide.

📌 10x – 100x Engineers using Claude Code

The issue isn’t average programmers improving – that’s good.

The issue is :

What happens when 10x engineers start defaulting to Claude instead of their own creative friction? Won’t we eventually ‘regress to the mean’?

If models are trained on yesterday’s brilliance, and tomorrow’s brilliance is guided by those models, where does true novelty come from?

📌 The Need for Galapagos Island

The Galapagos Islands fascinated biologists because species evolved in isolation. No cross-pollination. Pure adaptive pressure.
In causal terms a clean ‘control’.

📌 But why do we need Galapagos Island for Gen AI?

I think it is important that the 10x-100x Engineers don’t lose their edge to ‘regression to the mean’.
As strange as it may sound, I believe Gen AI progress and perhaps the path to AGI even lies in such Galapagos Islands.

I Imagine every big company hiring these 10x engineers and kind of putting them inside a Galapagos Islands (figuratively of course) where they are left to their own devices and solve some of the cutting edge problem through their own innovative thinking rather than using ‘Claude Code’ or ‘Cursor’.

From these “islands,” innovation flows outward.
Models can learn from the output but the source remains untouched.

📌 10x Engineers will be hired more

The advent of Claude code and cursor doesn’t mean the end of 10x Engineers. It just means even average programmer can intermittently become a 10x-100x programmer.

The 10x Engineers will continue to be in great demand in future. The edge and novelty of the world models will depend on the quality of inhabitants in this so called ‘Galapagos Islands’.