AI and the Mangrove Problem
Walk along a tropical shoreline and you’ll find thickets of mangroves where the sea meets the land. Their roots form a knotted shelter where juvenile fish hide from predators. Strip those mangroves out and the reef looks fine for a while. But without nurseries, young fish never reach maturity. A few years later, the reef collapses.
We risk doing the same thing to our talent ecosystem with AI.
Today’s AI tools perform at roughly the level of a junior. They draft, summarise, clean data, generate first passes. Seniors get to stay in “the interesting bits” while machines chew through the dull work that once trained people. A single mid-weight IC now does the work of three. On paper, that’s efficiency. In practice, it’s hollowing out the pipeline.
The short-term story is seductive: fewer hires, faster output, lower cost. Juniors are messy, expensive, and inconsistent. AI is tireless. If you only optimise for this quarter, why hire juniors at all?
Because the next decade comes quickly. Seniors retire, move into leadership, or burn out. If no one has come up behind them, the ladder breaks. And what disappears isn’t just bodies — it’s tacit knowledge, craft instincts, and the social fabric built when people learn together. Close the entry points and the profession ages, narrows, and loses resilience.
This doesn’t mean abandoning AI. It means treating it as a simulator, not an autopilot. Let juniors practice on real briefs, compare against senior benchmarks, and get feedback on the “why”, not just the “what”. Protect real apprentice work inside delivery models. Reward seniors for developing talent. Investors and clients should demand pipeline plans, just as they demand security or compliance.
The lesson is simple: efficiency without nurseries leads to collapse. The reef doesn’t die tomorrow; it dies when you’ve stopped looking. AI can give us leverage without taking our future — but only if we keep the mangroves intact.