The Bull Case for Ambition

Citrini Research's The 2028 Global Intelligence Crisis makes a serious claim: intelligence itself may be becoming abundant.

For most of modern history, human intelligence has been scarce. That scarcity priced labor, services, and entire asset classes. If machine intelligence scales faster and cheaper than human cognition, that premium unwinds.

Most commentary and thought pieces like Citrini's focus on the labor impact. The floor drops out from repetitive cognitive work. The impacts on the market are disastrous (Citrini and many others) or utopian (various delusional theorists).

Certainly, that's one potential path. But there is another: when intelligence becomes abundant, the ceiling rises on what can be built. That is the part we are underestimating.

Speed Without Structure Is Fragility

AI can now generate code, draft contracts, optimize pricing models, and refactor services in seconds. In short, we can build quickly. This is an exciting advantage in today's marketplace.

However, abundant intelligence does not by itself remove the constraints of software product development such as legacy architecture, compliance complexity, or systemic technical debt. In fact, over the course of my career, I've seen incremental intelligence exacerbate these problems:

• Faster code generation without deeper test coverage increases blast radius.
• More analytics without cleaner data pipelines increases false confidence.
• Automated workflows layered onto unclear compliance logic increase regulatory exposure.

In each case, intelligence improved locally while systemic risk accumulated globally. Acceleration on top of unknown risk does not create efficiency. It creates fragility.

Most revenue-critical systems were built under conditions of cognitive scarcity, which meant slower change, fewer contributors, and human bottlenecks acting as informal safety rails. Abundance removes those bottlenecks. If the architecture doesn't change, risk compounds.

The Bull Case

But this is precisely why the bull case exists.

The opportunity is not to move faster on yesterday's foundations but instead to redesign the foundations.

A system worthy of abundant intelligence looks different from what we've been building for decades:

• Deployment pipelines designed for agent collaboration. An agent can open a PR, flag its own confidence interval on the change, and route to human review only when risk exceeds a defined threshold.
• Blast radius budgets as a first-class architectural primitive. Systems with defined blast radius budgets at the component level so that any autonomous change, human or agent-initiated, cannot exceed a pre-specified scope of impact without an explicit override.
• Compliance as a runtime property instead of an audit artifact. Compliance logic embedded as executable policy at the API layer so that regulatory constraints are enforced at call time rather than discovered six months later by an auditor.
• Confidence-weighted observability. Observability pipelines that track not just what the system did, but how certain each agent was when it decided—so drift in model confidence becomes a monitorable, alertable signal like latency or error rate.

In that world, AI does not merely cut costs. It unlocks capabilities that were previously out of reach.

And in that world, the newest, cutting-edge advancements are quickly relegated to table stakes while ambitious companies keep raising the ceiling higher. It will require continuing human intelligence to assess the landscape, intelligently deploy capital, and build something even better than what exists.

Where Citrini and I Diverge

This is also the point where Citrini Research's argument diverges from my own. Its assessment of the value of human capital assumes that we continue to build the same things to solve the same problems. But that's never been our story. Every productivity revolution has generated more demand for human creativity than it displaced, because the ceiling of what's possible rose faster than anyone predicted.

Abundance does not eliminate opportunity. It expands it. But it also clarifies what was always true: the constraint was never intelligence. It was imagination.