Certain moments in history become reference points.
People of an age remember where they were when John F. Kennedy was shot. Many remember watching Neil Armstrong step onto the moon. Others recall the night the Berlin Wall fell or the horrible morning the towers fell on September 11.
These moments become markers in time. Years later someone asks, “Where were you when that happened?”
I believe this past week may become one of those moments.
Two developments this week stood out to me. On the surface they appear unrelated. One came from the world of cybersecurity. The other from the economics of artificial intelligence itself.
Taken together, they tell a much bigger story.
The first centers on a system Anthropic has been working on called Claude Mythos. In simple terms, Mythos represents a new class of AI capability that can analyze large software systems and reason about vulnerabilities in ways that previously required highly skilled security researchers. Instead of humans painstakingly combing through code looking for weaknesses, AI systems can now review enormous codebases, trace execution paths, and identify potential exploits at machine speed.
If that capability continues to mature, the implications are enormous. For decades the security ecosystem has operated under the assumption that finding vulnerabilities is difficult and time consuming. That difficulty acted as a natural brake on the system. What Mythos and similar AI capabilities suggest is that the brake may be disappearing. When machines can systematically hunt for software flaws across millions of lines of code, the balance between attackers and defenders shifts dramatically. The bottleneck moves from discovering vulnerabilities to fixing them before they can be exploited.
The second development came from a very different direction, but it may be just as disruptive.
Over the past several months we have begun to see what some are calling a “New Deal for AI.” Companies like OpenAI are driving an unprecedented wave of investment in artificial intelligence infrastructure. Massive data centers, enormous compute clusters, and global capital flows are being mobilized to support systems that can increasingly perform tasks once reserved for highly trained professionals.
Artificial intelligence is no longer just another software tool. It is becoming a general capability that can write code, analyze data, assist doctors, draft legal documents, design products, and automate large portions of knowledge work. When intelligence itself becomes scalable through machines, the structure of the economy changes. Entire professions will evolve. Some jobs will disappear. Entirely new industries will emerge.
The same technology that could transform cybersecurity is also poised to reshape the broader economic and social fabric of our society. One points to a future where AI can expose weaknesses in the digital systems we rely on. The other points to a world where AI reshapes how work itself gets done.
We may be witnessing the dawn of the AI century.
Banking systems, healthcare networks, energy grids, transportation systems and the countless applications that run modern society all rely on software. If the discovery of exploitable flaws becomes dramatically easier, the pressure on organizations to maintain resilience increases just as dramatically. It is not hyperbole to say that the security industry may be staring at a structural turning point.
Meanwhile, the amount of capital flowing into AI infrastructure now rivals the largest technology buildouts in modern history. This is not simply another productivity tool. It represents the possibility that intelligence itself becomes widely accessible as a computational resource. The ripple effects extend into education, labor markets, economic policy and the broader social contract.
History offers a few useful comparisons. The Industrial Revolution transformed physical labor. The internet revolution transformed information access and communication. Artificial intelligence has the potential to transform decision making and knowledge work. That combination may well define the twenty-first century.
On one side we are confronting a world where AI may dramatically accelerate the discovery of software vulnerabilities. On the other side we are watching the emergence of a new economic engine capable of reshaping how work itself is performed. That convergence suggests we may have crossed a threshold.
The age of AI is no longer theoretical. It has begun.
What happens next will not unfold in a single wave. Physical AI systems are advancing rapidly as robotics move into the real world. Quantum computing could eventually introduce its own disruptions in cryptography, materials science and advanced simulation. Within the next three to five years those technologies may begin intersecting with the AI capabilities we are already seeing today.
How should people respond? Start something — AI has made it cheaper than ever to build a company. Learn to work with these systems rather than against them. Lean into the human qualities machines cannot replicate: judgment, creativity, trust. And stay adaptable, because the pace is not slowing down.
One day people may look back at this moment as the point when artificial intelligence stopped being a fascinating technology and became the defining force of a new era. The week when the implications became impossible to ignore.
The real question is whether we recognized the moment for what it was.
The future has arrived. Ready or not.
