The Arc of AI Agency
From systems that answered, to systems that act — and the open question still sitting at the center.
Rules & logic
Hand-coded systems following explicit instructions — and the engine behind decades of early automation. Only ever as smart as the rules someone wrote.
Machine learning
Systems that learned patterns from data instead of fixed rules — recommendation engines, image recognition, prediction.
The LLM era
Large language models that respond to a prompt and stop. Fluent, useful, but passive — they answered, they didn't act.
Agentic workflows
Models that plan multiple steps, use tools, and self-correct. Real, deployed — but steered by human-written tracks underneath.
Superintelligence (ASI?)
Intelligence beyond human level, with genuine intention and judgment in chaos. Much-discussed, not here yet — and honestly nobody knows the date.
Today's "agents" are less autonomous beings and more highly advanced, LLM-driven workflows. They plan, call tools, and recover from their own errors, which is new and genuinely useful. But the intention, the steering, and the guardrails are still entirely human. We've built systems that convincingly simulate agency without actually having it. Incredibly useful — just don't mistake it for the real thing.