Every few months, intelligence gets visibly better. Something that required an awkward handoff now works in one shot. A task that needed a specialist is suddenly available in a tab. The pace is real, and I do not think it is slowing down.
An intelligence can write, reason, search, compare, plan, and act. As those capabilities improve, the question gets more important, not less: to what end?
That question is alignment.
Ability has no destination
Intelligence helps a system see more options. It can make a better plan, find a hidden pattern, draft a clearer message, and complete work with less help. Those are real gains.
But capability does not contain a theory of what should be done. A system can be exceptionally good at optimizing a goal that was badly stated, out of date, or never truly belonged to the person it serves. It can do the wrong thing with remarkable fluency.
That is not a distant safety thought experiment. It is a product problem already. Ask an assistant to make a calendar more efficient and it may remove the breathing room that made the week survivable. Ask a business tool to increase conversion and it may optimize a moment that makes customers less likely to trust the business later. In each case, the answer can be locally sensible and globally wrong.
That is why I separate the two ideas.
Intelligence answers: what can be done? Alignment answers: what should matter now, and for whom?
The first is an engineering problem. The second is a relationship. I think the companies that understand this will build a different class of product from the ones racing only to make the answer appear faster.
The missing layer
Most AI products begin and end with a conversation. The person supplies the goal, the context, the constraints, the correction, and often the quality check. The model supplies an answer. The exchange can be useful, but the person remains the operating system.
That model breaks down when the work is ongoing. A person should not need to restate their never-dos every Tuesday, re-explain the shape of an important relationship, or translate a business strategy into a fresh prompt for every new agent.
The missing layer is the one that holds direction over time: goals, permissions, constraints, changing priorities, and the right to revise all of them. It decides when the intelligence should work quietly, when it should bring a choice forward, and when it should stop.
That layer is not a trick prompt. It is not a personality setting. It is the actual product.
A useful distinction
This is not an argument against general intelligence. General intelligence is extraordinary precisely because it can help across many kinds of work. It is the engine.
But an engine is not a destination. For intelligence to become useful in a life or a business, it has to be situated in one. It needs to know whose work it is supporting, what success looks like there, and what kind of action requires a human decision.
That is the work behind myOrbit: not asking people to become better prompt writers, but building a place where intelligence can take direction, keep it, and be corrected when it gets it wrong.
Capability will keep moving quickly. The useful question is whether the direction can keep up.