Software can absolutely act goal-driven without having consciousness etc - every pathfinding or navigation system or chess engine does this. Lots of "old-schoo

Software can absolutely act goal-driven without having consciousness etc - every pathfinding or navigation system or chess engine does this. Lots of "old-school AI" algorithms have explicit modeling of goal or target states. (In fact, the oldest "goal-driven" system is the control loop - like in thermostats - which was the founding invention of cybernetics, the predecessor of modern computer science) LLM coding agents are clearly able to identify some sort of "goal" state in their prompts, work towards those and track progress - otherwise agentic coding wouldn't work. The question is of course how well this works if it's all just "grown" neural network biases and not a fixed data structure like a goal tree. So I think it's possible that an agent can be thrown off-track, "forget" its goal, etc. But the basic structure of identifying goals, evaluating progress in light of those goals and then predicting the next action based on that is definitely there. Just use an agentic model with thinking traces visible for a while and you can see that for yourself.