More and more agents, and automation becoming stronger,

What truly makes people uneasy is never "what it can do",
But: if it makes a mistake, who can explain? Who is responsible?

This is also why I have always believed that @inference_labs' direction is very right.
It's not about pursuing more dazzling autonomy,
But about prioritizing verifiability and accountability.
Making the system not just "look like it's working",
But ensuring every step has traces, can be reviewed, and can be questioned.

This will become even more important in 2026.
Because when autonomy truly begins to take over decision-making,
Systems that are fuzzy, black-box, and rely on trust will eventually run into problems.

The correct attitude should be:
First, clarify the underlying rules,
Then discuss scale, efficiency, and imagination.