Nufar Gaspar

We're not at a point where agents can or should replace humans altogether.

They can replace tasks, but, you know, not entirely.

And this has a few clear implications.

The main one is that first you want to have a very clear playbook based on your company regulatory state.

So probably...

Companies that are from a higher regulatory point of view, they have to be much more strict versus companies that perhaps are from industries where they can take bolder risks.

And here you have to define where agents can aim for full autonomy and what are the guardrails versus places where you're not aiming there and the guardrails need to be accordingly.

The other thing that you need to define is, let's say that we already get something good out of our agents.

If employees get their time freed up, you need to clearly define what you expect them to do with it.

Stating that it's not a matter of just replacing them, but rather you want to perhaps grow the business, look for other places where they didn't have enough bandwidth.

That creates both business value and value.

It reduces the fear and avoids employees sabotaging the agent behavior because they're afraid that any time freed up will be just a case for letting them go.

And lastly, you have to have very clear goals to measure how the agent will be tracked versus goals or how will you measure success.

And that aligns everyone on the value and the why behind the work and creates typically much better results.

When it comes to attitude, we're talking about the attitude of your employees and your managers.

And when we look at the audit data of superintelligent, often the attitude is a very good predictor of how ready the company will be, regardless of all the other data.

So what I want to encourage you here is to be very proactive to manage the duality of employee sentiment and channeling this enthusiasm that they typically have.

to eliminate the grant work while still addressing biases and profound fears about the job security or being quite set in the old ways.

And often the attitude that comes from the interviews are very surprising.

For example, one interesting observation is that often the most talented engineers are the worst adopters of new AI tools.