I’m Khaled. I’m a technology lawyer working alongside enterprise legal teams, thinking about what work we should hand to AI, and what work we shouldn’t.
The Limits of Human Effort
Until now, there was only one way to keep attacking a problem.
Throw more of yourself at it.
You could feel like the most disciplined person in the world at that moment.
You could work for hours and hours. Keep pushing at the same thing.
But eventually, and true to human nature, you hit a point where more effort stops producing better work. You’re, dare I say… tired.
At some point, you’re just moving things around and convincing yourself you’re still working. So you decide, “You know what, I’m better off going at this fresh again tomorrow.”
There is only so much energy we can throw at a problem. Or there was. Now, a certain kind of intelligence has become a commodity, so we can throw (artificial) intelligence at the problem.
The Limitless Energy of AI
With agents, that intelligence doesn’t need to stop when we do. It doesn’t get tired. It just keeps going. You can even run a hundred subtly different versions of the same intelligence at the same problem, all at the same time. And agents keep going enthusiastically! (Maybe even a little too enthusiastically at times.)
An agent can work towards a goal, check its own work, see where the output fails to meet certain criteria that you set or it has set for itself, and just go again.
And again. (And again).
The upside? We can produce deliverables much quicker.
Provide faster answers.
Write faster.
Research faster.
Review (and redline!) faster.
Now, what I’m paying attention to is the work we can throw intelligence at that we would never have thrown human energy at in the first place. Either because the work was too great for the return we might get from it, or because we simply didn’t have enough years left in our working lives…
Take every contract a company has ever signed.
Every single contract.
Ask, Where are we taking on the most liability?
What do we keep conceding? At what point in the negotiation?
What patterns have we missed?
The Risk of Too Much Intelligence
Previously, someone would have to read thousands of contracts. So it was never going to be done. And because we knew the size of the task was too large, we just never asked these questions. Not knowing was a risk we were willing to absorb.
The same goes for years of customer conversations, thousands of support tickets, or every internal request a team has received. We have always had more information than we could realistically process. Until now.
Now we can throw intelligence at it. And that changes what work is reasonable to consider doing. And this sounds great in principle. But there is something I’m realising I need to be careful about here… The limits of human energy was also a filter: If something took three weeks, we had to decide whether it was worth three weeks. If a point in a contract wasn’t worth spending time on, we probably left it alone.
That filter is starting to disappear.
A great post from Anna Guo the other day made me think about this in the context of contract negotiations.
AI has made redlines incredibly easy to produce. But someone still has to review all those redlines. If the counterparty is overzealous in their use of AI, you get a contract back with redlines on everything. Changes that don’t really matter. Comments that just describe a change, without attempting to negotiate or explain why it’s needed.
Redlines that carry zero awareness of the nuanced context of the deal in front of them.
Someone just told an AI to review the contract.
There was no one stopping to think, actually, this isn’t worth fighting over.
No feeling of the inherent cost that every redline carries.
So agents can take on work that we never would have done.
They can keep going long after we would have stopped.
But when production becomes cheap, we lose one of the things that made us ask whether something was worth producing at all.
We are going to get much better at answering: Can we do this?
The harder question is: Should we throw intelligence at it?
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