The further you are from the outcomes of a decision, the easier it is to make a bad call. It’s a natural consequence of large systems where the decision-maker gets delinked from the person who has to absorb the results. And because it’s a systemic problem, that means we can design it out.

Two things that ruin my day: arbitrary bureaucratic hurdles and being told to “go fast and break things”. Turns out, they’re both just the extreme ends of the same risk spectrum: too risk-averse and you don’t get anything done, too risk-happy and you hurt people.

The problem is, localizing yourself on that risk spectrum requires the right incentives. It’s how you end up with both symptoms exhibited by the same team: be bold, but I don’t want to get yelled at if something goes wrong.

Let’s start with some definitions.

First off, bureaucracy is not a dirty word. It’s the overhead that makes a large people system with many actors produce consistent results at scale without harmful results. It’s a force multiplier.

When you go too lean on bureaucracy you get to watch engineers trying to reinvent things like program management from first principles. Good bureaucracy puts structure around decision-making and ensures that the right people are having the right conversations at the right times. Bad bureaucracy induces valueless make-work. People who act like children often point fingers at good bureaucracy when it has prevented them from enacting a stupid idea. This sort of whining accounts for about 60% of the content on AM radio.

Now, “moving fast and breaking things” isn’t bad either. You’re giving yourself permission to do something differently that may require other changes in the environment going forward. But remember that “move fast, break things” explicitly calls out the price of doing so. What things are you breaking? Can they be unbroken? What if the things you might break are people? Furthermore, what if you’ve abstracted away the things you might break far enough away that you can’t even see them when you’re moving fast?

And how do you find the sweet spot?

My risk management peeps already know what’s coming, but rather than asking you to FMEA your life here’s some simpler questions instead to start figuring out if you’ve got it right:

1. Can I even describe what “going wrong” might look like? Recovering juvenile delinquents and budding horror authors, this is your space to play in. Get imaginative.
2. Can I quantify that in terms of likelihood? Quantification turns uncertainty into risk and means we can grapple with it. One in a million hits a lot differently when you have five million transactions an hour.
3. Can I hit the undo button? Basically, how reversible is this? If it’s a software rollback with no data destruction, easy peasy. If you’re an autonomous vehicle trying to decide if that’s a toddler or a shadow, not so much.
4. Who gets hurt, and did they get a vote? The lady in the warehouse standing next to a robot wasn’t in the sprint planning meetings. The guy getting his medical claim denied by his insurance didn’t have input on the model weights. Yet people very far away from both of them accepted risk on their behalf.
5. Does whomever made the call have to face the consequences of the outcome? Accountability rolls upward to human beings, not downward to machines. If you put in a decision-making system, you own the decision. And the further away you are from those consequences, the more careful you must be.
6. How do you know the right decision was made? Detectability is key here for any decision-maker capable of learning. You can’t change how you make choices if you don’t get any feedback.


Setting aside the psychos, decent well-meaning people get the assessment of the above wrong all the time. Four main factors can do it to you: decision fatigue, blame avoidance, self-preservation, and short-termism.


Decision fatigue. Every decision requires cognitive energy. It’s why you hear of so many leaders emphasizing their monolithic wardrobes: even choosing your socks costs a decision. Furthermore, context switching costs even more energy. When you’re out of juice, you default to whatever’s safest for you, including anything that conserves that cognitive energy.

Blame Avoidance. No one wants to be yelled at. Delay costs nothing, whereas a perceived bad decision costs uncomfortable meetings. You’d rather optimize for whatever your boss thinks looks good versus what you might know is actually good.

Empire Building. Everyone wants to keep their jobs, no matter how phoney-baloney they may be, because everything else is predicated on having a job so that you can live. No one got an incentive for making their own existence go away.

Short-Termism. If you’re not around when the consequences land you have no incentive to do anything but discount the risk to zero. When you receive positive incentives for an excellent quarterly return, but the consequences hit in year 3 long after you’ve moved on, why not claim the win and run? Longitudinal studies rarely follow decision-makers around.

Now, are any of these novel concepts? Hardly. There’s a reason these all have such familiar names. We’ve been at war with these in human organizations since we started being human. Decision-making systems are decision-making systems regardless of the actor.

This is an allegory about agentic development.