Cultivating Judgment in the AI Age
Key Points
- The rise of cheap, abundant AI means everyone—from consultants to internal teams—must become “judgment merchants,” cultivating the hard‑to‑teach skill of good business judgment across all roles.
- Because intelligence costs are dropping dramatically, value now comes from identifying what remains scarce (e.g., selection, sequencing, implementation, human resources, attention) and targeting those bottlenecks.
- Effective judgment is context‑sensitive synthesis, requiring you to tailor decisions to the specific circumstances and constraints of each AI project.
- The speaker will outline ten concrete principles (starting with the scarcity principle and context) to help professionals systematically develop and demonstrate strong judgment in the AI era.
Sections
- Cultivating Judgment in the AI Era - The speaker warns that as AI drives down the cost of intelligence, every professional must deliberately develop the hard‑to‑teach skill of good business judgment—becoming “judgment merchants”—and outlines ten principles for doing so.
- Judgment, Sequencing, and Deprioritization - The speaker stresses that good judgment means ordering AI bets as thin‑sliced, trust‑building MVPs and explicitly defining non‑goals to prevent scope creep.
- Coalition Principle for AI Project Success - The speaker explains how rapid feedback in AI initiatives combined with strategically mapping and sequencing stakeholder buy‑in—creating early wins to shift support from passive permission to active ownership—is essential for effective judgment.
- Cultivating Human Judgment in AI Era - The speaker argues that clear, logical thinking and transparent trade‑off analysis are essential soft skills that distinguish humans from token‑spitting AI, and that encoding such judgment into scalable systems transforms personal insight into lasting organizational capability.
Full Transcript
# Cultivating Judgment in the AI Age **Source:** [https://www.youtube.com/watch?v=O_VL5clgN_I](https://www.youtube.com/watch?v=O_VL5clgN_I) **Duration:** 00:14:46 ## Summary - The rise of cheap, abundant AI means everyone—from consultants to internal teams—must become “judgment merchants,” cultivating the hard‑to‑teach skill of good business judgment across all roles. - Because intelligence costs are dropping dramatically, value now comes from identifying what remains scarce (e.g., selection, sequencing, implementation, human resources, attention) and targeting those bottlenecks. - Effective judgment is context‑sensitive synthesis, requiring you to tailor decisions to the specific circumstances and constraints of each AI project. - The speaker will outline ten concrete principles (starting with the scarcity principle and context) to help professionals systematically develop and demonstrate strong judgment in the AI era. ## Sections - [00:00:00](https://www.youtube.com/watch?v=O_VL5clgN_I&t=0s) **Cultivating Judgment in the AI Era** - The speaker warns that as AI drives down the cost of intelligence, every professional must deliberately develop the hard‑to‑teach skill of good business judgment—becoming “judgment merchants”—and outlines ten principles for doing so. - [00:05:10](https://www.youtube.com/watch?v=O_VL5clgN_I&t=310s) **Judgment, Sequencing, and Deprioritization** - The speaker stresses that good judgment means ordering AI bets as thin‑sliced, trust‑building MVPs and explicitly defining non‑goals to prevent scope creep. - [00:08:35](https://www.youtube.com/watch?v=O_VL5clgN_I&t=515s) **Coalition Principle for AI Project Success** - The speaker explains how rapid feedback in AI initiatives combined with strategically mapping and sequencing stakeholder buy‑in—creating early wins to shift support from passive permission to active ownership—is essential for effective judgment. - [00:12:12](https://www.youtube.com/watch?v=O_VL5clgN_I&t=732s) **Cultivating Human Judgment in AI Era** - The speaker argues that clear, logical thinking and transparent trade‑off analysis are essential soft skills that distinguish humans from token‑spitting AI, and that encoding such judgment into scalable systems transforms personal insight into lasting organizational capability. ## Full Transcript
We're all becoming judgment merchants. I
know that's a new word. I'm coining it.
The reason I'm saying that is that
whether you work as an external
consultant in AI around AI or whether
you're working inside a company and you
are building in AI systems, wanting to
build an AI systems, leaning in on Chad
GPT, everyone is going to have to start
practicing judgment. This is not a
taught skill. This is not something that
you can just go and say, "Oh, I know
judgment now. I'm good at judgment." In
fact, for a long time, the ability to
exercise good business judgment was the
bar for principal product manager, the
bar for a senior engineering leader.
Now, what I'm suggesting to you is that
we need to find ways to cultivate that
for every level, for every job family.
Why is that? Because intelligence is
becoming too cheap to meter. Sam Alman
was saying that intelligence is falling
x a year in cost. X a year for the same
intelligence level. If that is even
remotely close to true, we have to
double down on being good judgment
merchants. And if that sounds too
abstract, it's not going to be by the
time you're done with this video. I'm
going to go through 10 principles. As
far as I know, no one has really put
together a miniourse on how to have good
judgment in the age of AI, even though
that's an irreplaceable skill and we
talk about it a lot. So, let's get into
it. What are 10 ways we can show we
exercise good judgment? This applies
regardless of job family. And this
should be specific enough for you to
actually jump in and wrap your head
around. That's my goal. Number one, the
scarcity principle. So intelligence is
abundant, right? If it's coming down at
a cost of 40x a year, everybody's going
to have intelligence. Value then
migrates to the next bottleneck.
Basically, one of the ways you show
value, whether you are inside a company
like Walmart or Netflix or Amazon or a
tiny company like a series A or a Seed
or whether you're outside as a
consultant, everywhere you look on an AI
project, you will see places where
intelligence unlocks an enormous amount
of volume and you will see places where
that volume bottlenecks. Part of your
value is finding the bottlenecks. It's
the scarcity principle. Find what is
still scarce in a world where
intelligence is abundant. Get eyeballs,
get get binoculars, get a microscope,
whatever metaphor you want, but find the
scarcity. The scarcity is there. Maybe
it's scarcity of selection and sort of
finding what to choose. Maybe it's
scarcity of sequencing. It's really hard
to know how to sequence. Maybe it's
scarcity of implementation. Maybe it's
scarcity of human resources in other
areas. There is always going to be
something scarce. Maybe customer
attention is scarce, right? Find the
scarcity. The fastest signal of good
judgment is how precisely you can define
the true current bottleneck. And that is
true whether you're internal or
external. Principle number two, context.
Judgment is contextsensitive
synthesis. In other words, you are
reusing patterns with an awareness of
what makes this situation unique. Good
judgment is excellent pattern
recognition crossed with excellent
context discrimination. You know the
current context and you have enough of a
pattern recognition that you can
actually put them together. Poor
judgment is overgeneralizing on a past
success or failure or just relying on an
AI generated best practice. The
implication is that if you are hungry to
show you have good judgment, you can
surface the nontransferable elements of
your recommendation and put those in
center stage. So when you're talking
internally about a project you want
done, when you are externally and you're
pitching something as a consultant, what
is unique about this moment, this org,
this system? Let's say you're a product
manager and you're trying to get
something built and it's an AI native
architecture. What is it about this org
that makes that solution specifically
correct? If you are looking to show you
have good judgment, look to show you
understand context deeply. That is your
advantage. Get passionate about a
particular corner of context. Principle
number three is the constraint
principle. You are analyzing what's
possible and you are judging what's
possible. Now, analysis by itself is
paralyzing. analysis will tell you all
of your options. But a great business
builder will think in terms of
constraints, will think in terms of what
is the possible build that we can
execute today. And so an excellent
judge, someone who shows good judgment
in the middle of the AI age, understands
intuitively within a given context what
is possible. Now, do you see how these
principles build on each other? I've
sequenced them carefully. These are not
randomly allocated principles. They
build on each other so that you actually
develop a cleaner and cleaner
understanding of judgment as we go
forward. Number four is the sequencing
principle. Most insights fail because
timing is bad or sequencing is bad.
Judgment shows up in ordering your bets
to create momentum and proof before
resistance starts to mount. In other
words, if you are internally trying to
champion an AI system and there is some
skepticism about how this system will
work, order your bets carefully. Show
good judgment by showing you know how to
sequence bets and thin slice your value
so that you can deliver something that
people can believe in. Thin slicing
value sounds abstract until you
basically have to look at an MVP of a
buildable system and say this little
piece that's what I'm going to deliver
because that earns trust. Maybe
initially we're only going to deliver a
chatbot on this particular page on the
website. Maybe initially we're only
going to convert this part of the wiki
into a rag system internally. Maybe
initially I'm only going to offer this
particular piece of value in my
consultancy as an AI consultant because
I know I can deliver it and I know I can
deliver it fast. That will earn trust
and then I can deliver more. Sequencing
matters and good judgment shows up in
knowing what is possible. Now, principle
five is dep prioritization. Everyone's
favorite word. Know what not to do. Have
non- goals. Explicitly list and defend
ideas that you are not going to go after
and not going to pursue. Have a
rationale for that. That is something I
will guarantee you that AI is not so
great at. AI loves to expand scope. One
of the signals of good judgment in 2025
of someone who is accountable for their
work is they will be honest with you at
a moment's notice about what they are
saying no to what they are
deprioritizing what they cannot do. That
is irreplaceable. And that is something
honestly that is an excellent piece of
career advice in an age littered with do
more, do more, do more. What are you
doing that is too much? What are you
doing that you need to let go of so you
can focus more effectively? And if you
really commit to that, if you choose
what you're going to depprioritize when
you look at a project, you open the door
to disproportionate leverage. And so
when you see projects that are runaway
successes, part of why they're runaway
successes is someone in that project
said, "This is the goal. Not this, not
this, not this. We are building a
chatbot for the customer. It will not
have the ability to use images. It will
not have voice initially. It will not
give you the ability to upload files. it
will be extremely good at talking about
the products on our website. That is all
focus have non- goals and that's true
whether you're trying to define what to
build or whether you're trying to define
what you're doing next. It is it is a
universal truism. It's absolutely
essential. You you have to say no in
order to be able to say yes. And it's
something that I I keep beating the drum
on it because AI is so bad at it. And I
want to call out like the there are
things AI is terrible at and this is one
of them. like specialize in this, right?
Dep prioritization. Number six, the
calibration principle. Judgment
compounds through feedback on accuracy.
In other words, your judgment gets
better as you get feedback on what goes
right and what does not go right. You
start to anticipate more correctly as
you get feedback on what works and
doesn't work. In a sense, this principle
is fractal. It works for your career in
the sense that you try things on and you
say that worked, that didn't work. But
that takes period of years, right? That
takes time. It also works on projects.
It works on AI projects especially well
because AI projects are typically run
fast and they're run hard and you get
feedback quickly. And so if you set up
an AI agent and you see nobody is using
it internally, you get feedback on how
you scope that agent. Maybe you
prioritize incorrectly. Maybe you depp
prioritize the one thing that the
business actually wanted. You can learn
from that. You can calibrate. You can
get better. Principle number seven. This
is another key element of good judgment.
It's a coalition principle. Good
judgment includes mapping the social
graph of decision makers and sequencing
their buyin correctly. You need to be
planning conviction moments where
stakeholders experience early wins and
shift their stance from merely
permitting something to happen to active
ownership. And if that sounds too
abstract, if you're trying to get
something over the line internally as a
project, it only happens if you get your
director and then your director's peer
and then your senior vice president and
then finally the seauite on board.
That's exactly what I just described. I
just used abstract terms for it so
everybody could understand it. It's the
same thing. If you're a consultant, you
run through the same process. Do you see
that? One of my larger thesis is that we
are overblowing the death of
consultants. It is it is actually I
think more correct to say that a lot of
the busy work in producing decks that
consultants have done for a long time is
going to go away. But the idea of
someone who offers good judgment is
becoming more and more important because
AI is bottlenecked on good judgment. And
so excellent consultants that offer good
judgment are priceless. But so are
excellent internal teammates who offer
good judgment. In a sense, we are all
becoming consultants. So the coalition
principle matters. Figure out who needs
to go from permission to excitement to
ownership to enthusiasm and sequence
your conviction moments, your aha
moments to get them there. That's good
judgment. Again, AI can't help you
there. Principle eight is the
responsibility principle. Judgment
carries ownership. The clearest tell of
good judgment is a willingness to say,
"If I'm wrong, here's how we'll know it,
and here's how what we'll do." You don't
have to be right all the time to have
good judgment. People sometimes think
you do, but you have to have
accountability and you have to be
willing to say if I made a mistake,
here's what we're going to do about it.
This is where I often tell people the
fastest way to fix AI slop at work is to
tell everyone, you are accountable for
every word you write. It can be with AI,
but you're still accountable. That
accountability is a sign of good
judgment. Own the consequences. Own the
consequences. Again, not something AI is
good at. Number nine, the transparency
principle. In the old model, assess
opacity, signal value. Trust the deck.
That's a fancy way of saying just trust
our deliverables. A shiny report. Now,
people actually trust transparent
reasoning more. This is a trend that's
opening up because intelligence is so
available. When intelligence was was
expensive, people trusted that a wellp
polished deck was a sign that you'd put
a lot of good thought into it. Now, a
wellp polished deck is just, you know, a
chat with Kimmy K2 away, but a
thoughtful deck is not. A thoughtful
deck still requires good old-fashioned
brain power. And so, being more
transparent with your reasoning is
coming into vogue. You want to be honest
about the options. You want to be honest
about your depp prioritization logic,
about your assumptions, how you think it
through, what trade-offs you're
negotiating. That is something that
wasn't true 5 years, 10 years ago in the
same way that it is today. that is
somewhat new and it's a response to AI.
It is a way of showing you know how to
think clearly, logically in an age where
AI just wants to spit tokens because the
difference between intelligence that
just says everything is on the table. We
won't have non- goals. We're going to be
super aggressive. An intelligence that
can lay out hard trade-offs really
clearly is real. If you've seen good
thinking, you know the difference
between really good quality thinking and
the first draft out of chat GPT. Don't
just ship the first draft out of Ched
GPT. Good judgment is showing
transparently how you are actually
wrestling with the problem. Principle 10
is the compounding principle. Judgment
creates leverage when it's encoded into
systems that last. And so a lot of good
judgment is figuring out how to solve a
problem by scaling out a playbook or an
automation that others can run with. So
your judgment shifts then from personal
heroics to true organizational
capability. I want to give you some
encouragement. The 10 principles I've
outlined are all things that AI is not
getting better at all that fast. So if
you're sitting there wondering why is
Nate talking about this soft skill
stuff? Isn't AI going to be good at all
this stuff? The answer is these are the
soft skills that distinguish what humans
are good at in the age of AI. I want you
to know it because I think it's not
something that is taught well because we
didn't have to learn it except by
osmosis before. Principal engineers
learn this from other principal
engineers for their discipline. Now
someone has to start teaching it for all
of us because suddenly judgment is all
of our job. Good judgment is something
that AI can't take away. So we'd better
get good at it. So we'd better learn it.
So we better learn how to teach it. And
that's where this is coming from is I
want everyone to start to get into the
idea of having good judgment. And I want
you to start to break down the mental
wall between being inside the company
and outside the company because I think
a lot of the traditional roles that
consultants had are now being occupied
by people inside the company as well.
Those lines are starting to blur. And
similarly, you see consultants doing
software work that in the old days would
have been done by internal employees.
It's another example of AI pushing the
lines. And that's all happening because
intelligence is becoming cheaper and
cheaper and judgment is becoming more
valuable. Judgment is the new
bottleneck. Judgment is what is becoming
scarce when analysis is free. I hope you
enjoyed this. I hope you feel like you
have a better sense of what actually
goes into the idea of good judgment. And
I hope you're able to apply it at work
because that's the whole point. I wrote
this up more on the blog. I have a
prompt to help you think through where
you need to learn and grow on judgment.
Dig in and have fun.