AI‑Driven Interactive Decision Instruments
Key Points
- The workplace is transitioning to a new “operating surface” where AI tools like ChatGPT‑5, Claude, and Gemini turn traditional documents, spreadsheets, and slides into interactive, decision‑making artifacts.
- The biggest bottleneck in modern companies is not generating ideas but proving and executing decisions, which AI‑enhanced interactive artifacts can streamline by making decisions auditable, executable, and rapid.
- These AI‑driven artifacts act as “front‑end instruments” that combine simple inputs, UI elements, tests, and approvals, replacing multiple meetings and decks with a single, tweakable surface.
- The shift is enabled by easy distribution of single‑file canvases, low cost of AI services already bundled in employee plans, and built‑in governance features that capture and lock decision logic.
- While such instruments won’t replace large‑scale, highly refined processes like Amazon’s weekly business reviews, they are powerful for most teams, allowing rapid creation, reuse, and remixing of decision‑making tools.
Sections
- From Docs to Interactive AI Artifacts - The speaker argues that modern workplaces are shifting from static documents and spreadsheets to AI‑driven, editable, and executable front‑end artifacts—enabled by models like ChatGPT‑5, Claude, and Gemini—that turn decisions into fast, auditable instruments rather than mere paperwork.
- Transforming Static Deliverables into Instruments - The speaker urges replacing slow, document‑centric processes with programmable, auditable “instruments” that bundle explicit schemas, logic, UI controls, testing, and change tracking to accelerate decision‑making and boost team trust.
- From Static Docs to Live Artifacts - The speaker explains that while implementing an access‑review runner is technically straightforward, the real difficulty lies in cultural resistance and discipline needed to adopt interactive, continuously updated artifacts instead of traditional static documents.
- Shift Incentives to Decision Instruments - The speaker proposes rewarding employees for creating and using dynamic, gate‑driven “instrument” blocks that speed decision‑making—altering performance reviews and promotion criteria—while pointing out that tool makers like Notion are already rebranding from static document editors to execution surfaces.
- Shift from Authoring to Runtime Value - The speaker highlights a paradigm shift where the worth of AI-driven artifacts is realized during execution rather than creation, urging teams to experiment with and measure the adoption of AI “instruments” like GPT‑5 canvas in everyday workflows.
Full Transcript
# AI‑Driven Interactive Decision Instruments **Source:** [https://www.youtube.com/watch?v=SLYKFHtKR90](https://www.youtube.com/watch?v=SLYKFHtKR90) **Duration:** 00:16:20 ## Summary - The workplace is transitioning to a new “operating surface” where AI tools like ChatGPT‑5, Claude, and Gemini turn traditional documents, spreadsheets, and slides into interactive, decision‑making artifacts. - The biggest bottleneck in modern companies is not generating ideas but proving and executing decisions, which AI‑enhanced interactive artifacts can streamline by making decisions auditable, executable, and rapid. - These AI‑driven artifacts act as “front‑end instruments” that combine simple inputs, UI elements, tests, and approvals, replacing multiple meetings and decks with a single, tweakable surface. - The shift is enabled by easy distribution of single‑file canvases, low cost of AI services already bundled in employee plans, and built‑in governance features that capture and lock decision logic. - While such instruments won’t replace large‑scale, highly refined processes like Amazon’s weekly business reviews, they are powerful for most teams, allowing rapid creation, reuse, and remixing of decision‑making tools. ## Sections - [00:00:00](https://www.youtube.com/watch?v=SLYKFHtKR90&t=0s) **From Docs to Interactive AI Artifacts** - The speaker argues that modern workplaces are shifting from static documents and spreadsheets to AI‑driven, editable, and executable front‑end artifacts—enabled by models like ChatGPT‑5, Claude, and Gemini—that turn decisions into fast, auditable instruments rather than mere paperwork. - [00:03:18](https://www.youtube.com/watch?v=SLYKFHtKR90&t=198s) **Transforming Static Deliverables into Instruments** - The speaker urges replacing slow, document‑centric processes with programmable, auditable “instruments” that bundle explicit schemas, logic, UI controls, testing, and change tracking to accelerate decision‑making and boost team trust. - [00:06:23](https://www.youtube.com/watch?v=SLYKFHtKR90&t=383s) **From Static Docs to Live Artifacts** - The speaker explains that while implementing an access‑review runner is technically straightforward, the real difficulty lies in cultural resistance and discipline needed to adopt interactive, continuously updated artifacts instead of traditional static documents. - [00:09:48](https://www.youtube.com/watch?v=SLYKFHtKR90&t=588s) **Shift Incentives to Decision Instruments** - The speaker proposes rewarding employees for creating and using dynamic, gate‑driven “instrument” blocks that speed decision‑making—altering performance reviews and promotion criteria—while pointing out that tool makers like Notion are already rebranding from static document editors to execution surfaces. - [00:13:52](https://www.youtube.com/watch?v=SLYKFHtKR90&t=832s) **Shift from Authoring to Runtime Value** - The speaker highlights a paradigm shift where the worth of AI-driven artifacts is realized during execution rather than creation, urging teams to experiment with and measure the adoption of AI “instruments” like GPT‑5 canvas in everyday workflows. ## Full Transcript
We are moving to a new operating surface
at work. It is not just a function of
chat GPT5. I know I've talked a lot
about chat GPT5 the last few days.
That's because 700 million 800 million
people have it and we all use it. Now I
want to go beyond that. I want to talk
about the idea that we have a new
operating surface at work that yes is
exemplified by chat GPT5 but is also
going to be exemplified by Claude, by
Gemini and others over the next few
months. The stakes are really high. The
real drag in modern companies is not
creativity where AI has been attacking
over the last two years. It is so easy
now to get a hundred ideas, a thousand
ideas. The real bottleneck is the cost
of proving a decision. We do that in
docs. We do that in spreadsheets. We do
that in slides. And you know what's
happening over and over now? Chats
become docs. Chats become spreadsheets.
Chats become slides. And the challenge
is that we are still bolting on our old
decisionmaking to this new way of
working. I want to suggest to you that
with chat GPT5, we crossed a Rubicon. We
now have for the first time an
incredibly easy way for anyone who is
not a coder to create interactive
artifacts that collapse that chain.
Interactive artifacts that make
decisions executable, auditable, and
fast. My thesis is very simple. The unit
of work is shifting from static
deliverables to instruments of work.
Front-end artifacts that you can open
and tweak and run. An instrument will
couple some small typed inputs, a little
UI, maybe some tests or an audit in very
clean ways to look at the results. A
good instrument will replace several
meetings and a deck with one surface and
a very quick decision. Why is this
happening now? What makes this possible
today? Number one, distribution. It is
easy now to have single file canvases
that can travel as easily as slides
across internal tools. You can share
that chat GPT5 canvas so easily. Claude
does this too. You can share the cloud
canvas really easily. There's no
infrastructure to run that. Cost is also
so cheap. If you have all of your
employees on a chat plan anyway, and the
canvas comes with it, it's essentially
free. Governance is also easy because
tests and approvals live in the
instrument. You can actually capture
what you did and then if you really want
to lock it, just stick a screenshot of
that UI and stick it somewhere. It's
easy to log your decisions. The nice
thing is you can also compound and
remix. So these artifacts are not dead,
they're living. You can remix a weekly
business review artifact and make it
better next time. You can reuse it. Now,
I will add a caveat here. As someone who
worked on weekly business reviews at
Amazon, I am not trying to pretend that
one artifact produced by one person in
chat GPT replaces a weekly business
review instrument that has been honed by
business analysts over years for a team
at Amazon scale. What I am saying is
that most teams don't operate at that
scale and most decisionmaking doesn't
require that formula review process.
There's a whole class of practical work
done decisions that are right now being
made very slowly with documents with
artifacts. They don't need to be and
that is the new class of work that I'm
talking about when I talk about this
motion from static deliverables to
instruments. So what is an instrument?
It has an input, a very explicit schema
and sample fixtures. It has logic
functions that you can read and test.
The code is visible. Edge cases are
declared. It has a UI, a display first
scoreboard that has a few knobs you can
touch and dial. It has tests, so gates
are at the top and if it doesn't work,
it doesn't run. It has an audit encoded
in it and ideally it will have an
export. The key is making sure that you
take those instrument components
seriously. For example, if you have
inputs, logic, and UI, but you have no
audit trail, you can't really see what
changed when people started to mess with
your dashboard. And in the course of a
meeting there can be a lot of changes
and adjustments. So I want to suggest to
you that the strategic impact of getting
this this work done is really
understated because we haven't really
lived it yet. The real challenge here is
actually moving from a world where we
have high latency and high friction and
low trust for a lot of work even among
good functioning teams because people
can't remember the slack and they've
been trained over and over again not to
just trust the meeting but to get stuff
into a doc. get to a world where you
have more leverage, where trust
increases because you can actually see
it in the interactive artifact, where
you can just generate free evidence by
just running the artifact again with new
data points. You want to get to a point
where you have a portfolio of artifacts
that replaces your portfolio of
PowerPoint decks, something that lets
you run the business with artifacts.
Now, this is not going to work for
everybody. Again, I've said it before.
This doesn't replace BAS at scale. This
doesn't replace excellent SAS tools for
scaled up companies, but it does allow
you get a lot of practical work done.
I've created a dozen instruments to get
you started. And they're designed to
work together as a coherent operating
system for smallcale teams and something
that gives large- scale teams ideas
about how to run fast for those in
between the cracks where the real work
gets done stuff. Let me lay them out for
you briefly and then you'll get like
full prompts for them in the substack.
Run the business. You get a WBR
scorecard and you get a data quality
sentinel. Something that like helps you
obsess over your data quality and check
your data quality where it matters. For
shipping decisions, I've got an
experiment decision pad and I've got a
launch gate for you. For reliability,
I've got an incident commander dash and
I've got so radar. Again, these are very
configurable, right? You can adjust the
prompts the way you want. You don't like
my WBR? Don't use my WBR. Use the prompt
and make it yours. That's the whole
point. Revenue and risk. You have deals.
You have contract risk triage. These are
things you can actually put into on the
sales side. Customers, you have customer
health triage. You have a pricing and
mix simulator for your people side. You
can get a hiring and funnel health one.
You can get an access review runner. And
this is just the beginning. These are
designed to form an ops operating system
from the get-go and a loop you can put
in anywhere. But this is just the
beginning of getting your head around
the idea that you have instruments now
and not static artifacts. I want to
suggest to you that there are real
challenges with rolling this out that
are not technical. In fact, the
technical piece is mostly done. It is
relatively easy to get these to start to
work. Instead, the risks show up in
culture terms. People overtrust these,
right? Like sometimes they will have
shallow data in here and they will not
show their thresholds and they will not
pay too much attention to the artifact
because they're not used to it and they
will allow a lot of sprawl. They'll
remix the artifacts in 50 different
versions. This requires discipline just
like having a document standard requires
discipline. It's not like it's a free
ticket and you don't have to
administrate the artifact. The power
lies in the fact that it collapses a
bunch of other work into one clean
interactive artifact that makes
decisionmaking faster. So the work
really changes as a result and you have
to be ready to impose that on the
culture as a leader. So meetings can run
inside the artifact. You can record
them, use granola, use otter, use
whatever your recording uh AI is of
choice and then you have the record of
the meeting. You have the artifact
itself and you're done. That's the whole
thing. You need to get to a point where
you are encouraging people to test
artifacts, version them, and make sure
that people are using artifacts
appropriately in appropriate context and
not just overusing them in ways that
aren't helpful. You don't want 16
different versions of the same meetings
artifact running around because then
people will not trust it. And so there's
a certain level of experimentation you
want to encourage when you're trying to
get an artifact to gel. And then you
need to converge and actually pick the
winner and anoint that and standardize
it and discourage further
experimentation while you focus on other
parts of the workflow you want to align
out. Part of how you do that is by
challenging the operators, the runners
of the business to own the outcomes
associated with these artifacts. If you
have someone in sales who is running the
meeting that the artifact is associated
with, they own the artifact. If you have
someone in legal, they own the artifact
for the legal review. You get the idea.
The key here is that you have artifacts
that tie to consistent organizational
patterns, to product launches, to
incidents, to pricing, to access to
hiring, to weekly business reviews. And
you keep them as consistent and
versioned as possible. And yes, for
bigger teams, for bigger orgs, of
course, you're going to have like, you
know, the weekly business review version
for this team versus that team because
they're like 50 person teams and they
have different business units and they
have different metrics. I get that.
That's why prompts are easy to mix
together. The point though is that you
want to manage that cadence of
evolution. You want to manage who owns
it. You want to assign ownership just
like you do with other good culture
changes. And you want to map the
instruments to the meeting cadence in a
way that gives everyone predictability.
That's what builds trust. That's what
builds trust. I would suggest if you
want to move this way that you stand up
an instrument studio, a place to
maintain schemas, tests, export
standards, what counts as good that you
assign a bar raiser to review the
prompts that are used for any new
version so that people maintain those
standards and you get better over time.
And I want you to challenge people and
change the incentive to reward
decisioning that ships through gates,
not through decks or through docks. You
want people to start to think in terms
of how they can accelerate decisioning
and how they can leverage instruments
instead of flat docks to do so. So
change your incentives. Maybe change how
you do performance reviews. This could
get as far as looking at promotion
readiness is looking at whether someone
can articulate and define a new artifact
in a way that's useful for their team.
Just giving you an example there. I want
to close with one other piece. We've
talked a lot about how this changes
things for business runners, right?
People who run the business, operators.
What happens for tool builders, people
who build Word, Docs, Notion, Sheets,
people who are essentially building the
static docs of the past. I want to
suggest to you that Notion's already
aware of this and others are too because
they know the product is no longer a
document editor. It's an execution
surface. That's why Notion's homepage is
what do you want to make today? There's
going to be a ton of competition for
this space. And as a builder of a
business, you are going to be spoiled
for riches in how you actually convert
your team over to instruments. If you're
in the tool building business and you're
used to static docs, one of the really
interesting ways you can involve here is
choose to ship primitives for
instruments. Shipped inputs as blocks,
logic blocks, tests and gates, stable
exports, things that people need to
compose instruments for various
workflows. I think that's a really
interesting opportunity I haven't seen
anybody fully grasp yet. You want to be
in a place where you can have somewhat
opinionated building blocks if you're in
the document creation space because if
you just have free text, people will
abuse that. Whereas if you have inputs
with regular schemas and people can
choose those, you're going to get much
more useful downstream blocks. Give
people helpful limitations to help them
build composable instruments. And so
part of what I'm doing when I suggest
the prompts down in the substack is I'm
trying to hold to and key to an
opinionated schema, a schema you can
stick with over time because you need
that consistency to build useful
artifacts. One of the interesting
implications of all of this is that we
are moving to a world where policy is
code. So a business rule is literally
encoded in Typescript somewhere or a
business rule is encoded in an artifact
somewhere. approvals happen on the
surface. We don't really have this yet,
but we want to get to a world where we
have lightweight e signatures and not
just a buttonclick go no-go. Right now,
it's just going to be a buttonclick go
no-go that's encoded in the artifact and
you screenshot it. That's fine for
getting started, getting into the
instrument world. I want to see a world
where we actually have artifacts that
start to evolve into those mini
applications. And I expect to see that
over the next 6 months to a year. One of
the keys is making sure that these are
everywhere. You can link them if it's
Claude Claude and and the artifacts or
if it's chat GPT and the canvas, you can
link them anywhere. They're public
facing links. So, link them in the
invites. Link them in the chat. Link
them in the issue. Make sure that these
are interoperable and everyone sees
them. And make sure, and I'm just going
to advise this because I've seen this
happen. Make sure that you do have those
screenshots because people can go in,
click on them, and change things
afterward. right now and remix the
artifacts, which is great if you're chat
GPT and you're trying to encourage
innovation, but it's perfect hell if you
want to make sure you have a steady
state. And so until these artifacts
evolve with a little bit more miniapp
internal checkpoints, you be the one
that takes those screenshots and encodes
this is what we talked about, this is
what we decided. So you can always go
back to that state relatively easily. In
fact, at this point, honestly, you
cannot just encode the screenshot. You
can frankly grab a code snippet and it
becomes an even more immutable record of
what happened. I want to suggest to you
that there are some business model
shifts here. First, we are moving to a
world where AI needs to be visible and
governed from AI being in the shadows.
That means models need to have authors
for these artifacts. They need to have
run summaries and audits. You need to be
able to generate tests from the code
that show what you did. We are at the
beginning of this. you can use some
fancy prompt work and you can get
something like this going in GPT5 with
canvas. There's going to be more. I also
want to suggest to you that value is
starting to acrue at runtime, not author
time. That's a very profound shift. So
think about it for a second. It's not
the authoring of the artifact that
matters the way authoring the PRD
mattered when I came up as a product
person. It is it is the way value occurs
at the time you run the artifact and
have the conversation. And so the value
is in the active instrument itself. And
there's sort of a profound implication
there if you're building in the product
space. One of the things that I want to
suggest is that you lean into adoption
of these instruments if you're doubtful
but want to try and be willing to make
the first step trivial and imperfect.
Hey, let's replace the deck this week.
It might not be perfect, but let's see
how it goes and have the conversation.
That's a two-way door. We can do that.
See if you can start to measure the
share of meetings that run on an
instrument versus the share of meetings
that run on something flat. See if you
can start to optimize to support
instruments being used more and more as
you have internal AI teams that want to
support you. This is so much more
interesting work than just building the
chatbot to talk with the HR policy
manual, which for whatever reason seems
to be the default thing that people who
greenlight AI teams internally always do
first. No, do something interesting like
this that actually accelerates the
business. Think about AI as a outcome
driver directly, not just a chatbot.
Move the center of gravity from defining
a narrative into execution. That's what
these instruments do. Instruments don't
actually kill documents. They just they
demote them, right? Docs will capture
the narrative, the context, the story.
You're going to turn the meeting minutes
automatically into a document and a
story. Instruments are what give you the
decision and capture the record and then
you can move on. Instruments are what
let you go faster. And we've never
really had that before. So my challenge
to you is figure out how you can ship
higher quality decisions and prove that
they're better quality. And that's
exactly what I focused on with these 12
prompts to build these 12 instruments.
Better quality decisioning, fewer slide
decks. Welcome to a world where we have
a new way of working. We're all going to
learn about it