Ideas. Ryan Macintosh explores the rise

of what he calls the electro-industrial

stack, a new foundation for how we build

and power America's industrial future.

Angela Strange identifies a critical

turning point in financial services and

insurance where decades old systems are

finally ready for reinvention. And Sarah

Wang reveals how a dynamic agent layer

is emerging to overtake traditional

systems of record fundamentally changing

how enterprise software operates. These

aren't just forecasts. their firsthand

perspectives from investors driving

change across American dynamism,

financial services, and enterprise

technology.

My name is Ryan McIntosh. I'm an

investing partner on the American

Dynamism team. My big idea for 2026 is

that the electro-industrial stack will

move the world. The next industrial

evolution won't just happen in

factories, but inside the machines that

power them. This is the rise of the

electroindustrial stack. Combined tech

that powers electric vehicles, drones,

data centers, and all of modern

manufacturing. I I think there are

common uh tropes people report on.

People talk about China's so far ahead

uh we can't catch up. And actually, you

know, you go back a couple years ago and

people were saying, you know, China's

very far behind and America's incredibly

fast. So, we've seen sort of like a

whiplash and now it's the opposite. I

think the reality is that uh you know,

the technology that China has, America

can do. Uh we're very good at uh

engineering. We're very good at doing

specific things. And in fact even like

the you know recent stuff around rare

earth for example rare earth separation

and processing we know how to do this we

can do this we [music] can do it

incredibly fast. The real challenge is

building the ecosystem to do this

industrially at scale and doing it at a

low cost. Another example you know

people typically talk about is is

companies like SpaceX or Android these

large businesses that need to move

incredibly fast and thus vertically

integrate. In many ways they're

vertically integrating by necessity not

strategy. There just isn't an ecosystem

of companies that can scale with them.

That is not the case in China. There are

tier one, two, three suppliers,

components, raw materials that exist in

those ecosystems as well as the, you

know, the institutions [music] and uh uh

political bodies that allow them to move

incredibly fast. Those are the things

that might take years or decades [music]

for us to catch up to China. We can do

the technology, but everything else

needs to grow with it, or else we're

just moving the bottleneck. So if you

want to build uh the electro-industrial

[music] stack or the core components

that feed into these technologies in the

United States uh you need to blend

Silicon Valley software talent and

culture uh with industrial veterans.

Even companies like SpaceX, they were

pulling propulsion talent from people

who worked on you know shuttle program

and various old school [music]

contractors when Shawwell came from

aerospace corporation. Like there there

is a there is a world where you need

this actual expertise. You [music] need

to know what's been tried before. There

are smart people ex out there in these

other companies, but you need to be able

to move [music] a lot faster. There's a

lot of advantages of software today. So,

you need to be able to get the software

talent that may not exist in these

companies previously. [music] You also

want to colllocate engineering and

manufacturing concepts like design for

[music] manufacturing uh are something

that you know when you're tightly

integrated on the same footprint or in

the same ecosystem uh you can move a lot

faster. And I think also you need to

build prestige around the mission. Um,

for a lot of sort of traditional Silicon

Valley talent, the smartest people can

work on a number of problems and there

are a lot of problems that are worthy of

working on. Some of them pay more than

others. So, you need to attach sort of a

a prestige or a purpose to what you're

working on and uh use that to to [music]

attract the top talent. The way that

software will affect the physical world

is through these sort of embodied

[music] electrified components. And it's

not just, you know, not just a humanoid

robot or an electric vehicle, but it's

the batteries, it's the power

electronics, it's the compute, it it's

it's the motors. All these things we're

going to need to either reshore or

vertically integrate within the

companies who are building the end

product. These are, you know, very

technical. These require a lot of

expertise. These are very difficult

problems to solve. But the companies who

solve it and the countries who have the

talent base to in order to support it

are the ones who are going to win in the

21st century. And as software and

artificial intelligence get stronger and

they start having you know more of a

presence in in automation and [music]

industrial military owning these supply

chains is going to become even more

important. And I think as we you know

look forward 50 100 years owning the

supply chains today are going to have a

lot of effects of who controls both the

sort of economic and military uh powers

[music]

uh in in the future.

the AI applications fund. And my big

idea for 2026 is there will be a

dramatic turning point coming to

financial services and insurance where

finally the risk of not replacing legacy

systems will exceed the risk of change.

It's already happening. [music] Major

institutions will let long-standing

contracts lapse and implement their

newer AI native competitors. Why? The

next generation of infrastructure

doesn't just add [music] AI. They unify

the data from legacy cores, from

external systems, from unstructured data

into a new system of record, enabling

FIS not only to scale, but to take full

advantage of AI. When this happens,

there are three major changes that are

important for both customers and

builders. One, workflows will finally

become parallelized. No more bouncing

between screens, cut pasting data. For

instance, your mortgage team could see

the 400 plus tasks that are needed to

underwrite your loan, do them in

parallel, and even have agents do some

of the more mundane ones for you to

check later. Second, the categories as

we know them are going to expand. For

instance, [music]

customer data from onboarding, KYC, KYB,

transaction monitoring, even how those

customers behave with your customer

service team could all sit into a single

risk platform. brings together fraud,

risk, compliance much more effectively.

And then [music] third, most excitingly

for the builders, the new winners here

will be 10x bigger. Not only because

those software categories [music] are

bigger, but because software is able to

consume a lot of the labor that humans

didn't want to do anyways or that banks

or insurance companies couldn't hire for

fast enough. So, as the saying goes,

it's not [music] AI that's the

competition, it's your competitors using

AI. So the best banks, the best

insurance companies will fix their

plumbing and enable them to take full

advantage and be the most competitive

going into the next decade. Companies

have been talking about this for

decades. Why is it different now?

Primarily three reasons. One, we have to

remember that many of these companies

still live on mainframes, decades old

mainframes, and their systems were

already on the verge of breaking with

the scale. Two, now companies see that

they're leaving a lot of revenue on the

table [music] by not being able to take

advantage of AI. For instance, in

insurance, [music] underwriters

sometimes can't even get to the demand

that they have because they're not able

to process it fast enough. They can't

bring in the documents. They can't scan

them. This is a huge revenue upside that

can be captured if you get the right

system and you layer AI on top. Third,

there are strong [music] viable options

of this next generation of AI first

software built by entrepreneurs [music]

who deeply understand your industry, are

deeply technical, and have entirely

rearchitected your platforms to one

enable you to scale and two be

incredibly flexible in terms of how you

can add AI on now and in the future. I

see a ton of opportunity here and

potentially a dramatic reordering of the

winners and losers of incumbent

companies based on who become the early

adopters of some of these new platforms.

And we're already seeing it. There's

some banks and there's some insurance

companies that are starting to get the

reputation of being forward thinking,

easier to work with, wanting to lean in.

And those companies in some areas like

mortgage servicing have been able to

turn areas of their business from 5%

margin businesses to 50% [music] margin

businesses. And you imagine doing that

across your company as quickly as

possible. It's going to make a much

bigger difference against your

competitor that maybe takes 2 or 3 years

to catch up. One of the reasons as an

investor that I get so excited about

infrastructure is that it's [music]

beautiful infrastructure that enables

beautiful consumer experiences and

beautiful business experiences.

For instance, why does your bank market

products to you that you already have?

It's because your customer data sits

[music] in all of these different

sectors. Why can't customer service

agent A answer questions about customer

service B if you call in about your

banking operations? Now, imagine the

future of a unified data layer and

incredibly smart people supplemented by

agents that can understand your needs,

help you with any product you already

have, anticipate your needs in the

future. That would be a beautiful

experience for both customers and

businesses. In 2026, [music]

we're going to see a dramatic

acceleration for any company that has

built a new AI first platform that sells

into this large industry. But the

opportunity is massive. So if you are a

founder who deeply understands or is

deeply curious about any archaic aspect

of banking or insurance, the opportunity

is now. You can build your software

faster and customers are ready to buy.

Growth, and my big idea for 2026 is that

systems of record start to lose their

edge. A passive system of record layer

stops making sense when agents can

independently execute on unsigned

intent. [music] I expect to see a new

dynamic agent layer that actually makes

sense for employees to replace legacy

systems of record. This is a very

exciting development on the long road of

inserting intelligence into companies. I

don't say that systems of record are

losing privacy lightly at all. I used to

work at a firm that almost exclusively

invested in ERPs and other systems of

record because of the stickiness of the

data gravity. There was a wave of SAS

2.0 that was wellunded and tried and

failed to take on the system of record

mostly through a better UI. This is the

first time that we've seen a genuine

threat to that and that's because the

distance between intent and execution is

collapsing and that's creating not a 20

to 50% better experience for the user

but how you get to that magical TEDex.

Let's take the concrete example of ITSM

IT service management. This has

traditionally been the domain of

powerhouse company Service Now. I

chatted with a head of IT recently who

told me for the first time in his two

decade long career he believed that IT

support was fundamentally going to

change. It will look completely

different in 5 [music] years. So why is

that? If you think about the way that

the old systems work, how long it takes

to do something like request access to

new software in the firm and you [music]

contrast that with the ITSM agents that

are arriving. They plug into your stack

and this type of request becomes nearly

[music] instantaneous. Through

advancements in LLM, you can now extract

intent. You can classify the request

type. You can map it to a known

workflow, identify user entities, and

the request from the user becomes

fulfilled in a way that is efficient and

accurate. So, we think there's a couple

of valuable layers in this new paradigm.

Of course, there's the foundation model

layer. We believe that stays valuable.

Um, but it's really the emerging agent

layer that sits as close as possible to

the user and is collecting data on that

user, understanding user preferences

that we think acrru value in the future.

Based on everything that we're seeing in

the wild, we believe this is a huge

opportunity for new players to come in

and win. [music] Why is that? We're in a

phase right now where the product is

getting better on a weekly, if not

daily, basis, and you need teams that

move fast. If you're going to collapse

[music] intent and execution, what

bridges that is actually having an

accurate or reliable [music] solution

for your customer. Otherwise, they're

not going to use it. They're not going

to trust the agent that you're building.

That's why we're [music] starting to see

even agents built on top of classic

iconic platforms like Data Dog lose to

some of the new AI SRE companies like a

a Resolve or a Traversal. We're

extremely excited about this opportunity

and 2026 is going to be the year that

the dynamic agent layer overtakes the

system of record.