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The New Defense Stack: Five Frontiers Rewiring the Industrial Base · Defense B2B podcast news daily - for industry professionals subscribe to develop your skillsets

0:00
Welcome to Copilot Podcasts. A military drone
0:04
just landed on a tank trail in South Korea, not
0:07
a runway, not a tarmac, a literal manoeuvre trail
0:10
used by tanks and artillery, and then took off
0:13
again. That happened this week and it's not just
0:16
a cool aviation story. It's a signal that the
0:20
entire architecture of how the US defence industrial
0:22
base thinks about resilience is being rebuilt
0:25
from the ground up. Today we're breaking down
0:28
five developments that are reshaping that industrial
0:31
base right now. Battlefield drone autonomy, hypersonic
0:35
test infrastructure, orbital security gaps, AI
0:39
training environments, and a brand new cyber
0:42
security playbook from CISA. By the end of this
0:45
episode you'll understand what these five things
0:47
have in common. They matter for contractors and
0:49
suppliers beyond the big primes, and what the
0:52
workforce actually needs to look like to make
0:54
any of this real. I've got someone here who's
0:57
been deep in this material, so let's get into
1:00
it. So the framing I'd start with is this. These
1:02
five developments aren't random headlines. They're
1:05
five expressions of the same underlying shift.
1:07
The defense industrial base is becoming more
1:09
distributed, more data driven, and more dependent
1:12
on evidence rather than promises. And that changes
1:15
what it means to be a competitive supplier, a
1:18
credible contractor, or a skilled worker in this
1:20
space. Okay, so let's start with the drone story
1:23
because that one genuinely stopped me. What actually
1:26
happened with the Mojave aircraft? So General
1:29
Atomics Aeronautical Systems and Hanwha Aerospace,
1:32
that's a South Korean defense company, announced
1:34
a demonstration where their Mojave aircraft flew
1:37
from a conventional South Korean Army runway
1:39
to a simulated battlefield site, landed on a
1:42
rough maneuver trail normally used by tanks and
1:44
artillery, and then departed and resumed flight.
1:47
The aircraft carried dual weapon rails with inert
1:50
payloads, so this was a controlled demonstration,
1:52
not a combat event. But General Atomis described
1:56
it as the first battlefield flight operation
1:58
of this kind by a medium -altitude, long -endurance,
2:01
uncrewed aircraft. Wait, so the whole point is
2:04
that it doesn't need a real runway? Exactly.
2:07
And that's the durable headline here. Runway
2:09
independence. Because reconnaissance becomes
2:12
dramatically more resilient when aviation can
2:14
disperse beyond large, predictable airfields.
2:17
Mojave combines persistent fixed -wing reach
2:19
with high lift surfaces, rugged landing gear,
2:22
and a smaller support footprint. Its value isn't
2:25
simply that it can land short, it's that it can
2:27
reconnect sensing with dispersed ground operations.
2:31
A forward site could potentially support intelligence
2:33
collection, communications relay, resupply, other
2:36
approved mission packages. And the partnership
2:38
model here, General Atomics and Hanwha, that's
2:41
not just a business deal, right? There's something
2:43
bigger going on with how they're planning to
2:45
build this thing. Right. And this is where it
2:47
gets really interesting for the industrial base.
2:49
General Atomics and Hanwha plan to co -develop
2:52
and co -produce a production version for South
2:54
Korean and global customers. They're expecting
2:56
a critical design review in November and a first
2:59
production aircraft flight in 2027. Those milestones
3:02
create demand signals for structures, engines,
3:05
avionics, sensors, secure communications, tooling
3:08
and lifecycle support. And they reward suppliers
3:11
that can document quality, cyber hygiene, configuration
3:14
control and export compliant collaboration. So
3:17
this isn't just a win for General Atomics, it's
3:20
a signal to the whole supply chain. That's the
3:22
key insight. The source material frames it explicitly.
3:25
Expeditionary autonomy is an ecosystem sale,
3:28
not merely a platform sale. Programs still need
3:31
maintainable ground stations, training environments,
3:34
field diagnostics, spares planning, and trustworthy
3:37
software updates. Small firms should notice that.
3:40
The airframe is almost the least interesting
3:42
part of the commercial opportunity. And what
3:44
does the workforce actually need to look like
3:47
to support something like this? Because I imagine
3:49
it's not just traditional aircraft mechanics.
3:52
It spans aircraft mechanics, flight test engineers,
3:54
autonomy developers, mission planners, and supply
3:57
chain specialists. Technicians need cross training
4:00
in conventional aviation discipline and the distinctive
4:02
maintenance needs of uncrewed systems. Software
4:05
teams need systems thinking because sensor behavior,
4:08
communications limits, and human authority all
4:10
meet inside one mission workflow. And manufacturing
4:14
programs need metrology, composite fabrication,
4:17
electronics inspection, and digital thread skills
4:19
that survive production scaling. That's a really
4:22
different skill profile than what you'd need
4:23
for a traditional manned aircraft program. Completely
4:26
different. And the source makes a point I think
4:29
is worth sitting with. Project leaders need enough
4:31
technical literacy to separate demonstrated performance
4:34
from marketing language and future aspiration.
4:37
That blend of skepticism and ambition is exactly
4:39
what makes a defense workforce trustworthy to
4:41
customers and crews. The demonstration showed
4:44
a physical aircraft completing a difficult recovery
4:46
and relaunch sequence under representative terrain
4:49
conditions. It did not prove every operational
4:52
claim or survivability requirement. That distinction
4:55
matters. Okay, let's move to the hypersonic story,
4:58
because this one surprised me in a different
5:00
way. I expected it to be about a new missile
5:03
or a new propulsion breakthrough, but it's actually
5:05
about something more foundational. Yeah, this
5:08
is the one that I think gets underappreciated.
5:11
AVEX was selected for a contract worth up to
5:13
$92 .2 million for a three -year role supporting
5:16
the Pentagon's Sky Range program through the
5:18
Test Resource Management Center. The work covers
5:20
airborne range integration, flight operations,
5:23
telemetry relay, resilient communications, payload
5:26
integration, and mission data across Western
5:28
and Pacific test corridors. So it's not about
5:31
building a hypersonic weapon, it's about building
5:34
the infrastructure to test one. Exactly. And
5:37
the framing in the source material is really
5:40
sharp on this. Advanced propulsion cannot mature
5:43
through equations and wind tunnels alone. Programs
5:46
need repeatable flight opportunities that return
5:48
usable evidence from extreme speed, heat, vibration,
5:52
and communications conditions. The strategic
5:54
bottleneck is increasingly the test network surrounding
5:57
the vehicle, not the vehicle itself. That's a
6:00
genuinely counterintuitive way to think about
6:02
it. The bottleneck is the test infrastructure.
6:05
And Sky Range addresses that by moving major
6:07
instrumentation from fixed sites and specialized
6:09
ships onto high -altitude airborne platforms.
6:12
Former RQ -4 aircraft, those are the large surveillance
6:15
drones, are being repurposed as range hawks,
6:18
carrying sensors and communications equipment
6:20
for flight test observation. Airborne nodes can
6:22
reposition across long corridors and relay telemetry
6:25
while a test article crosses distance rapidly.
6:28
Wait, they're taking retired surveillance drones
6:30
and turning them into flying test laboratories?
6:33
That's essentially what's happening. And the
6:36
architecture aims to improve scheduling flexibility
6:39
data resilience, and the frequency of meaningful
6:41
experiments. The technology stack reaches from
6:44
optical and radio frequency sensing to timing,
6:47
networking, storage, and post -flight analytics.
6:51
Every layer must preserve data provenance, because
6:54
an impressive flight with unreliable evidence
6:56
teaches very little. The system is best understood
6:59
as a mobile laboratory distributed across aircraft,
7:03
networks, ranges, and analysis teams. And the
7:06
government's award notice apparently frames this
7:08
as a prototype project whose follow -on depends
7:10
on validated, accepted performance. So there's
7:13
real accountability built in. Right, and that
7:16
creates an incentive for measurable milestones
7:17
rather than promises about eventual hypersonic
7:20
dominance. It also favors companies that can
7:22
work across aviation safety, cybersecurity, spectrum
7:26
coordination and test operations. Suppliers should
7:28
treat interoperability and calibration records
7:31
as competitive assets, not back office paperwork.
7:34
A credible test enterprise lowers uncertainty
7:36
for propulsion developers, materials teams, interceptor
7:40
programs and acquisition officials alike. So
7:43
the larger point is that the United States is
7:46
investing in the infrastructure that makes claims
7:48
testable. That's actually a pretty hopeful framing
7:51
for what could otherwise sound like a very dry
7:53
procurement story. The source puts it well. The
7:56
race worth winning is the ability to learn safely,
7:58
quickly and honestly at the edge of physics.
8:01
Higher test cadence can reveal weak designs earlier,
8:04
reward manufacturable solutions, and make counter
8:07
-hypersonic sensing more realistic. Knowledge
8:09
compounds when experiments are repeatable and
8:12
data remains trustworthy. Alright, let's go orbital,
8:16
because the Space Command story this week had
8:18
a quote that I thought was pretty blunt for a
8:20
senior military official. General Stephen Whiting
8:23
said that tracking has improved, but targeting
8:25
quality understanding still has a long way to
8:28
go. He identified specific gaps, commercial and
8:32
allied data integration, sensor -to -command
8:34
links, and surveillance capacity. The problem
8:36
he's describing isn't merely seeing an object
8:39
in orbit, it's understanding behavior well enough
8:41
for accountable decisions. So we can see things,
8:44
we just don't always know what they're doing
8:45
or why? That's the gap, and it requires observations,
8:49
identity, intent assessment, command systems,
8:51
and authorized responses to share consistent
8:53
information. Whiting also called for expanded
8:56
awareness beyond geosynchronous orbit and into
8:59
cislunar pathways, that's the Earth -Moon neighborhood.
9:02
That horizon matters because future commerce,
9:04
science and security will increasingly share
9:06
that space. And then there's the workforce piece,
9:09
which had some very specific numbers attached
9:11
to it. Space force leaders described goals of
9:13
25 ,000 uniformed guardians and 12 ,500 civilian
9:17
personnel by fiscal 2031. They linked that growth
9:21
to new missions, more satellites, more combat
9:24
crews, and greater training demand. Officials
9:26
also emphasized live, virtual, and constructive
9:29
environments for testing skills before operators
9:31
face real consequences. That's a significant
9:36
expansion. And the framing around workforce capacity
9:39
being part of program credibility, not a separate
9:42
HR conversation, that feels like a shift in how
9:46
the Pentagon is thinking about this. It is. A
9:48
sensor contract without trained analysts, maintainers,
9:51
instructors and cyber defenders is an incomplete
9:54
capability. The industrial base should plan facilities,
9:57
curriculum, clearances, digital engineering and
10:00
instructor pipelines alongside hardware. High
10:03
value roles include orbital analysts, astrodynamics
10:06
engineers, sensor specialists, data architects
10:09
and command and control integrators. And there's
10:12
a human factors dimension here that I don't think
10:14
gets enough attention. Designing displays that
10:17
communicate uncertainty without overwhelming
10:19
operators. That's one of the premium skills the
10:21
source identifies. Human factors engineers must
10:24
design displays that communicate uncertainty
10:26
without overwhelming operators in time sensitive
10:29
situations. And the source makes a point that
10:32
I think is really important. Leaders should reward
10:34
people who expose data gaps early because orbital
10:37
confidence cannot be manufactured by presentation
10:39
slides. Okay, that line is going to stick with
10:42
me. Orbital confidence cannot be manufactured
10:45
by presentation slides. Let's talk about the
10:48
AI story because this one reframes the whole
10:51
debate in a way I wasn't expecting. So Shield
10:54
AI published an essay on September 17 that made
10:57
a central argument. Defense autonomy is an experience
11:00
problem before it's an algorithm problem. Their
11:03
claim is that public data rarely contains the
11:06
exact threats, sensors, geography and degraded
11:09
links that missions require. Generative systems
11:12
can imitate abundant patterns, but mission autonomy
11:15
must behave predictably where examples are scarce.
11:18
So it's not that the algorithms aren't good enough,
11:20
it's that they haven't seen the right situations.
11:22
That's the argument. And it's worth noting this
11:25
is Shield AI's perspective as a company, not
11:28
an independently verified performance result.
11:30
But the constraint they're pointing to is real.
11:33
Their proposed solution is high fidelity simulation
11:35
that can supply controlled repetitions, rare
11:38
conditions, and inspectable outcomes. A useful
11:41
synthetic environment modeled terrain, atmosphere,
11:44
vehicle dynamics, sensors, communications, and
11:46
causal consequences. And there was separate commentary
11:49
that day about the chain of command question.
11:52
Who actually has authority when an autonomous
11:54
system is operating? Right, and that commentary
11:57
proposed explicit chains of command and delegation
11:59
limits for defense AI agents. The framing is
12:03
that machines can search, correlate, navigate,
12:05
recommend, and execute bounded tasks faster than
12:08
a person. But people still define objectives,
12:11
interpret context, approve consequential actions,
12:14
and remain accountable for mission outcomes.
12:16
That's not a technical constraint, it's a design
12:19
choice that has to be made deliberately. And
12:21
multi -agent systems make this even more complicated,
12:24
right? Because software might delegate tasks
12:26
across cooperating components. Exactly. Procurement
12:30
tests should therefore examine coordination,
12:32
override behavior, logging, and degraded communications,
12:35
not just accuracy averages. Teams also need to
12:38
know when an autonomous system is outside the
12:40
conditions represented in training. Trust grows
12:43
when the interface makes uncertainty visible
12:45
and the organization rehearses intervention without
12:48
drama. That phrase, rehearses intervention without
12:51
drama, is doing a lot of work because the failure
12:55
mode is that you only find out the override doesn't
12:58
work when you actually need it. And the workforce
13:00
implications are significant. Simulation designers
13:03
need physics, geospatial data, sensor modeling,
13:06
scenario authoring, and interoperability standards.
13:09
Machine learning engineers need data lineage,
13:11
evaluation design, edge deployment, and methods
13:14
for measuring behavior over time. Operators need
13:17
enough AI literacy to challenge recommendations
13:19
without becoming part -time model developers.
13:22
Ethics, safety, and legal specialists belong
13:24
inside the engineering loop, where authority
13:27
is designed rather than explained later. That
13:29
last point is interesting, ethics inside the
13:32
engineering loop, not bolted on afterward. Let's
13:35
get to the cyber security story, because CISA
13:38
published something this week that I think changes
13:40
how a lot of organizations should be thinking
13:42
about their defenses. CISA published guidance
13:44
on September 16 on cyber decoys for critical
13:47
infrastructure, and the framing is important.
13:50
Decoys are a complement to zero trust, not a
13:53
replacement for it. The guidance addresses a
13:55
specific problem. intruders who use valid credentials,
13:58
native tools, and living off -the -land techniques
14:00
after gaining access. Those are the hardest attackers
14:03
to detect because they look like legitimate users.
14:06
So a decoy is basically a fake asset that no
14:09
legitimate user would ever touch. And if someone
14:11
does touch it, that's your signal. That's exactly
14:14
right. CESA describes tripwires, breadcrumbs,
14:18
honey tokens, and honeypots as related tools
14:20
with different complexity. Tripwires alert on
14:23
interaction Breadcrumbs guide suspicious exploration,
14:26
and honey tokes are monitored pieces of fake
14:28
data. Honeypots provide more complete simulated
14:31
systems but demand stronger isolation, logging,
14:34
and expertise. Because legitimate users should
14:37
not touch well -designed decoys, alerts can reduce
14:39
noise and accelerate investigation. And CESA
14:42
organizes the planning around Mitre Engage and
14:45
Mitre AT &CK, so this isn't just a theoretical
14:48
framework, it's tied to real adversary behavior.
14:51
Right. The aim is to expose intruders, impose
14:54
cost, or safely gather intelligence under controlled
14:56
conditions. And the design challenge is believability
15:00
without creating new pathways into production
15:02
systems. That's a real engineering problem, not
15:05
just a configuration task. What I find genuinely
15:08
interesting about this is the mental model shift.
15:11
Defenders aren't just building walls, they're
15:13
reshaping the environment so that suspicious
15:15
intent becomes visible. That's a fundamentally
15:18
different posture. And the source captures it
15:20
well. Zero Trust verifies every access decision,
15:23
while decoys create places where suspicious intent
15:26
becomes easier to see. That pairing can help
15:28
protect defense networks, launch infrastructure,
15:31
energy systems, water operations, and supplier
15:34
ecosystems. The guidance is also explicit that
15:37
decoys support detection and response. They don't
15:40
replace identity, patching, segmentation, or
15:42
recovery controls. So it's not a silver bullet.
15:45
It's an additional layer that makes the whole
15:47
system smarter. Exactly. And CISA frames this
15:50
as a clear workforce development lane for organizations
15:53
with limited security staff. Analysts can learn
15:56
threat -informed detection, triage, and evidence
15:58
handling through contained lab exercises. System
16:01
administrators can map normal access paths and
16:04
identify places where suspicious interaction
16:06
would be unambiguous. Threat intelligence teams
16:09
can translate adversary behavior into defensive
16:11
hypotheses instead of just collecting reports.
16:14
And for vendors, the market opportunity is strongest
16:17
where deception integrates with tools customers
16:19
already operate, endpoint, identity, network,
16:23
cloud, security analytics. That's the key procurement
16:26
signal. Buyers will value interoperability, and
16:29
they'll need lifecycle features for ownership,
16:32
testing, documentation, retirement, and false
16:34
positive review. Managed service providers can
16:37
help smaller contractors gain expertise, but
16:39
accountability cannot be entirely outsourced.
16:42
The credible business case is incremental improvement
16:45
measured against each organization's threat model
16:47
and response capacity. Okay, so when you step
16:50
back from all five of these, the Mojave drone,
16:53
Skyrange, Space Command's orbital gaps, S .H
16:56
.I .E .L .D. AI's simulation argument, and CESA's
16:59
decoy guidance, what's the through line? What
17:02
are they all actually saying together? The through
17:04
line is that the defense industrial base is becoming
17:06
more distributed, more data -driven, and more
17:09
dependent on evidence rather than promises. Mojave
17:12
shows that ISR can move with the force instead
17:14
of being anchored to fixed airfields. Sky Range
17:17
shows that the learning cycle for advanced weapons
17:19
depends on test infrastructure as much as the
17:21
weapons themselves. Space Command shows that
17:24
orbital security is a data integration and workforce
17:27
problem, not just a sensor problem. And the AI
17:29
and cyber stories fit that same pattern. They
17:32
do. Shield AI's argument is that autonomy earns
17:35
authority through evidence, through simulation,
17:38
through inspectable outcomes, through rehearsed
17:40
intervention. And CESA's decoy guidance is about
17:43
making the environment itself more informative,
17:45
so defenders learn faster than attackers can
17:47
adapt. All five developments reward organizations
17:50
that can document what they know, expose what
17:52
they don't, and build systems that get smarter
17:54
over time. And the workforce implications are
17:57
consistent across all five as well. It's not
17:59
just technical skills, it's the ability to translate
18:02
between physics, software, mission authority,
18:05
and coalition trust. That's the premium skill
18:07
set. and the source material is consistent on
18:10
this, the industrial base should plan curriculum,
18:13
clearances, digital engineering, and instructor
18:15
pipelines alongside hardware. A contract without
18:18
the trained people to execute it is an incomplete
18:20
capability. That's true whether you're building
18:23
a drone, a test range, a satellite constellation,
18:26
an autonomous system, or a cyber resilient network.
18:29
Here's what this really comes down to, I think.
18:32
The defense industrial base isn't just being
18:34
asked to build faster or cheaper, it's being
18:37
asked to learn faster, to generate evidence,
18:39
to expose gaps, to make uncertainty visible before
18:42
it becomes a crisis. And that's a genuinely different
18:45
ask than what the industrial base has historically
18:47
been optimized for. The old model rewarded scale
18:50
and stability. The emerging model rewards adaptability
18:53
and epistemic honesty, knowing what you know,
18:56
knowing what you don't, and building systems
18:58
that can tell the difference. Epistemic honesty
19:00
in defense procurement. That's not a phrase you
19:03
hear every day. And yet, it's exactly what all
19:06
five of these developments are pointing toward.
19:08
Mojave's demonstration didn't prove every operational
19:10
claim, it showed a physical aircraft completing
19:13
a difficult sequence under representative conditions.
19:16
Sky Range's value isn't a guaranteed weapon,
19:18
it's the infrastructure that makes claims testable.
19:21
Space Command's warning wasn't about capability,
19:23
it was about the gap between what we can see
19:25
and what we can understand. Shield AI's argument
19:28
wasn't about algorithm superiority, it was about
19:31
where the training data comes from. And CSIS
19:33
guidance wasn't about guaranteed detection, it
19:35
was about incremental improvement measured against
19:37
your actual threat model. So the actionable insight
19:40
for anyone in this space, contractor, supplier,
19:43
workforce, professional, acquisition officer,
19:45
is to ask the evidence question. Not can this
19:48
system do the thing, but how do we know it can
19:51
do the thing, and what happens when conditions
19:54
change? That's the question that separates the
19:57
organizations that will thrive in this environment
19:59
from the ones that won't. And it applies at every
20:02
level, from the prime contractor to the small
20:04
firm supplying a single component to the analysts
20:07
sitting in front of an orbital tracking display.
20:09
We started this episode with a drone landing
20:11
on a tank trail. And I think that image is actually
20:15
a pretty good metaphor for everything we've talked
20:17
about today. The defense industrial base is learning
20:20
to operate in terrain it wasn't originally designed
20:23
for. Rougher. more distributed, more uncertain,
20:28
and the organisations that figure out how to
20:30
land and take off again in those conditions are
20:32
the ones that are going to matter. That's the
20:35
new defence stack. Thanks for being here on Copilot
20:39
Podcasts. We'll see you next time.