
Accelerate Decisions, Dominate Operations, and Dunedain with Mack Ohlinger
Why accelerating decision-making—not just building models—is the real frontier of defense AI
Guest: Mack Ohlinger – CEO, Dunedain
Most AI conversations in defense focus on models, data, or compute. This one does not. Mack Ohlinger, CEO of Dunedain, is building agent-based systems designed to compress military planning and decision-making timelines from days to seconds. This episode breaks down what actually matters: architecture, user interaction, and the hard reality of getting AI from demo to production.
Topics
- Building agent-based AI systems for military planning workflows (MDMP/MCPP)
- Why most AI companies fail between demo and production
- The role of architecture, testing, and user interaction in mission-grade AI
Takeaways
- The core constraint in defense is decision speed, not access to data or models.
- AI systems that succeed mirror existing cognitive workflows and compress them, rather than replacing them outright.
- The gap between demo and production is driven by integration, edge cases, and real user behavior—not model performance.
- High-quality data is necessary but insufficient; systems must continuously learn from users in real environments.
- Modular, MOSA-aligned architectures introduce integration complexity that must be actively managed.
Timestamped Highlights
[00:00] – Intro and mission: accelerating decision-making in defense
[02:30] – From operator experience to startup: identifying the planning bottleneck
[07:00] – Why most AI demos fail to survive contact with real users
[10:30] – The challenge of testing stochastic, multi-agent systems
[18:00] – How to frame AI capability for defense customers (KPPs, outcomes, trust)
[26:00] – Decision-making under changing requirements and dynamic missions
[28:30] – The future: AI-enabled planning from the CoCom level to the individual operator
Resources & Links
- Mack Ohlinger — https://www.linkedin.com/in/mack2
- Dunedain — https://dunedainsystems.com/
“The hardest part is not building the system. It’s getting from 99% to 100%—from demo to production.”
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