The Air Force’s DASH 2 (Decision Advantage Sprint for Human-Machine Teaming) experiment reinforced something Rackner has been building toward for a while: decision advantage isn’t about collecting more data, it’s about turning information into action faster, with humans still in control.
DASH 2 showed that AI-enabled decision services can generate decision options at a scale and speed humans alone can’t match. The value isn’t “automation for automation’s sake.” The value is giving battle managers more viable options sooner, with enough transparency to support confident decisions under pressure. That’s exactly what REAPER is built to deliver.
Rackner’s work aligns with the exact gap DASH 2 is targeting: the cognitive bottleneck between seeing the battlespace and choosing what to do next.
REAPER addresses that bottleneck through a modular approach to battle management, delivering composable decision functions that can be tested quickly, improved iteratively, and integrated into existing workflows without forcing operators into a single monolithic system.
Instead of trying to build one platform that does everything, REAPER enables battle managers to plug in the decision support they need, where they need it, when they need it.
In practice, decision advantage requires multiple decision functions working together. DASH 2 emphasized that flow by pushing beyond “understanding” into “execution.”
REAPER supports that end-to-end progression through two foundational capabilities:
Perceive Actionable Effects (PAE): making raw operational inputs usable by structuring them into actionable effects
Match Effectors (MEF): turning those effects into executable options by identifying the best available assets to achieve them
DASH 2 is where that second capability became real. By delivering MEF, REAPER helped translate operational intent into actionable recommendations, pairing effects with effectors based on constraints like readiness, timing, risk, and operational priorities. This is the kind of human-machine teaming that scales, because it doesn’t replace the decision-maker. It accelerates them.
DASH 2 validated a direction Rackner is already built for: fast, modular, explainable decision support that works in real operational environments.
REAPER proved that the future of battle management won’t be judged by whether AI can produce an answer. It will be judged by whether AI can produce multiple good options, fast enough to matter, and clear enough for operators to trust.