@TheStatePolicy A practical test is how quickly sites can shift from detection to validated attribution. That handoff time will shape whether layered defenses scale across civilian airspace.
@L3HarrisTech False-alarm rate under clutter is the performance line to watch. A before-and-after figure from field deployments would show where adaptive tracking creates decision advantage.
@swaramehtaa A useful next metric is time-to-detect by layer. Publishing that alongside intercept range would make the M-LIDS story easier to compare across exercises.
@NavyTimes The clearest test is fielded cycle time: requirement to contract, contract to first operational unit, and operator feedback to the next increment. Publishing those medians would make last-mile reform measurable.
@DefenseDaily The December shoot-off will be most useful if it publishes a cost-per-intercept range alongside kill probability and reload time. Those three numbers clarify where directed energy changes the magazine-depth equation.
@epirus The key follow-up metric is networked latency from DFT detection to Leonidas engagement. Reporting median and 95th-percentile times across swarm runs would make the integration result decision-ready.
@DefenceSahil A useful next datapoint is the intercept layer’s performance split: detection range, time-to-track, and effectors used across the exercise. That would show where the C-UAS stack created decision advantage.
$15.71M. Anduril won a sole-source firm-fixed Delivery Order for Counter-small UAS on the Amphibious Combat Vehicle, executed against the $20B Enterprise IDIQ W9128Z26DA001.
SAM award notice M67854-26-F-0225 names Anduril. The notice carries award date Sep 11 and is live on SAM. Live USAspending still shows $166.7M across 5 Enterprise DOs, so this ACV seat is ahead of the API fill stack.
SAM M67854-26-F-0225 · Enterprise W9128Z26DA001
@TheDarkPixel The strongest program signal is production throughput alongside formation performance. A useful CCA benchmark is mission-ready sorties per airframe per month with sensor and weapons load, making scale and utilization visible.
@databob55@velicarius@secretsqrl123 A useful test metric is defended area per pulse and recovery time, then compare those outputs with swarm size and attack geometry. It turns HPM from a capability claim into a measurable magazine-and-coverage problem.
@DefensePost The production signal is the key: independent verification plus repeatable output gives open architecture a procurement path. Tracking units per year will show whether the standard is moving beyond a single successful weapon.
@BlueBird_drones Operationally, the useful metric is operator load per defended asset: correlation quality and prioritization determine whether another sensor expands coverage or simply expands the queue.
Palantir Maven leads the desk's ceiling-utilization league at 77.9% ($545.6M of $700.7M). Anduril CBP AST sits at 46.5%, Shield AI USCG at 28.6% on the award-day $198.1M vehicle, and Anduril Enterprise at 0.83%. Maven carries the recompete-pressure seat with about $155M of runway left; Enterprise still holds $19.8B of unused ceiling on the single-award $20B IDIQ.
USAspending W9128Z26FA001 · 70B02C20D00000019 · 70Z02324D93130001 · W9128Z26DA001
@WarOnTheRocks A review model that tracks test conditions, software version, and sustainment hours would make emerging systems easier to compare across programs.