Unlike national defense, which benefits from centralized R&D from organizations like DARPA, the U.S. fire service is highly fragmented across 20,000 independent departments. This structure has historically stifled the adoption of advanced technology, creating an opportunity for private companies to fill the innovation gap.

By coining the term 'low altitude economy,' China is signaling a deliberate, top-down industrial strategy to own the market for autonomous flying vehicles (EVTOLs) and delivery drones. This isn't just about a single company; it's about creating and regulating a new economic sector to establish a global manufacturing and operational lead.

Block's CTO argues that LLMs are a wasted resource when they sit idle overnight and on weekends. He envisions a future where AI agents work continuously, proactively building features, running multiple experiments in parallel, and anticipating the needs of the human team so that new options are ready for review in the morning.

The strategic advantage isn't fighting huge blazes, but extinguishing fires within the first 10-20 minutes when they are small and manageable. This prevents the exponential growth that leads to megafires, a concept often missed due to media's focus on large-scale disasters.

Avoid deploying AI directly into a fully autonomous role for critical applications. Instead, begin with a human-in-the-loop, advisory function. Only after the system has proven its reliability in a real-world environment should its autonomy be gradually increased, moving from supervised to unsupervised operation.

Autonomous systems can perceive and react to dangers beyond human capability. The example of a Cybertruck autonomously accelerating to lessen the impact of a potential high-speed rear-end collision—a car the human driver didn't even see—showcases a level of predictive safety that humans cannot replicate, moving beyond simple accident avoidance.

The evolution of Tesla's Full Self-Driving offers a clear parallel for enterprise AI adoption. Initially, human oversight and frequent "disengagements" (interventions) will be necessary. As AI agents learn, the rate of disengagement will drop, signaling a shift from a co-pilot tool to a fully autonomous worker in specific professional domains.

While on-device AI for consumer gadgets is hyped, its most impactful application is in B2B robotics. Deploying AI models on drones for safety, defense, or industrial tasks where network connectivity is unreliable unlocks far more value. The focus should be on robotics and enterprise portability, not just consumer privacy.

AR and robotics are bottlenecked by software's inability to truly understand the 3D world. Spatial intelligence is positioned as the fundamental operating system that connects a device's digital "brain" to physical reality. This layer is crucial for enabling meaningful interaction and maturing the hardware platforms.