The core bottleneck in agile manufacturing isn't the machinery, but the manual creation of work instructions, often done in PowerPoint. This slow, error-prone process prevents rapid iteration and keeps factory workers operating on outdated information. Automating this "atomic unit of information" is critical to creating a robust industrial base.

In complex systems (e.g., electromechanical devices with software), problems often arise not within a single discipline but in the interactions between them. Engineers must adopt a systems-level view to anticipate and address these "undefined requirements" where different components intersect.

The most common failure in automation is focusing on the robot or software. True success is determined by deeply understanding and codifying the entire process, including its environment and inherent variabilities. Getting the requirements right is the core challenge; the technology itself is secondary.

When screw lengths differ by only a few millimeters, assemblers can easily use the wrong one. This may seem to fit correctly but results in insufficient thread engagement, compromising the product's structural integrity, especially under stress like thermal cycling.

A key lesson from SpaceX is its aggressive design philosophy of questioning every requirement to delete parts and processes. Every component removed also removes a potential failure mode, simplifies the system, and speeds up assembly. This simple but powerful principle is core to building reliable and efficient hardware.

When scaling to production, the biggest pitfall is the implicit knowledge held by the original design team who unconsciously fill procedural gaps. To succeed, involve someone with a manufacturing background but no project history to rigorously review procedures and expose these unstated assumptions before scaling.

Designers should consider the human operators and machines that will assemble their product. By making choices that simplify manufacturing—providing clear instructions and avoiding known difficulties—the process becomes smoother and more efficient, akin to 'riding a bike downhill.'

Choosing a modular, reworkable product architecture can save money during early development. However, this approach often creates operational complexity that is difficult to scale. This strategy is only viable if there's a clear plan and trigger point to transition to a more fixed, scalable design.

Experts often design components in isolation, perfecting their specific 'Lego' piece. When it's time to assemble the final device, these pieces fail to fit together because a systems-level approach was missing from the start, leading to costly rework and integration challenges.