Traditional design processes like formal crits were built for a slower, larger-scale era. At Cash App, they systematically delete processes that don't add value, finding that many have become performative rituals that slow down high-velocity, AI-powered teams.

To enforce its "the best part is no part" philosophy, SpaceX has a rule: if you aren't adding back at least 10% of the requirements you previously deleted, you aren't being aggressive enough. This counter-intuitive metric ensures engineers continuously question and simplify designs.

Musk encourages his teams to be so aggressive with simplification that they sometimes go too far. The need to occasionally reinstate a deleted part or process is not a sign of failure, but proof that the deletion effort is appropriately aggressive and pushing boundaries.

Instead of iterating on existing solutions, Musk's approach is to start with an ideal, 'theoretically perfect' product and work backward to determine the tools and methods needed to create it. This pushes teams beyond incremental improvements and toward fundamental breakthroughs.

The most critical step in optimization isn't the "how," but the "what" and "why." Before implementing any efficiency hack, interrogate your underlying goal. Without this, you risk becoming highly efficient at unimportant tasks or chasing goals shaped by external pressures rather than your own values.

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.

An engineering team's velocity is often bogged down by non-engineering work, which can consume a significant portion of their time. A leader's primary role in accelerating projects is to identify and systematically remove these obstacles, freeing engineers to focus on creative problem-solving and core design tasks.

The default instinct is to solve problems by adding features and complexity. A more effective design process is to envision an ideal, complex solution and then systematically subtract elements, simplify components, and replace custom parts. This leads to more elegant, robust, and manufacturable products.

Don't just plug AI into your current processes, as this often creates more complexity and inefficiency. The correct approach is to discard existing workflows and redesign them from the ground up, based on the new paradigms AI introduces, like skipping a product requirements document entirely.