The Five Step Algorithm
ProductivityQuestion requirements, delete steps, optimize, accelerate, and finally automate in that specific order to avoid wasting effort on unnecessary tasks.
3 more supporting quotes are in the member records.

일론 머스크
An entrepreneur and engineer leading Tesla and SpaceX, known for applying first-principles physics thinking and rapid iteration to manufacturing and aerospace.
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Principles are our summary of their public statements.
Question requirements, delete steps, optimize, accelerate, and finally automate in that specific order to avoid wasting effort on unnecessary tasks.
3 more supporting quotes are in the member records.
Deliberately delete more than necessary to ensure the process is lean; if nothing is ever added back, the deletion wasn't aggressive enough.
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Over time, rules and bureaucracy naturally accumulate until they stifle all progress; active effort is needed to remove them.
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Human nature remains constant, meaning civilizations and organizations follow predictable patterns of rise and fall.
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Choose unconventional materials if they solve specific technical hurdles, such as using polymers instead of metal for electromagnetic transparency.
Create a culture where people passionately defend their ideas and clash like rocks in a tumbler to produce a refined result.
Working closely with the first users of a clinical trial or product launch helps developers understand the nuanced impact and real-world utility of the technology.
Progress requires a clear, quantifiable metric that allows different approaches and competitors to be compared objectively.
Product improvements often come from observing how a user interacts with the system day in and day out, revealing needs that developers could never have anticipated.
Musk followed a strategy of starting with a premium sports car for early adopters to fund the development of more affordable, mainstream vehicles.
If regulatory hurdles and slow utility industries make ground-based scaling impossible, move operations to environments with fewer permits and higher efficiency.
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Use a small fleet of real-world units to validate and refine data generated by millions of simulated units to ensure AI training translates to reality.
Set the most aggressive deadlines possible that still have a 50% chance of success to maximize speed and identify bottlenecks.
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