Incremental process improvement is insufficient for true simplification. Drawing on Elon Musk's method, the goal should be to aggressively delete steps until you remove one that is actually necessary and must be re-added. This counter-intuitive approach ensures you have identified the absolute minimum viable process with no superfluous elements.

Applying AI to an inefficient workflow with unnecessary approvals or handoffs won't solve the core problem. Teams must first optimize their manual processes to be efficient before looking to AI for automation. This ensures AI adds value rather than just automating existing flaws.

Many companies rush to automate messy processes, which only locks in inefficiency. Instead, learn and refine the process by doing it manually first, as early Amazon and DoorDash did. Only automate once the system is optimized, using technology to speed up good systems, not paper over bad ones.

A critical error in AI integration is automating existing, often clunky, processes. Instead, companies should use AI as an opportunity to fundamentally rethink and redesign workflows from the ground up to achieve the desired outcome in a more efficient and customer-centric way.

The biggest gains from AI come not from automating steps in an existing process, but from starting with the desired outcome and co-creating a new workflow with AI. This "first principles" approach leverages AI's capabilities far more effectively than piecemeal automation.

Before implementing AI automation, you must validate and refine a process manually. Applying AI to a flawed system doesn't fix it; it just makes the system fail more efficiently and at a larger scale, wasting significant time and resources.

American Housing Corp's first factory was built for flexibility to iterate on the product, not for automated efficiency. They believe automation is the final step, implemented only after a process is validated and de-risked manually. Trying to automate an unproven process is a common and costly mistake.

Don't put AI on a broken process. Before applying AI, first map and optimize your current workflows. AI can't fix fundamental flaws like too many approvals or unnecessary handoffs; it can only accelerate an already efficient process.

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.