10x MandateThe only constant in life is change itselfNarrator In a world built on routines, most people accept the old ways—until something truly better arrives and makes the past seem unbearable.Mrs. Parker Timmy, why do you think people stick to the same old things, even when they don’t work well?Timmy Because, Mrs. Parker, changing is scary! And you might lose the stuff you already have. Unless… the new thing is way, way better—like ten times better!Mrs. Parker But how do inventors actually make something 10x better? Is it just luck, or is there a playbook?Timmy They take things apart—unbundling! And then make each piece work together faster, using plug and play. But some things just can’t be sped up, no matter what.Mrs. Parker So if you try to make the plug and play system perfect, the system gets brittle and breaks when the world changes, right?Timmy Exactly! But AI has a cool trick: instead of rebuilding everything again and again, you build a loop that learns from mistakes and gets smarter every time.Mrs. Parker So, the secret isn’t in rigid rules, but in creating a system that learns and adapts. That way, the solution keeps getting better—almost on its own!quotes: The 10x Mandate Often, you don't realize how bad something is until a truly good alternative appears, suddenly revealing the old way as intolerable. However, human nature resists change. Due to switching costs, loss aversion, and status quo bias, getting people to move is incredibly difficult—unless the new thing is at least 10 times better. When a solution is 10x better, it's surprising how fast demand can shift, like water turning to ice. The ingredients to create such a solution often already exist. The innovation lies in unbundling a currently unscalable system and optimizing it to hit a specific price point with healthy margins. As Jim Barksdale said, "There are only two ways I know of to make money: bundling and unbundling." The Architectural Playbook Critical Path Analysis shows us the path to unbundling. The goal is to use Dependency Inversion—where high-level and low-level modules depend on abstractions (APIs), not on each other—to parallelize formerly serial steps. This approach, however, runs into a fundamental limit described by Stephen Wolfram's Computational Irreducibility, which states that some steps in a complex process cannot be parallelized and must be computed serially. The trick is to identify the few, true, minimal, and independent causal chains and parallelize everything else. Amdahl's Law then helps quantify the potential speedup from these improvements and reduce waste. The Brittleness Trap This structural optimization creates a problem: a brittle system. When foundational constraints change, as they always do thanks to forces like Moore's Law, the entire system can be disrupted. This puts you on a treadmill, constantly re-architecting just to keep up. The AI-Native Solution The "Bitter Lesson" of AI shows the way out of this trap. Don't waste time building things that will be replaced. The rules and logic you write in code don't matter in the long run; platforms, tools, and logic are all ephemeral. The only durable strategy is to build systems-level data pipelines. This creates a system that learns and adapts instead of breaking through a continuous loop: Find the edge cases where the system fails in production. Save these failures as high-value training data. Finetune new models that learn from this data. Test the new models against edge cases and then in the real world to verify they're better than the current ones. Release when ready, and repeat the loop. Crucially, this requires building for scale from the start while always designing for verifiability by instrumenting the end-user experience and capturing exceptions. This is what makes the learning loop robust. The AI-native solution not only creates something truly useful but also comes with a durable moat. @Timmy: Resourceful 8yr old @Mrs. Parker: Unpredictable Examiner +Theme: Rendered in the style of dynamic abstract expressionism, featuring bold, sweeping brushstrokes and vibrant splashes of color. The composition exhibits a sense of movement and energy, with thick layers of paint creating texture and depth. The interplay of contrasting hues and fluid forms evoke an emotional intensity, reminiscent of mid-20th century avant-garde art.
