👋 , I’m Alessandro—a writer, engineer, and strategist based in Rome, Italy.

AI and the future of knowledge work

Around 1900, a factory that wanted electricity had to make it. Power was a capability you built in-house, with your own generators, your own plant, and your own staff to run it; as late as 1909, 64 percent of the electric motor capacity in US manufacturing still ran on power generated on site.

Efficiency must be defensible

If you invest in a business improvement attainable by everyone else, you have not created a competitive advantage. At most, you have ensured you don’t fall behind and unlocked the capacity to deploy to work on more meaningful innovations.

AI moves validation downstream

When the cost of production is high, validation needs to happen at the planning stage; when the cost of production is low, it’s easier to just produce whatever thing needs to be tested (software, copy, creative, etc.) and see how it performs in the wild.

All good strategies are unique

When devising a business strategy (or what they think is one), companies too often look at their competitors or other similar players and try to reverse-engineer what they are doing. They do this because they want validation that the path they are on is worth pursuing.

Competitive advantage is your value-cost gap

Your competitive advantage is most easily quantified as the gap between the perceived value of your products (i.e., your pricing power) or services and the cost you incur to deliver those services.

Economies of scale are not exclusive

While access to economies of scale does create efficiencies, it is not a competitive advantage per se.

Tacit knowledge is hard to capture

While explicit knowledge can be captured, tacit knowledge cannot be captured—or at least, not in a very practical way.

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