Models of Scale

There are essentially two models of scale for an organisation: people and tech. To scale, you either hire more people or use tech to have one of your people do more. 

In the past, people were the primary driver in scaling an organisation. Charismatic founders, like Richard Branson, attracted and retained great talent and therefore created some of the most productive companies. However, recent technological developments now allow the majority of internal, human-dependent tasks to be automated via no-code tools such as Make and Lindy AI. Bespoke agentic AI and custom LLMs further drive this shift, accelerating automation in tandem with progress in code generation.

What Comes Next?

My prediction is that the “tech factor” will surpass the “people factor.” We will see unicorn companies run by very few individuals (often fewer than ten), and hence a different type of founder personifying success in entrepreneurship. 

In the software world, far fewer successful founders will resemble the 'Richard Branson persona', while more will embody hyper-logical tech generalists like Elon Musk, Mark Zuckerberg, Bryan Johnson, and Larry Ellison. This is because these founders scale organisations primarily through tech, which will surpass people as the main factor of scale.

Moreover, with fewer people, less alignment is needed as communication channels scale((n^2-n)/2). With considerably fewer people, leaders need to spend less time on alignment and more time enabling their people to automate their and others’ work.

I suggest that founders, especially those with little tech knowledge, will increasingly spend a considerable amount of their time understanding how to write code, practicing abstract thinking (especially for automation), and learning about artificial intelligence – which requires understanding of stochastics, statistics, geometry, and iterative logic in code. This will be infinitely more useful now than it would have been a decade ago. It’s not about having to write code yourself, but understanding a fundamental model of scale for your organisation.

Previously, understanding these concepts was simply a 'nice-to-have' that fostered empathy between founders—or between founders and technical staff. Now, it is essential for making the right decisions about scaling a company. Founders who fail to prioritise this will lose significantly to competitors who automate through code first and rely on people second.

Factors of Organisation Effectiveness

When I think about the overall effectiveness of an organisation, it looks like this:

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Overall Effectiveness = Quantity of People • Alignment Factor • Efficiency Factor

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More people get more done, but only under two circumstances. The efficiency of the additional person should be greater than 0. Moreover, people should not work on the same things or on anything that isn't required – a principle I refer to as the alignment factor.

For instance, if your employees spend 50% of their time on overlapping tasks or irrelevant tasks, your alignment factor is 0.5. It should be in the interest of every founder to get the alignment factor as close to 1 as possible. With less people achieved by means of automation, keeping the alignment factor high will be easier. Finally, a look at the efficiency factor shows two essential components in its formulation:

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Efficiency Factor = Automation Factor • Quality Factor (Individual Output)

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‍The automation factor is essentially tech. The interesting thing about tech is that it is theoretically infinitely scalable. While the alignment factor can never be higher than 1, the automation factor could be 50 or higher. One person can now automate work within one organisation that replaces 50 people. While a great hire might have been twice or three times as productive as a bad hire, possibly even 10 times more effective in roles such as sales and marketing, the automation factor starts to outweigh the quality factor. Moreover, there is a relationship between the quality factor and the automation factor. The higher the quality of a talent, the better and more scalable the code and automations they create. With less people needed, founders can spend even more time on attracting quality talent rather than hiring fast. 

Thus, my conclusion is thatthose capable of driving the automation factor up by magnitudes of 50 to 100 will dominate organisational productivity. A new type of founder, one who is stellar at tech, abstraction, and judging talent (rather than merely attracting it), will dominate the next era of tech ventures.

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