The AI-Native Org: A New Shape for Software Companies
The traditional org chart of a software company, with a small group deciding why, a larger group deciding what, and the broad middle deciding how, is no longer applicable. The rise of AI has compressed the translation layer, making it cheaper and faster to execute on a bad idea. The cost of defining why and what has increased, while the cost of how has decreased. This shift has significant implications for the shape of work and the role of managers.
The middle of the org chart, where most of the translation work was concentrated, is where the most significant changes will occur. The work of translating business intent into product spec, and then into code, is no longer necessary. This means that the roles of engineering managers, who coordinated translation, are at risk. The work that justified these roles is dissolving, and managers need to contribute to the why, what, or trust system to remain relevant.
The agent era has removed the alibi for not being hands-on. The principle of leadership has always been the same – passing down comments is the cheap version of leadership, and the real version is showing what’s possible by doing it. The agent era doesn’t change the principle; it removes the excuse for not being in the work. The hands-on layer is the layer that survives, and the teams that figure out the new shape first will be smaller, stranger, and more opinionated.
The Decision Logic of the AI-Native Org
The decision logic of the AI-native org is centered around the use of agents to perform translation work. This means that the roles of engineers and managers need to change. Engineers need to focus on defining the harness, holding the line on quality, and designing systems that agents can safely operate inside. Managers need to contribute to the why, what, or trust system to remain relevant.
The use of agents has significant implications for the org chart. The ratio of what people to how people is going to flip, and most teams aren’t ready for it. The agent era requires a different type of engineer and manager, one who is hands-on and contributes to the why, what, or trust system. The traditional roles of engineering managers and engineers are no longer applicable, and teams need to adapt to the new shape of work.
The agent era also requires a different type of leadership. The principle of leadership has always been the same, but the agent era removes the excuse for not being in the work. Leaders need to be hands-on, contributing to the why, what, or trust system, and showing what’s possible by doing it.
Winners, Losers, and Disrupted Parties in the AI-Native Org
The winners in the AI-native org are those who can define the why and what, and contribute to the trust system. These are the people who will thrive in the new shape of work. The losers are those who are stuck in the traditional roles of engineering managers and engineers, and who are not able to adapt to the new shape of work.
The disrupted parties are those who are currently in the middle of the org chart, where most of the translation work is concentrated. These are the people who will be most affected by the changes brought about by the agent era. The middle is the dangerous place to be right now, not because middle people are bad, but because the middle is where the translation work is concentrated, and the translation work is the work that’s going.
The agent era also disrupts the traditional org chart. The ratio of what people to how people is going to flip, and most teams aren’t ready for it. The agent era requires a different type of engineer and manager, one who is hands-on and contributes to the why, what, or trust system.
The Skeptical Case for the AI-Native Org
One of the skeptical arguments against the AI-native org is that it relies too heavily on the use of agents, and that this will lead to a loss of control and quality. This argument is valid, but it misses the point that the agent era is not just about using agents, but about changing the shape of work and the role of managers.
Another skeptical argument is that the AI-native org will lead to job losses, as automation replaces human workers. This argument is also valid, but it misses the point that the agent era is not just about replacing human workers, but about changing the nature of work and the role of humans in the org chart.
The Signal to Watch Next in the AI-Native Org
The signal to watch next in the AI-native org is the adoption of agents by software companies. As more companies adopt agents, we will see a shift in the shape of work and the role of managers. We will also see a change in the org chart, as the ratio of what people to how people flips.
Another signal to watch is the development of new tools and technologies that support the AI-native org. As these tools and technologies become more widespread, we will see a further shift in the shape of work and the role of managers.
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By Daniel Cross, Digital Growth Strategist at TrendFlashy
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