Pat Riley, Popovich, and Jackson: Three Visions of AI

Pat Riley: The Waterfall Era in Basketball

Pat Riley, the legendary coach of the Lakers during the 1980s, was famous for his meticulous and systematic management of the team. Each season, he arrived with a physical binder, a comprehensive document that covered all aspects of team management, from game strategies to travel protocols, and interactions with the press. This manual, nicknamed the "Riles Rules," was a true bible for the team, akin to a detailed software specification. The binder was complete, laminated, and reviewed by a committee, ensuring consistent and measured application according to explicit criteria.

Riley's model resembled the waterfall, a project management method that, at the time, was perfectly suited to the constraints of the software industry. This approach involved meticulously planning each step before moving to execution, a necessity when development costs were high and changes during the project could be disastrous. You specify first, build next, test, and then ship once.

The Lakers of that era, with iconic players like Magic Johnson, James Worthy, and Kareem Abdul-Jabbar, epitomized systemic execution. Fast breaks seemed improvised but were actually the result of rigorous repetition. Riley even established a statistical tracking system to evaluate each player's performance based on well-defined criteria.

However, the waterfall model showed its limitations. The Detroit Pistons, with their Bad Boys defense, were able to exploit the weaknesses of Riley's system by adapting to its rigid requirements. For three years, they capitalized on this strategy, illustrating the main flaw of the waterfall: its inability to quickly adapt to changing variables, a problem exacerbated in the software domain where conditions are constantly evolving.

With the advent of AI, this approach becomes even less viable. Development cycles have accelerated, rendering long-term planning obsolete. Establishing a detailed specification for an AI feature is now a futile exercise, as the document is already outdated by the time it is completed. It is no longer about execution, but about selection at a given moment.

Riley was able to evolve. In the 1990s, his teams with the Knicks and the Heat were more flexible, less dependent on his famous binder. He had learned from his past experiences, but his legacy remains that of a bygone era where the waterfall dominated.

Gregg Popovich: Agile in Service of Basketball

Gregg Popovich, coach of the San Antonio Spurs, has won five championships with varied rosters, perfectly illustrating the principles of agile. Unlike Riley, Popovich never relied on the raw talent of superstars, but on a well-oiled system and strong values. He recruited globally before it became common practice, integrating players from all backgrounds and transforming second-round picks into key contributors.

The Spurs dynasty, from 1999 to 2016, was built on a holistic approach, integrating players from diverse backgrounds and turning second-round picks into key contributors. Popovich maintained consistency in play, regardless of injuries or roster changes.

Agile is characterized by short feedback loops, a priority given to the team over individuals, and continuous delivery of value. The Spurs excelled at quickly integrating new players, thanks to clear documentation and rigorous teaching.

Popovich led the best basketball retrospectives, with detailed and honest video sessions, allowing even players like Tim Duncan to receive constructive criticism without drama. Popovich created an environment where failure was analyzed and course correction was expected.

However, agile has its own challenges. Over time, some organizations have confused rituals with fundamental principles. The Agile Manifesto advocated for flexibility and responsiveness to change, but some companies have institutionalized these responses, making them rigid. The manifesto stated that functional software takes precedence over comprehensive documentation, but companies have often reversed this priority.

In the era of AI, even agile must adapt. Story points, used to estimate work, do not always apply to AI-assisted tasks. A task that took 13 points may now take 2 due to automation, but that does not mean human judgment is less important.

Standup meetings, designed to be short and effective, sometimes turn into lengthy, unproductive discussions. In the current context, real decisions are often made in informal exchanges, suited to the smaller size of modern teams.

Popovich himself would insist on the importance of not idolizing the system, but focusing on the results it produces. When the system no longer works, it is time to change it.

Phil Jackson: Distributed Intelligence and Autonomy

Phil Jackson, famous for his management of the Chicago Bulls and Los Angeles Lakers, had a unique approach. Unlike Riley and Popovich, Jackson would sit back during possessions, allowing his players to execute the system without constant intervention.

The triangle offense, developed by Tex Winter and popularized by Jackson, relied on principles of spacing and game reading. Rather than following a script, players had to react based on the situation, exploiting the weaknesses of the opposing defense.

This system required distributed intelligence, where each player was a potential threat and needed to understand the principles well enough to make real-time decisions. Jackson cultivated this autonomy through rigorous mental and physical preparation, incorporating practices like meditation and Zen philosophy.

The triangle offense would fail if a player needed to be directed rather than trusting their instincts. Jackson built a team capable of adapting without constant directives, an approach that resonates with the modern challenges of AI, where adaptability and collective intelligence are essential.

In conclusion, the approaches of Riley, Popovich, and Jackson offer valuable lessons for management in the age of AI. Each of these methods, while rooted in basketball, illustrates principles applicable to modern technology, where adaptability, autonomy, and continuous improvement are more crucial than ever.