"The Lifecycle of Greed and Fear: Engineering Considerations That Product Managers Should Watch out For"

Aviral Vaid

Aviral Vaid

Apr 04, 20243 min read

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"The Lifecycle of Greed and Fear: Engineering Considerations That Product Managers Should Watch out For"

Introduction:

In the relentless pursuit of productivity and getting more for doing less, greed and fear often come into play. This article explores the interconnected nature of these emotions and how they impact both individuals and the economy. Additionally, we will delve into the engineering considerations that product managers should be mindful of when dealing with real-time requirements, data and model dependencies, and data collection methods.

The Lifecycle of Greed and Fear:

Greed, at its core, stems from the innocent idea that one is right, deserving, or owed something for their efforts. It starts with the desire to feel recognized, appreciated, and rewarded. However, this innocent idea can quickly turn into delusion as individuals justify their willingness to push for more than they have put in. Greed is fueled by the desire to believe that one is worth the extra effort and the ability of the economy to validate or challenge that belief.

Conversely, fear manifests when individuals start fearing what else they have to fear. It is a state of constant worry and apprehension, where positivity is overshadowed by negative expectations. Just as individuals were blind to negative aspects when consumed by greed, they become blind to potential positive outcomes when consumed by fear.

Connecting Greed and Fear to Engineering Considerations:

Interestingly, the cycle of greed and fear can also be observed in the realm of engineering considerations that product managers should be aware of. Let's explore how these emotions intertwine with real-time requirements, data and model dependencies, and data collection methods.

1. Real Time Requirements:

Real-time calculations are a crucial aspect of many algorithms. However, determining whether results can be calculated in advance or if they need to be calculated in real-time is a significant consideration. Greed may lead product managers to seek instant results, while fear may push them to prioritize speed over accuracy. Striking a balance between these emotions is crucial for delivering optimal solutions.

2. Data and Model Dependencies:

Data and model dependencies play a vital role in the accuracy and efficiency of algorithms. When data is added or modified, it becomes essential to identify which models need to be re-run or even re-trained. The speed at which these updates occur, known as Service Level Agreements (SLAs), can be influenced by both greed and fear. Greed may prompt managers to rush updates, while fear may cause them to delay or avoid updates altogether.

3. Data Collection Methods:

The method of data collection, whether it is batch or continuous streaming, is another consideration for product managers. Greed may drive the desire for constant data influx, fearing that any delay might result in missed opportunities. Conversely, fear may lead to a reluctance to collect real-time data due to concerns of overwhelming the system. Striking the right balance between these emotions is crucial for efficient data collection.

Actionable Advice:

  • 1. Embrace Rationality: Recognize the influence of greed and fear in decision-making processes. Take a step back to evaluate the situation objectively, balancing the desire for more with realistic expectations.
  • 2. Collaborative Decision Making: Involve a diverse team of stakeholders in engineering considerations. This helps mitigate the influence of individual greed or fear and ensures a more holistic approach to decision-making.
  • 3. Prioritize Long-Term Value: Instead of succumbing to short-term greed or fear, focus on the long-term value and sustainability of engineering decisions. Consider the potential impact on scalability, reliability, and maintainability.

Conclusion:

The lifecycle of greed and fear is a universal force that impacts both individuals and economies. By understanding the interconnected nature of these emotions, product managers can make more informed engineering decisions. By embracing rationality, practicing collaborative decision-making, and prioritizing long-term value, product managers can navigate the complex landscape of engineering considerations with clarity and purpose.

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