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जिंदगी अपनी सीमाओं को चुनौती देने के लिए है || आचार्य प्रशांत (2025)
ललकार
19.7K views
1 month ago
Inner Growth
Startup
Maya
Decision Making
Economic Security
Climate Change
PhD
Success
Description

Acharya Prashant addresses a student's dilemma between a high-paying corporate job at NVIDIA and a successful startup. He explains that while employment is designed for the employer's profit and personal growth is merely incidental, running one's own venture provides structural challenges that lead to inner growth. He notes that parental resistance to risk often stems from a historical background of poverty and starvation, which creates a deep-seated but outdated need for basic economic security. He advises the student to prioritize inner growth over mere outer success, especially since the startup is already revenue-positive. To a PhD scholar, Acharya Prashant suggests completing her degree as it represents a significant learning curve and not a failed investment. He emphasizes the importance of immersion in all activities, asserting that the quality of time and depth of involvement are more important than the quantity of hours. He encourages challenging one's limits in every aspect of life, from academics to physical fitness. Regarding the loss of loved ones, he advises focusing on those who are currently present rather than being consumed by guilt over those who have passed away, as everyone is eventually part of the same cycle of departure. Acharya Prashant clarifies the concept of Maya, explaining that it should be understood as a medium to reach the truth rather than something to blindly succumb to. He describes emotions and desires like lust as chemical processes that must be observed to understand their reality. On the topic of environmental conservation, he dismisses the nihilistic argument that nothing matters because everything ends. He argues that if one cares about their own suffering and survival, they must extend that same care to the planet and other beings. Finally, he states that right decision-making is based on the necessity of the work rather than the certainty of its success.