Algorithmic trading, often referred to as algo trading, has revolutionised the world of financial markets. It involves the use of automated systems and computer algorithms to make trading decisions and execute orders. Algorithmic trading strategies offer the potential for increased efficiency, speed, and precision in trading, but it is not without its challenges and pitfalls. Successful algo trading requires a deep understanding of markets, disciplined risk management, and the ability to adapt to changing conditions. It's a world where technology and human decision-making intersect and where even the smallest mistake can lead to significant financial losses. Here, we will explore the top seven mistakes to avoid in algorithmic trading strategy development. These mistakes encompass various aspects of trading, from inadequate research and overreliance on automation to poor risk management and emotional decision-making. By understanding and avoiding these common pitfalls, traders can enhance their algorithmic advanced trading strategies and increase their chances of success in today's dynamic and competitive financial markets.