Sayan Chatterjee

I believe your goal as a leader is to do whatever it takes to improve performance. Leaders should identify areas of improvement and actively work to reduce blockers for their teams. For health/family issues, give the team member enough break time to heal before they can come back to work 100%. There should be absolutely no surprises, provide constructive feedback asap. Be specific, do not wait until the quarterly/annual review cycle for this dialogue. Discuss it at your weekly 1x1s. Better to use the review cycles to recognize their success and contributions.

This is especially true in the current ecosystem where every industry will be impacted by AI. Allocating budget/resources for continuous learning will be key for leaders to keep their teams motivated and engaged. In the past, I've allocated some % of Sprint Planning to cross train engineers across their subject matter expertise (eg Andriod developers train iOS developers and vice versa). Providing access to MOOC platforms (Coursera, Udemy etc) is an effective way to train your team. Also allocating some dedicated time at weekly 1x1s and encouraging your team about continuous learning would be significantly beneficial.

I've always encouraged my team to use MOOC platforms (Udemy, Coursera etc) to get the training they need. Engineering hackathons have also been great tools for taking new product improvement ideas from ideation to implementation. Allocating budget/resources for creative projects during Quarterly planning has also been a game changer.

I believe in trust, psychological safety and learning from failure culture. Looking back on my engineering leadership career, the places I’ve worked best offered all of them. My engineering leadership principles have been Build fast -> Ship fast -> Fail fast -> Learn from mistakes fast and repeat that cycle. I believe an organization's culture that encourages risk taking and understands that failure is part of future success can bring the best performance out of their employees.

I believe the MOOC platforms (Coursera, Udemy etc) are excellent ways for continuing education. That's especially true for emerging trends like AI/ML. Couple of my personal favorites are Generative AI with Large Language Models (at Coursera) and Deployment of Machine Learning Models in Production MLOps (at Udemy). Both courses were very hands on and helped me build applications real time. Other than MOOCs, the major cloud providers (AWS, GCP, Azure) offers free AI/ML courses. Youtube also is an excellent resource. But most importantly, imo the drive/tenacity for continuous learning should come from inside that'll propel you to the next level ("The tools for learning are abundant, it’s the desire to learn that’s scarce." - Naval Ravikant).