Algorithm efficiency and project deadlines are both critical but vary depending on the project type. For non-iterative projects (one-time deliverables), both must be prioritised since there's no chance for revisions. A solid design, efficient algorithms, and comprehensive code reviews are key to ensuring performance and meeting deadlines. In iterative projects (multiple releases), there’s more flexibility. Deadlines can be prioritized, with algorithm optimization addressed in later iterations. In both cases, careful planning, design, and communication are essential for success.

Striking a balance between efficiency and deadlines is always a challenge! I usually start by aligning with the team on the project's core priorities, whether speed or accuracy takes precedence. Then, I work on creating a baseline solution quickly and optimize iteratively, focusing on the areas that bring the most impact. Setting clear milestones and regularly reviewing progress helps in keeping both the team and the project on track.

Balancing algorithm efficiency and project deadlines requires clarity and strategy: 1. Define Priorities: Understand the end goal—prioritize speed for time-sensitive deliverables, accuracy for critical systems. 2. Iterative Approach: Start with a basic, functional solution. Optimize only where bottlenecks or precision gaps arise. 3. Timeboxing: Allocate fixed time to improvements; avoid over-engineering under tight deadlines. 4. Collaborate: Align team members on trade-offs, ensuring shared ownership of priorities. 5. Leverage Tools: Use profiling tools to pinpoint inefficiencies and focus optimization efforts. My strategy? Begin simple, iterate smartly, and continuously communicate trade-offs to stakeholders. What works for you?

My approach - - Dedicate 60% time in creating HLD and LLD before jumping into the code - Create a MVP utilising 20% percent of time, just focus on writing clean code at this step , not on the overall performance - Raise a PR at this stage and ask for Code reviews. - Iterate over the code and identify optimisations and potential failure points - Accomodate valid PR reviews and your own improvements as the final step of code delivery

It is always said to first make something working before improving its efficiency.If the product passes all the test cases and there is some time before the deadline, then we can improve the efficiency.